16 items tagged "digital transformation"

  • 3 important considerations when strategizing digital transformation

    3 important considerations when strategizing digital transformation

    While business and IT leaders are under pressure to boost their digital transformation plans, they should stop, rethink, and assess before fully diving into a roadmap.

    The question all companies face today isn’t whether to embrace digital transformation, but how to best take advantage of digitalization advancements, especially considering change driven by COVID-19.

    This mean that businesses must rethink their roadmap and long-term planning. Besides taking advantage of lessons learned from previous digital efforts, there are three considerations needed to support these changes: prioritizing the right technology before investing, developing holistic plans for data, and considering new organizational roles.

    1. Prioritize the right tech when digitizing

    IDC reported that businesses will spend $2.3 trillion a year on digital transformation within the next four years, with worldwide digital transformation technology investments set to hit at least $7.4 trillion in the same time period. But before discussing the technology, it's important to note that many digitalization projects fail due to lack of competencies or a misunderstanding of complexity.

    With many technology options available, it can be difficult to gauge what will benefit your organization. Prior to investing in any solution, businesses should conduct thorough quantitative and qualitative research. A qualitative investigation, featuring employee focus groups or interviews, can identify areas where workers need assistance. Quantitative research, leveraging analytics tools, collects data tracking performance, experience or engagement, which can then support the qualitative observations.

    The average digital transformation project has a 45% chance of delivering less profit than expected. Poor planning is to blame for many transformation efforts falling short. A thorough roadmap is needed to keep up with the pace of innovation. One way to do this is to devise both long- and short-term digital plans to meet immediate and future needs.

    Start by creating a cohesive timeline with monthly goals (ROI sales, website visits, etc). A short-term plan should last roughly three to six months, while a long-term plan should last about six to 12 months. To get an accurate picture of performance, organizations should regularly run performance tests on their systems. They can also survey employees to gauge how they are reacting to the technology.

    In order to meet the demand for disruption, companies need to focus on data-driven innovation. This means businesses must consider the aspects of scope complexity and adoption. One element of this is assessing the learning curve for employees. When introducing new technology solutions, whether it be IoT or machine learning programs, you will need to train employees to use it.

    To get a sense of both the learning curve the technology presents, and the scalability of it, consider undergoing a small-scale trial program before investing. This will provide visibility into how the technology performs and how employees react to it. From there, businesses can fully assess whether it is a fit for the company.

    2. Create a data-driven strategy for the long (and short) haul

    It is critical for businesses to devise a holistic plan for data, taking into account whether there are any privacy concerns or how to manage a potential data increase. Often, businesses do not understand how to gain the most value from the data they have. In order to do this, they must conduct a thorough data audit. This consists of identifying the current technology you use and interviewing your teams on how they are leveraging it. This can allow your business to learn what data you have, how to use it and what is still needed.

    3. Prepare your people

    Prioritizing the needs of your workforce is often an afterthought. Businesses must look to hire new talent or create new roles within the organization to help oversee transformation efforts.

    COVID-19 has accelerated the convergence of information and operational technology networks. According to Claroty, sixty-five percent of IT/OT professionals say their networks have become more interconnected since the pandemic began, and 73% expect them to become even more interconnected as a result of it. IDC research also found that 70% of G2000 organizations will have invested in a common IoT platform layer by 2024. With this situation, having a “connected worker” to oversee these changes can extend the life of your transformation. Organizations can drive projects forward and educate their workers by holding workshops on new technologies, providing employees with the opportunity to learn or potentially enter a specialized role within the organization.

    Eight in 10 organizations fast-tracked some part of their transformation this year, and nearly 80% reinvented their business model as a result of the pandemic. To ensure lasting success, organizations need to conduct thorough investigations, trial their technology, and regularly audit results. Investing in new roles and in workforce education will help organizations make the most of digital technology. While COVID-19 has put the pressure on businesses to boost their digital transformation plans, there remains a need to stop, rethink, and properly assess before fully diving into a roadmap.

    Author: Dave Goddard

    Source: InformationWeek

  • A guide to Business Process Automation

    A guide to Business Process Automation

    Are you spending hours repeating the same tasks? Office workers spend 69 days a year on administrative tasks. You might be wishing for a simpler way to get those jobs done.

    An increasing number of businesses are relying on automation tools to take those repetitive tasks off their plate. In fact, 67% of businesses said that software solutions would be important to remain competitive.

    So, how will our workforce change with business process automation? And how will your business develop as the digital transformation era makes things happen faster?

    In this complete guide, we’ll cover:

    • What is Business Process Automation?
    • 5 Business Process Automation examples
      • Accounting
      • Customer service
      • Employee onboarding
      • HR onboarding
      • Sales and marketing
    • The benefits of Business Process Automation
    • What business processes can be automated?
    • Best practices with Business Process Automation

    What is Business Process Automation?

    Here’s a simple definition: Business Process Automation is the act of using software to make complex things simpler.

    (It’s also known as BPA or BPM. The latter means Business Process Management.)

    You can use BPA to cut the time you spend doing every-day tasks. For example, you can use chatbots to handle customer support queries. This uses robotic process automation (RPA). Or, you can use contract management software to get clients to put pen to paper on your deal.

    How else can you use business process automation?

    Business Process Automation examples

    Accounting

    Research has found that cloud computing reduces labor costs by 50%, which is probably why 67% of accountants prefer cloud accounting.

    So, how can you use an accounting automation solution in your business?

    • Generate purchase orders: Purchase orders have long paper trails that can be difficult to keep track of. Prevent that from becoming a problem by automating your purchase orders. Your software creates a PO and sends it automatically for approval.
    • Handle accounts payable: Automating your 'accounts payable' department can take tedious payment-related jobs off your hands. The software scans your incoming invoices, records how much you need to pay, and pays it with the click of a button.
    • Send invoices: Do you send the same invoices every week or month? Use automated invoicing systems to create business rules. For example, you can invoice your client on the 1st working day of each month without having to set a reminder to do it manually.

    Customer service

    Customer service is crucial for your business to get right. But it can take lots of human time, unless you’re taking advantage of these business process automations:

    • E-mail and push notifications: Use machine learning software, like chatbots, to handle incoming messages. The technology will understand your customer inquiry, and respond within seconds. Your customers or business users don’t need to wait for a response from a human agent.
    • Helpdesk support: Do you have an overwhelming log of support tickets? By automating your helpdesk, you can route tickets to different team members. For example, if someone says their query is about a billing issue, you could automatically send their ticket to a finance agent.
    • Call center processes: Think about what tasksyour call center team. Chances are, they’ll send emails once they hang up the phone. Or, they’ll set reminders to contact their lead in a few days. You can automate those repetitive tasks for them to focus on money-making calls with new leads.

    Employee onboarding

    Lots of paperwork and decision-making is involved with bringing on a new team member. However, you can automate most of the onboarding process with automation software. Here are some use cases.

    • Verify employment history: You don’t have to call a candidates’ references to verify they’ve worked there. You can automate this process using tools like PreCheck . This software scans data to find links between your candidates’ names and their past employers.
    • Source candidates: Find the best candidates by automating your recruitment process. For example, you can post a job description to one profile and syndicate it to other listing websites.
    • Manage contracts: Long gone are the days of posting an employment contract and waiting for your new team member to post it back. You can automate this business workflow with document signage software. It sends the document via email and automatically reminds your new team member to sign and return it. It simplifies the entire lifecycle of bringing a new team member on board.

    (Some fear that automation will destroy jobs in this process. Forrester data goes against this: 10% of jobs will be lost, but 3% will be created.)

    HR onboarding

    Your Human Resources teamwork with people. But that doesn’t mean they have to manually do those people-related tasks themselves. You can use the HR process automation for things like:

    • Time tracking: Figure out how much money you’re making per customer (or client) by tracking time. However, you can’t always rely on team members to record their time. It’s tricky to remember! You can automate their time-tracking, and use software to break down the time you’ve spent on each activity.
    • Employee leave requests: Do your staff need to send an email to submit a PTO request? Those emails can get lost. Instead, use a leave management system. This software will accept or decline requests and manage shifts based on absences.
    • Monitoring attendance: Keep an eye on your staff by using an automated attendance management system. You can track their clock-in (and out) times, breaks, and time off: without spying on them yourself.

    Sales and marketing

    Artificial Intelligence (AI) is the top growth area for sales teams, its’ adoption is expected to boost by 139% over the next 3 years. Your sales and marketing team can use business process automation for these sales and marketing activities:

    • Lead nurturing: Don’t rely on sticky notes to remind you of the leads you’re nurturing. You can add them to a CRM. Then, use automation to follow-up with your leads using a premade template or social media message.
    • Creating customer case studies: You can automate surveys to collect customer experience feedback. Add data processing software to pull sentiments from individual feedback submissions. From there, you can find customers likely to make the best case studies.
    • A/B testing: You’re probably running A/B tests on your website to determine which elements work best. Automate that process using tools like Intellimize. They’ll automatically show variations to your visitors, and collect the real-time data to analyze. Pick the one with the best user experience metrics.

    Still not convinced? This could give your business a competitive advantage. Just 28% of marketers use marketing automation software.

    Benefits of Business Process Automation

    The use cases we’ve shared work for any business. But they’re not just 'nice to have'. There are several ways you’ll benefit from business process automation, such as:

    Increased efficiency and productivity: Your automation tools store information in the cloud. This means you can access your systems from anywhere. It’s great for remote or mobile workers who use multiple devices.

    Faster turnaround: You don’t have to complete your day-to-day tasks manually. Sure, you’ll need to spend a few hours creating your automations. But you’ll save time when your software does them faster.

    Cost savings: You might not think that the hours you spend doing certain tasks cost a lot in comparison to the software. But, those hours are salaried; you’re still paying each team member their hourly rate. McKinsey found that 45% of paid activities can be automated by technology. (That’s an equivalent of $2 trillion in total annual wages.)

    Fewer errors: Some studies argue that computers are smarter than the human brain. In fact,  Google found that customers that use custom document classification have achieved up to 96% accuracy. You’re less prone to human errors using business process automation.

    Better team collaboration: With automation software, your entire team can view the processes you’re making with their own account. They won’t need to wait for a suitable time to talk about strategy. They can check the automation processes to see for themselves. Again, this is great for distributed teams who don’t have in-office communication.

    Best Practices with Business Process Automation

    Ready to start using business automation software?

    Avoid diving in feet-first with the first application you find. Refer to these best practices to get the most value out of process workflow automations:

    • Know your business’ needs, and prioritize automation software that helps with them. For example, if your focus is improving customer wait times, look at chatbot-style automations.
    • Write a list of the repetitive tasks, such as data entry, you’ll be able to automate. Do this by asking your team. the people who work in a specific department day-in, day-out. Or, ask your project management team for their advice. Can you find a single process or tool to streamline most of their tasks?
    • Start training your entire team on how to use the process automations. Some applications offer this type of support as part of your purchase. IBM, for example, have a Skills Gateway.

    The final thing to note? Don’t rush into business process automations.

    Start small and get used to how software is used. Then, ask your team for feedback. It’s better to be safe than sorry with this type of business decision, especially when your business is at stake!

    Author: Matt Shealy 

    Source: SAP

  • Automating your organization in a couple of months through 4 steps

    Automating your organization in a couple of months through 4 steps

    Make automation a reality in the next 60 to 90 days

    Over the past three years, companies that scaled intelligent automation across their enterprises outperformed their peers in profitability, revenue growth and efficiency. And that performance gap is expected to widen over the next three years.

    This probably doesn’t surprise you. After all, you’re reading this blog. It’s also not news to you that automation is difficult, especially in an enterprise.

    Learning about automation approaches is definitely important, and so is starting in the right place.

    To help make sure that you’re set up for success, we’ve put together four steps you can take in the next 60 to 90 days to make automation a reality in your business.

    Step 1: Determine your goal

    At the end of the day, what are you hoping to achieve with automation? Do you want to provide better customer support? Are you trying to improve business processes so that your workers can focus on higher-quality tasks? Do you want to enable your employees to complete their work in less time so that they can spend more time with their families?

    The more specific you can be, the better. For example, CDG Prévoyance didn’t just want to improve their customer experience; they wanted to “provide the best service to our customers in a shorter amount of time and in the most effective channel.” For ENN Group, it was to drive clean energy options that improve the quality of people’s lives.

    Working with a specific goal in mind will help you keep your team’s efforts focused. It will also set you up for long-term success.

    Step 2: Choose one area of your business

    Often, our first instinct is to choose a project that will help everyone. However, when you’re introducing automation into your business, it’s best to start small.

    Automation could probably improve every part of your business in some way, so you’ll have a lot of options in front of you. Maybe you’ll find that there’s a department that is completely overwhelmed with time-consuming, manual processes. Maybe there’s a team that needs to make big changes due to recent data privacy regulations. Or maybe there’s an area that has faced recent budget cuts and now has fewer people to help get work done.

    Most importantly, you’ll want to look for an area where the people on the team are excited about taking on this new project. You’ll need them to be your partners throughout the process.

    For example, the Administrative Office of the Courts in a southeastern state had an overburdened payment claims team. When they started their discovery process, they saw that more than 70,000 claims were on hold, mostly due to simple errors that had to be corrected through manual processes. For Turkcell, it was that their marketing team had limited time to review 7.9 million contracts and confirm that the contract data matched the information in their CRM system.

    In both of these companies, they knew the teams needed help and the team members were eager to start automating repetitive tasks.

    Step 3: Set yourself up for a quick win

    The unfortunate truth is that some people won’t be on board with your automation project until you show that it’s successful. So, plan with that reality in mind.

    You will have already set yourself up for success by choosing a single project with an engaged team. It’s also great to consider what you can easily measure – those numbers are going to be important as you prove the value of automation. You may also want to consider low-code technologies that are quick and easy to implement.

    For ENN Group, this meant implementing an automated financial assistant that could perform routine tasks like pulling reports or tracking monthly ledgers.

    Step 4: Monitor the progress

    Automation is an iterative process, and teams tend to see results very quickly. Be sure to track metrics from the start so you can see what’s going well and what you’d like to improve.

    For example, ENN Group’s virtual assistant was an immediate hit, it completed between 2,000 and 3,000 tasks every day, which reduced processing time by 60%. At the Administrative Office of the Courts, they reduced their payment processing times from 45-60 days to less than 10 days.

    As these results come in, you’ll start to have additional opportunities, either to expand the solutions you’ve implemented or to scope out additional ways that automation could help teams. And these could be found in surprising places. At the Administrative Office of the Courts, having an automated payment system facilitated the first raise for the state’s public defenders in a decade.

    Automation tips

    Here are a few additional tips that can help make automation a reality for your company:

    • Develop an internal methodology for automation projects
    • Learn how to avoid false starts
    • Remember that not everything should be automated

    Author: Naomi Sherry

    Source: IBM

  • Combining digital transformation with the right ERP project

    Combining digital transformation with the right ERP project

    I’ve been an independent ERP (Enterprise Resource Planning) consultant for over 25 years now and I would like to think that I have always had the best of intentions for my clients. In our industry it is hard to believe that the failure of so many organisations (and their consulting partners) to reach that ideal state of a complex digital transformation. Granted these initiatives are always peppered with landmines and risks, yet few seem to know how to navigate them very well, if at all. That is despite decades of history and lessons-learned exercises to draw from.

    'It’s not Rocket Science'

    To be truthful the answers aren’t really that complicated, and they certainly aren’t rocket science. There are distinct things that make certain projects succeed and fail, below is a brief summary of things to think about.

    Key stages of ERP software and digital transformation

    There are four distinct stages to an ERP software project or digital transformation. Unfortunately, many don’t achieve the aims or goals of the first two:

    1. Building a business case
    2. Project inception
    3. Completing the implementation
    4. Digital transformation is completed

    Digital transformation and ERP software initiatives

    Those that complete a full digital transformation leveraged the benefits of that successful implementation and transformation. They have figured out how to launch their initiatives to greater heights and success.

    Here are the key criteria needed to reach a successful delivery:

    Fast-track software evaluation and selection

    An effective digital strategy and ERP software selection process can be an effective way to gain alignment and chart a clear path forward, but it’s also easy to get lost in analysis paralysis. The most effective organisations don’t get bogged down in a cumbersome evaluation and selection process or hire inexperienced consultants with little hands-on implementation experience to guide them. Instead, they used experienced and unbiased resources to arrive at the best effective quickly so they can invest more time and money in implementation.

    Focus on organisational change management

    Most people understand Organisational Change Management (OCM) at cursory level, but many have not learned the skills to effectively manage change. The best ERP consultants know that an effective implementation requires detailed change impact, organisational design, stakeholder and executive alignment, a benefits realisation plan, and a host of other organisational change strategies that go well beyond assessments and pretty Powerpoint presentations.

    Investment in business process improvements and design

    It is of critical importance to define a clear and precise future state business processes, potential business process improvements, and leverage best practices from your industry sector. As part of this process design, we should define business processes, change impacts to people, and identify opportunities to implement process changes even before new technology is implemented. An investment in these business process management activities early on will save significant time and money in the long run.

    Planning for benefits realisation optimisation

    If you don’t plan it, measure it, you probably won’t achieve it. Be sure to set clear and precise targets and measures not only for project justification purposes, but more importantly, to help manage business benefits going forward. Additionally, a benefits realisation plan will provide a good mechanism for governance during implementation and delivery.

    Don’t leave your project’s success up to chance. Instead, focus on these and other key business best practices to help you reach successful outcomes, business goals and greater business performance.

    Author: Mike Davis

    Source: SAP

     

  • Covid-19 is speeding up all kinds of changes in business

    Covid-19 is speeding up all kinds of changes in business

    A recent survey of more than 200 enterprise business professionals confirms that Covid-19 is hastening both personal and business change across every industry.

    In a May 2020 survey conducted by MicroStrategy, 88% of respondents said that Covid-19 has had some or a significant impact on their work, with more than 30% saying the impact has been significant. While 27% said that their employer has a new focus on employee upskilling because of changing priorities related to Covid-19, more than half of respondents (54%) said they now have a personal focus on improving their work-related skills or learning new ones.

    Back to business

    On the business side, 79% of survey respondents said that the impact of Covid-19 is accelerating their organization’s digital transformation initiatives. Top challenges and priorities that are now being addressed in order to adapt to a “new normal” include:

    • Budget changes
    • Employee productivity and retention
    • Remote work adaptation and collaboration
    • Connecting data with new KPIs
    • Ensuring trusted data to predict outcomes
    • Re-envisioning customer engagement

    In relation to customer engagement changes, 91% said that Covid-19 has had some or a significant impact on their organization’s customer experience and customer engagement initiatives, with 38% saying the impact has been significant. And, as a direct result of the pandemic, 68% say their organization’s use of analytics has increased.

    “Insight is great. Foresight is gold,” noted Constellation Research VP and Principal Analyst Doug Henschen in a recent webcast detailing Constellation Research’s Post-Pandemic Playbook for Business. Henschen said new leadership models, trust, remote work policies, reskilling investments, plus a focus on communications, mental health support and safety will be key people and process considerations moving forward. For technology, it will be all about continuity, resiliency, cloud to achieve scalability and flexibility, analytics for agility and performance, AI and automation, plus mobility and privacy.

    Author: Tricia Morris

    Source: Microstrategy

  • DataOps and the path from raw to analytics-ready data

    DataOps and the path from raw to analytics-ready data

    For the first time in human history, we have access to the second-by-second creation of vast quantities of information from nearly every activity of human life. It’s a tectonic shift that’s transforming human society. And among the myriad impacts is an important one for every business: the shift in data users’ expectations. In the same way that the advent of smartphones triggered expectations of access and convenience, the explosion in data volume is now creating expectations of availability, speed, and readiness. The scalability of the internet of things (IoT), AI in the data center, and software-embedded machine learning are together generating an ever-growing demand in the enterprise for immediate, trusted, analytics-ready data from every source possible.

    It makes complete sense, since there’s a direct correlation between your business’s ability to deliver analytics-ready data and your potential to grow your business. But as every data manager knows, yesterday’s infrastructure wasn’t built to deliver on today’s demands. Traditional data pipelines using batch and extended cycles are not up to the task. Neither are the legacy processes and lack of coordination that grew out of the siloed way we’ve traditionally set up our organizations, where data scientists and analysts are separate from line-of-business teams.

    As a result, enterprises everywhere are suffering from a data bottleneck. You know there’s tremendous value in raw data, waiting to be tapped. And you understand that in today’s data-driven era, success and growth depend on your ability to leverage it for outcomes. But the integration challenges presented by multi-cloud architecture put you in a difficult position. How can you manage the vast influx of data into a streamlined, trusted, available state, in enough time to act? How can you go from raw to ready for all users, in every business area, to uncover insights when they’re most impactful? And perhaps most importantly, how can you make sure that your competitors don’t figure it all out first?

    The raw-to-ready data supply chain

    There’s good news for everyone struggling with this issue.

    First, the technology is finally here. Todays’ data integration solutions have the power to collect and interpret multiple data sets; eliminate information silos; democratize data access; and provide a consistent view of governed, real-time data to every user across the business. At the same time, the industry trend of consolidating data management and analytics functions into streamlined, end-to-end platforms is making it possible for businesses to advance the speed and the accuracy of data delivery. And that, in turn, is advancing the speed and accuracy of insights that can lead to new revenue creation.

    And second, we’re seeing the emergence of DataOps, a powerful new discipline that brings together people, processes, and technologies to optimize data pipelines for meeting today’s considerable demands. Through a combination of agile development methodology, rapid responses to user feedback, and continuous data integration, DataOps makes the data supply chain faster, more efficient, more reliable, and more flexible. As a result, modern data and analytics initiatives become truly scalable, and businesses can take even greater advantage of the data revolution to pull ahead.

    What is DataOps for analytics?

    Like DevOps before it, which ignited a faster-leaner-more-agile revolution in app development, DataOps accelerates the entire ingestion-to-insight analytics value chain. Also like DevOps, DataOps is neither a product nor a platform; it’s a methodology that encompasses the adoption of modern technologies, the processes that bring the data from its raw to ready state, and the teams that work with and use data.

    By using real-time integration technologies like change data capture and streaming data pipelines, DataOps disrupts how data is made available across the enterprise. Instead of relying on the stutter of batch orientation, it moves data in a real-time flow for shorter cycles. Additionally, DataOps introduces new processes for streamlining the interaction among data owners, database administrators, data engineers, and data consumers. In fact, DataOps ignites a collaboration mentality (and a big cultural change) among every role that touches data, ultimately permeating the entire organization.

    What does DataOps look like from a data-user perspective?

    In a subsequent post, I’ll delve more granularly into the technical and procedural components of DataOps for Analytics, looking at it from an operational perspective. For this post, where I want to highlight the business impact, I’ll start with a quick overview of what DataOps looks like from a data-user perspective.

    • All data, trusted, in one simplified view: Every data-user in the enterprise has 24/7 access to the data (and combinations of data) they need, in an intuitive and centralized marketplace experience. Analysts of every skill level can load, access, prepare, and analyze data in minutes without ever having to contact IT.
    • Ease of collaboration: It becomes faster and easier for data scientists and business analysts to connect and collaborate, and crowd-sourcing of key information. For example, the identification and surfacing of the most popular and reliable data sets becomes possible.
    • Reliability and accuracy: Because the data is governed and continuously updated, with all users drawing from the same data catalogue, trust is high, teams are aligned, and insights are reliable.
    • Automation: Users are freed to ask deeper questions sooner, thanks to the automation of key repeatable requests. And with AI-enabled technologies that suggest the best visualization options for a given data set, chart creation is faster and easier, too. Other AI technologies point users toward potential new insights to explore, prompting them to reach relevant and previously undiscovered insights.
    • Ease of reuse: Data sets do not have to be generated again and again, for every application, but rather can be reused as needs arise and relevance expands – from planning and strategy to forecasting and identifying future opportunities in an existing client base.
    • Increased data literacy: DataOps fosters the easiest kind of data literacy boost by automating, streamlining, and simplifying data delivery. Regardless of existing skill levels, every member of your team will find it much more intuitive to work with data that’s readily available and trusted. At the same time, DataOps buttresses the more active efforts of skills training by delivering reliable data in real time. Getting the right data to the right people at the right time keeps even the most advanced analysts moving forward in new directions.

     What are the business outcomes?

    In every era, speed has given businesses a competitive advantage. In the data-driven era, where consumers expect real-time experiences and where business advantage can be measured in fractions of a second, speed has become more valuable than ever. One of the fundamental advantages of DataOps for Analytics is the speed of quality data delivery. The faster you can get data from raw to ready (ready for analysis, monetization, and productization), the faster you can reap all the benefits data promises to deliver.

    But speed is just the beginning. By delivering governed, reliable, analytics-ready data from a vast array of sources to every user in the enterprise, the raw-to-ready data supply chain becomes an elegant lever for business transformation and growth. Here are four key areas where DataOps galvanizes transformation:

    1. Customer intelligence: With an agile data supply chain, you can much more efficiently use analytics to improve customer experience and drive increased lifetime value. Discover deeper customer insights faster, and use them to customize interactions; increase conversion; and build long-term, one-to-one customer relationships by offering personalized experiences at scale.
    2. Reimagined processes: Accelerating, streamlining, and automating your data pipelines enables teams across your organization to more quickly and effectively optimize every aspect of business for efficiency and productivity. This includes automating processes, reducing costs, optimizing the overall supply chain, freeing up scarce resources, improving field operations, and boosting performance.
    3. Balanced risk and reward: Nimble data-delivery empowers analytics users to get timely insight into internal and external factors to make faster, smarter decisions around risk. Leaders can manage production; keep data current, consistent, and in the right hands; and stay compliant while preparing for the future.
    4. New business opportunities: And finally, a raw-to-ready data supply chain gives you the power to develop new products, services, and revenue streams with insights gleaned from data and/or to monetize the data itself. This may be the most exciting opportunity we’re seeing with DataOps for Analytics today; it’s certainly the most transformative. For example, consider how storied American conglomerate GE has transformed a century-old business model (selling hardware) to create a digital platform for commodifying their data. And think about how tech behemoths like Amazon and Google have used their massive stores of data and agile analytics capabilities to attack and disrupt traditional markets like insurance, banking and retail.

    The heart of digital transformation

    If you’re launching or underway with strategic digital transformation programs for competitive viability and if you’re a CIO or CDO, data is the key. To thrive, your initiatives need an agile, integrated data and analytics ecosystem that provides a raw-to-ready data supply chain, accelerates time-to-insight, and enables a rapid test-and-learn cycle. That’s DataOps for Analytics, and it’s the dawn of a new era in the evolution of the data-driven organization.

    Author: Mike Capone

    Source: Qlik

  • Digital transformation: Key goals and leaders

    Digital transformation: Key goals and leaders

    According to Innosight research, the average company tenure on the S&P 500 Index in 1977 was 37 years. By 2027, it’s forecasted to be just 12. At the current churn rate, about half of the companies now on the S&P 500 will be replaced over the next ten years. Digital Darwinism is steadily accelerating.

    '52% of the Fortune 500 have been merged, acquired, have gone bankrupt, or fallen off the list since 2000', notes Constellation Research Founder and Disrupting Digital Business author Ray Wang in a recent webcast. 'That is an amazing stat when you think about the level of disruption that’s happening inside lots of organizations'.

    Wang notes that digital leaders are now creating not just a digital divide, but a winner-take-all market. Overall, digital leaders now take up to 69.8% of market share, versus 30% for everyone else. And in percentage of profits, they lead with 77.1% versus 22.9% for everyone else. 'Using data-driven business models, they are able to create an unfair advantage, and it’s happening in every single marketing and every single industry', says the analyst and author.

    In Constellation Research’s latest digital transformation study, 68% of businesses with digital transformation projects are now seeing a positive ROI. Goals widely shared by these businesses include:

    • Reaching and engaging with customers more effectively
    • Building a competitive advantage in their current market
    • Implementing new, data-driven business models
    • Increasing revenue
    • Modernizing legacy IT and reducing costs
    • Improving agility
    • Faster innovation cycles
    • Improving the employee experience
    • Greater transparency
    • Compliance

    Who's leading the digital transformation charge?

    In 33% of organizations, notes Constellation’s survey, it’s the CIO who’s leading digital transformation initiatives. In 23% of organizations, it’s the CEO. In 20% of organizations, it’s the CDO (being chief digital or chief data officers). And depending upon who’s leading, the digital transformation priorities for the business may be different.

    When a CIO leads, their top three priorities tend to be:

    1. Building a competitive advantage (38%)
    2. Modernizing legacy IT and reducing costs (38%)
    3. Implementing data-driven business models (33%)

    When a CEO leads, their top three priorities are:

    1. Engaging with customers more effectively (57%)
    2. Building a competitive advantage (50%)
    3. Increasing revenue (43%)

    For CDOs (chief digital or chief data officers), the top priorities are also different, with:

    1. Implementing data-driven business models and engaging in faster innovation cycles tied for first place (50%)
    2. Engaging with customers more effectively, modernizing legacy IT, and reducing costs tied for second (43%)

    Conclusion

    No matter who leads your organization's digital transformation, it is obvious that businesses trnsforming digitally and data-driven are having a competitive edge in the present and future. When taking on the process of digital transformation for your business, make sure to align your data strategy with company goals and primary processes. Choosing the right person to lead this process is key to a successful transformation.

    Author: Tricia Morris

    Source: MicroStrategy

  • Gartner: US government agencies falling behind digital businesses in other industries

    Gartner: US government agencies falling behind digital businesses in other industries

    A Gartner survey of more than 500 government CIOs shows that government agencies are falling behind other industries when it comes to planned investments in digital business initiatives. Just 17% of government CIOs say they’ll be increasing their investments, compared to 34% of CIOs in other industries.

    What’s holding government agencies back? While Gartner notes that their CIOs demonstrate a clear vision for the potential of digital government and emerging technologies, almost half of those surveyed (45%) say they lack the IT and business resources required to execute. Other common barriers include lack of funding (39%), as well as a challenge organizations across all industries struggle with: culture and resistance to change (37%).

    Another key challenge is the ability to scale digital initiatives, where government agencies lag by 5% against all other industries. To catch up, government CIOs see automation as a potential tool. This aligns with respondents’ views on 'game-changing' technologies for government. The top five in order are:

    • Artificial intelligence (AI) and machine learning (27%)
    • Data analytics, including predictive analytics (22%)
    • Cloud (19%)
    • Internet of Things (7%)
    • Mobile, including 5G (6%)

    Of the more than 500 government respondents in Gartner’s survey, 10% have already deployed an AI solution, 39% say they plan to deploy one within the next one to two years, and 36% intend to use AI to enable automation, scale of digital initiatives, and reallocation of human resources within the next two to three years.

    Investing today for tomorrow's success

    When it comes to increased investment this year (2019), BI and data analytics (43%), cyber and information security (43%), and cloud services and solutions (39%) top the tech funding list.

    As previous and current digital government initiatives start to take hold, CIOs are seeing moderate improvements in their ability to meet the increasing demands and expectations of citizens. 65% of CIOs say that their current digital government investments are already paying off. A great example of this is the U.S. Department of Housing and Urban Development’s use of BI and data analytics to modernize its Grants Dashboard.

    Despite budget and cultural change challenges typically associated with digital government initiatives, make no mistake: many agencies are making great strides and are now competing or leading compared to other organizations and industries.

    There’s never been a better time to invest in game changing technologies to both quickly catch up, and potentially take the lead.

    Author: Rick Nelson

    Source: Microstrategy

  • How CIOs are learning from the COVID-19 pandemic to transform towards agile

    How CIOs are learning from the COVID-19 pandemic to transform towards agile

    If the COVID-19 pandemic taught us anything, it’s that you can never be too prepared for change – fast-moving, come-out-of-nowhere change that transforms the way we run our businesses, manage our people, and secure the stability of our enterprises. 

    Disruptive events in business are nothing new. As leaders, we have long invested in planning and processes that enable our organizations to withstand many types of disruption, be it social upheaval, unfavorable market conditions, supply chain breakdowns, or environmental disaster.

    COVID-19, however, was leagues beyond what even the most risk-aware organizations could fathom, let alone plan ahead for in a specific, actionable way. Now, emerging from the pandemic and moving forward into a work landscape that is perhaps more flexible and adaptable than ever before, the COVID-19 wake-up call must be heeded in a thoughtful, intentional manner that prioritizes digital transformation, so that organizations can be nimble and adaptive to the next major, fast-moving disruption. 

    CIOs Are Leading the Digital Transformation Revolution 

    Many CIOs are already in go-mode, leveraging the lessons of the pandemic to push for more agile organizations and business and technology scalability. In fact, a March 2021 SAPinsider survey reveals that 62% of executives and leaders have identified process efficiency as a top business priority for 2021. 

    With the pandemic forcing business to incorporate unprecedented agility into nearly every facet of operations, it’s not surprising that many leaders now see a highly customized and difficult-to-change ERP system as a liability during times of unexpected change. One CIO who has been leading their organization’s digital transformation project for the past year described the challenges of innovating on an antiquated platform as limiting their ability to do new and innovative things with SAP – and that implementing new functionality, or doing anything new, requires significant effort and testing. Those limitations don’t lend themselves to supporting the level of innovation CIOs are looking for, driving them to build new digital platforms with SAP S/4HANA.

    This CIO is certainly not alone in their push for proactive, strategic digital transformation. Right now, CIOs around the world are advocating more forcefully than ever to migrate systems to the cloud and to streamline digital operations by integrating disparate systems and data. The SAPInsider survey backs this up, noting that many CIOs are finding that their pushes toward digital transformation are meeting less resistance these days. With the pandemic proving the irrelevance of location for labor forces and technical infrastructure alike, the realization that the cloud is king has crystallized. The pandemic has ushered in a new era of accord: IT partners, and the technology and innovation they make possible, are not behind-the-scenes vendors, performing tactical functions. Instead, strategic technology partnerships are foundational to most organizations’ livelihoods.

    Many leaders are taking note – and taking action. Over half of executives in the SAPinsider study identified SAP S/4HANA as their most strategic investment in the coming year – despite the fact that SAP’s deadline isn’t until 2027 – and many have already committed to the budgets (66%) and headcount (36%) required to make the transformation goal achievable. With proper planning, S/4HANA can be a game-changing break from the complex, disparate systems that built rigidity into the essential fabric of your business. Is the unsorted data you’ve inherited or accumulated serving your goals? Most likely, it’s weighing you down without pulling its weight in terms of delivering trustworthy analytics. Digital transformation on the whole, and S/4HANA more specifically, provide a golden opportunity to assess your current data landscape and develop a proactive plan that will set your organization up for increased resilience and strategic innovation.

    If ever there were a moment to advocate for organizational resilience strategies, it’s today. The pandemic may be easing up in the U.S., but if the past year has taught us anything at all, it’s to expect the unexpected. Preparation and agility are not virtues we can afford to forget as the pandemic becomes a more distant memory. 

    Author: Steele Arbeeny

    Source: Dataversity

  • How digital transformation drives innovation of health clubs

    How digital transformation drives innovation at health clubs

    ‘Wellness’ was the most talked about topic during the entire lockdown. With nowhere to go, it took a big hit initially but soon it found solutions in digital transformation. Thriving at a faster pace, this industry accelerated the implementation of digitization, resorted to healthcare app development and replaced its offerings with digital classes, on-demand content and live streaming.

    The wellness industry runs on majorly three pillars- nutrition, fitness and travel. Health clubs are part of the fitness segment of this industry which focuses on whole-body wellness, unlike gyms where the focus is devoted to physical wellness more. A health club offers a comprehensive fitness approach, providing recreational sports and exercise facilities at one place to consumers.

    According to studies, health clubs globally witness an increase of 4.6% annually. Similar to other industries, health club industry also benefited from technology during the pandemic by including healthcare app development, online on-demand services, etc, in its offering.

    How digital transformation is useful for health clubs?

    Fitness was never this important for people as it has been over the last few years. During the lockdown, digital solutions were welcomed to reach those lockdown fitness goals. This sudden need for a shift to digitization paved the path for many interactive and innovative fitness solutions. Even though the industry started this transformation a little late, it adapted quickly to this change.

    Engaging with the members

    Engaging with the clients is the root driver of digitization for health clubs. Omni-channel trends were existing but engaging with clients accelerated during this period. Brands sought after pre-recorded content, live streaming for engaging with their members. They also used text experiences to connect with their clients.

    Using the technology to bridge the gap of not being accessible physically, clubs who launched their apps to have a platform for their content, stood out of the crowd. The virtual offering made it easy for clients to continue their fitness routine. Many took help from the healthcare app development companies for making this transition. Pretty sure, your gym trainer was teaching you over WhatsApp and Zoom. Wasn’t he?

    Making operations easy

    Digitization brings with it, ease of operations. In every industry, digital transformation has proved to improve functioning and reduced costs over time by streamlining the processes. Health clubs also took advantage of the technology to reduce their operational costs and provide an easy, seamless member experience through CRM systems and easy bookings.

    Bringing personalized experience

    Digitization helped health clubs to bring personalized experiences for their clients. Mobile applications enabled brands to provide personal fitness plans to each of their clients based on their needs. This was earlier done face to face but with digitization, this process has become seamless, easy and virtual. Healthcare app development integrated with AI takes this to another level.

    Using data

    Data is of prime importance when we talk about digital transformation in healthcare. Using the data collected through IoT devices and applications, brands can develop a 360-degree view of the client’s needs. Offering a comprehensive personalized solution to their problems, it also helped in learning about the behavior and preferences by using the algorithms and executing personalized outreach.

    The data can also help the brand to anticipate the fitness needs of their clients by using AI-driven methods. People need solutions to problems and data can help brands discover those problems even before their clients discover them.

    Digging deeper into a fitness experience

    The IoT devices help brands in expanding this digital transformation. By integrating wearable devices, applications in their health club experience, brands can elevate their member experience. They can also provide a deeper insight into their fitness regimen through analytical analysis of the data collected. There are some health clubs who are pioneering this segment.

    A roadmap to how Health Clubs can leverage the benefits of digital transformation

    Digital transformation in healthcare is not an easy process. Simply investing in technology will not suffice. Digital transformation in healthcare requires a stringent cultural shift. It applies to health clubs as well.

    Understanding the members and the experience you want to serve based on your brand is important. This helps in ensuring that the new technology and the fitness experience you want to serve your members complement each other. They should be in sync with each other and bring an authentic fitness experience.

    From the numerous ways that health clubs can leverage the benefits of digital transformation, we have a few in the list.

    Smart machines: Exercise and gym equipment that can be connected to the cloud and is responsive to an individual, is a popular thing among health clubs and gyms. Some of these smart equipment are even programmed with machine learning technology that enables self-learning and improvising the fitness journey of the user.

    3D body scanning: This technology can be used to create effective and accurate personal programs targeting the specific problems of the clients.

    Using SMS and texting services: Apart from providing only an exercise routine, a health club can also leverage the use of SMS or text services to motivate their members and give health reminders. This can also be used to send out awareness messages on mental health and other issues concerning the members. This will help in creating a more connected engagement channel.

    Wearable 3rd party devices: Health clubs can provide members with 3rd party wearable devices to track their progress and vitals inside and outside the gym for providing in-depth analysis.

    Digital transformation in healthcare has proved to be of supreme advantage. Adapting to advanced technology in the health club industry has and will prove to be groundbreaking. Not only does it bring efficiency in operations, but it also gives a competitive advantage. 

    Author: Robert Jackson

    Source: Datafloq

  • How small European businesses transition to an online environment due to covid-19 measures

    How small European businesses transition to an online environment due to covid-19 measures

    From the beginning of the crisis, the online space became the main market for entrepreneurs and especially small businesses. But the countless 'freebies' made it nearly impossible to make a profit.

    Since early 2020 when countries across Europe and beyond started to introduce lockdowns, entrepreneurs working primarily in-person — e.g. workshop facilitators, trainers, coaches and many others — lost access to their local face-to-face market. To keep afloat and save their business, most of them decided to quickly develop or adapt a service to sell online. The large inflow of new online offerings made it hard for both: entrepreneurs who were online already and the ones who just decided to join. 

    Imagine every Saturday you go to a big market (not something we do anymore, but you might still remember it). It has everything: food, clothes, white goods, antique items, books. It is not easy to know where is what, but it has a great atmosphere, it’s lively and interactive. You often meet your friends there and you spend hours walking around together. Sometimes you come there for an item you know you need and sometimes just to see what calls your attention. 

    One Saturday when you arrive at the market, you see that it became much bigger than before. Half of the stalls seem to have a sale on, while the other half is simply giving everything away. Fruits, vegetables, shoes, dresses, fridges and microwaves — anything you see has its free twin. At first look, they all seem the same. Naturally, you wander into the part of the market with free items. Since they are the same quality it doesn’t make sense to waste your Saturday budget on things you can get for free. 

    You spend an entire afternoon walking from one stand to another looking for more things to get. By the end of it, you are tired, your hands are full, and you saw that some of the items are not exactly top-quality but you can’t be bothered to go through yet another 20 stalls of the same product in the paid area. So you call it a day and go home. You and thousands of other market visitors that came there.

    What about the sellers? 

    None of them made any profit. One half didn't because they were giving their products away at no cost. The other half didn't because they still tried to sell but could not compete with the "freebies." Arguments such as “we have better quality” were too weak against something that was completely free. 

    A few Saturdays later, after this happened, again and again, the market shut down. The sellers with free items got exhausted from not having any return on their investment and lost interest in their trade. The others that still tried to sell went bankrupt and had to get a job to support their families. The customers stopped coming as well because of how aggressive everything was advertised and how difficult it was to make sense of what was on offer. 

    Now imagine that the "Saturday market" is actually the world of online services and the situation described is what has been happening since the beginning of the crisis. Here are the issues with what transpired:

    Oversaturation

    Let’s say before 2020, only 20% of all services from small businesses were offered online. Suddenly, with the lockdowns, the remaining 80% of face-to-face services got transferred into the online market. Not surprisingly, it started to overflow with offers. 

    On top of that, the offers were quite similar. The only difference was in the price: from low to mid-price to unbelievably expensive. The channels used to advertise and sell them became even more diverse than before. That made it almost impossible for potential customers to find what they were looking for and compare options. The online market became oversaturated. 

    Drop in quality

    The average quality of services offered online deteriorated. It was not enough to move what was done in-person into an online form and expect it to give the same results. 

    Recognizing that, many entrepreneurs and companies started testing their services by offering them completely for free. That in turn ‘cannibalized’ the market for the ones who were building their online business model long before the crisis. 

    Lower demand

    It is true that the prolonged confinement moved potential customers online as well. But unlike the supply, the demand side did not move there in full. Many of the prospects were suffering slowdown and losses in their own businesses. They did not require services that were not essential for survival. 

    Short transactions

    There are still things offered online that remained (or became even more) popular: a movie streaming channel, an app for live stream, or another digital tool that people need or love. The majority offered not by small businesses but by large well-established companies. Zoom, Netflix, Disney, Remote Working, and others are self-explanatory and easy to use. Their advantage is that they don’t require a call to explain why you need it. The transaction happens in one click and you can immediately benefit from what you paid for. 

    A revival of all things good?

    But for the millions and millions of small businesses online competing in Europe and elsewhere, offering tailor-made business consulting, educational services, facilitation and workshops, coaching and advice of all kinds — every day it becomes a little bit harder, sadly resembling the “Saturday market.” 

    On the bright side, it is inspiring to see that there are many stories — gathered through the nonprofit United Nations registered initiative Lockdown Economy — among small businesses with tangible products that became more successful online. 

    A little family bakery in the Philippines got endorsed by a celebrity on Twitter and suddenly they had more customers than they could imagine. Or a store in Albania with everything for babies and toddlers that has been around for a decade but never done anything online is now actually selling things through a very simple online account. A home-based crochet studio in Lebanon that started as a hobby, thanks to Instagram and the word of mouth reached thousands of people in a couple of months. 

    This trend looks like a revival of all things good: local, handmade, green, healthy, sustainable. What you can see is that customers are still gladly paying for things that make them happy.

    Author: Julia Skupchenko

    Source: Entrepreneur Europe

  • How to translate IIoT investments to ROI

    How to translate IIoT investments to ROI

    A digital transformation takes time, sometimes a considerable amount. This means it can be difficult to quantify ROI, at least in the short term. Return on investment for IIoT (Industrial Internet of Things) relies entirely on the data collected with the technology, and how it’s applied. The information itself may be incredibly valuable, but that won't matter if it's used ineffectively, further reducing the leverage.

    Real-time insights provide more of a direct influence on operations, offering minimal boons to a variety of business facets. That said, measuring real ROI is about the big picture and how all those smaller wins come together to provide a wholly effective strategy.

    It’s difficult to ascertain the ROI of IIoT and gauge whether or not you’re on the right track in the first place.

    Spending on IoT remains high for many industries, but the ROI is still up in the air. About 72% of construction business operators include new tech adoption as part of their strategic plan or vision for the future. Despite that, only 5% see themselves on the cutting edge of adoption. Here are some tips that can help you better plan industrial IoT adoption, while also getting the most out of the new technologies:

    Choose an objective

    Industrial IoT is an incredibly broad field that encompasses nearly every device, machine and process that exists today, and beyond. Just because the technology can be outfitted to work with every system in a facility doesn’t mean that’s what should happen.

    Before moving forward with any form of implementation, every organization should choose an objective for its IIoT campaign. What is the technology going to achieve? Should it be used to improve manufacturing efficiency? Will it help sync up workers across the plant floor? Is it better suited for fleet management and asset tracking?

    While it would be great to have multiple potential solutions in place, it would be nearly impossible to verify the ROI after doing so. By selecting a single objective and following through, data teams can adopt a more systematic approach that provides more accurate insights. In the end, it allows decision-makers to see firsthand whether IoT is a proper investment and worth pursuing on a larger scale.

    If nothing else, deploying IIoT with the intent to eliminate bottlenecks in existing processes is a great place to start.

    Go process by process

    With all the hype surrounding digitization and modern technologies, it's easy to get swept up in the tide. Overhauling every aspect of a business to honor advanced digital solutions may seem like a great idea, initially. The reality is that taking it all on at once is likely going to fail. For instance, switching to a paperless operation while simultaneously installing new IoT sensors on the factory floor will cause more confusion than positive support.

    As Harvard Business Reviews’ Digital Transformation of Business report states, merely spending more on cutting-edge technologies does not guarantee a positive outcome.

    The real winners will be the 'companies that both identify which core business capabilities they need to differentiate and make a commitment to transform these core business capabilities with the right digital technology'.

    Instead, take a look at the processes and systems currently in place and identify what will see the most significant boon from digitization. Choose one or two, and then get to work. Once the ball is rolling, it’s going to take time and resources to implement the proper solutions. New technologies will need to be installed, which means old equipment and tools might need to be phased out or upgraded. Employees will need training, and they may also need their own set of improved tools. Leadership will need to come up with new strategies for working with upgraded systems>, communicating with their workers and taking action.

    It’s a long, demanding process. Not something that happens overnight. That’s precisely why it’s best to take it one step at a time and focus on a single process or solution. Once a particular department or task is honed, then it’s time to move on to other digitization projects within the company.

    Choose a reliable vendor

    With new technologies it’s best to work with a vendor or specialist that already has considerable experience. Yes, it’s possible to develop an in-house IoT solution that’s also managed by a proprietary IT crew. It’s also a lot more costly and more likely that problems will arise as a result.

    Third-party vendors have more resources at their disposal merely because it’s what they do, exclusively. They tend to have more robust IT and security solutions, along with the appropriate human resources to keep everything safe. They can handle installation, upgrades and repairs, which takes the responsibility away from the leading organization. They also provide comprehensive support for when problems or questions do arise.

    Implement predictive operations with IIoT

    Predictive maintenance is something relatively new in the industrial field, made possible thanks to IIoT and the real-time insights it can deliver. Data can reveal hidden details about working machinery, output, potential errors and more. Collectively, it provides a detailed report about performance, allowing decision-makers to pinpoint what areas of the operation are lacking. They can take action, sooner rather than later, to correct any issues and replace ailing equipment.

    It’s a process that should be deployed across the entire operation instead of solely for maintenance. It can be used for a lot more than just predicting when equipment is going to fail, too. Employing machine learning and analytics applications can reveal when and how supplies are going to thin out, demand trends, and much more. Another term for this is business intelligence. Predictive operations throug big data analysis are one facet of business intelligence, albeit an incredibly lucrative one.

    Invest in IoT for predictive operations and ROI will innately improve.

    Improving ROI even before it can be measured

    These tips offer just a few ways that organizations can improve the ROI of IIoT implementation, even through preplanning. It may be difficult to quantify the real value of the technology upfront. Nonetheless, honoring these processes can help realize the bigger picture, which is something business leaders always demand.

    Author: Megan Nichols

    Source: Datafloq

  • How your organization can establish a results-based data strategy

    How your organization can establish a results-based data strategy

    Money never sleeps and neither does your data. In
    this article, we look at digital transformation: the ways of turning data into new revenue streams and apps that boost income, increase stickiness, and help your company thrive in the world of Big Data. 

    The first waves of digital transformation started decades ago and the ripples of this trend continue to be felt to this day. However, what exactly a digital transformation looks like varies widely from company to company. One common theme among many transformations, however, is trying to make better use of data, whether to build analytic apps to unlock new revenue streams or to make smarter decisions internally (or both).  

    While these are worthwhile applications, one blind spot that many teams charged with these projects share is that they look at the data they have on-hand before figuring out what kind of problems they wish to solve with it. 

    “I recommend starting your data strategy with a right-to-left approach, focusing on the desired business outcomes first, instead of the data, to support those outcomes,” says Charles Holive, Sisense Managing Director of Data Monetization and Strategy Consulting. “And there are primarily three areas that industries across the world look to improve: the top line, the bottom line, and customer satisfaction.”

    Define your desired outcome before you start building

    Every company knows they need to digitally transform in order to survive and excel in the modern era. However, many organizations fail to define their goals for this process before they start, and predictably encounter obstacles or outright failures instead of paving a path for future success.

    Business goals should be defined at the very beginning of the digital transformation in the “right-to-left strategy” that starts by answering this question: What is the organization specifically looking to solve or improve? Understanding the details is key, otherwise “digital transformation” will be merely a corporate buzzword that causes headaches, heartbreaks, and lost money instead of producing measurable improvements.

    From there, rather than trying to accumulate and house the company’s entire dataset, the digital transformation team should identify the specific actionable insights and associated data needed to solve for (and measure) agreed-upon outcomes.

    “Not every dataset is made equal; some are more valuable than the others. So being outcome-focused is a way that can you stack-rank the data sets that are most important. Your team can then begin moving that most-important data into your warehouse.”

    Experiment to guide a winning data strategy

    Just as the waterfall method of software development, the strategy of gathering all the requirements upfront and then building and releasing a complete application, has fallen out of favor for agile methods, the same thing should happen when creating an outcome-first data strategy: Rather than trying to build a complete data warehouse right from the outset, approach data strategy as an “innovation factory.”

    “Identifying the exact data you need to solve a singular problem results in a perfect candidate to go into your warehouse on the first cycle. This is because you know exactly what the business is going to do with that data set,” Charles explains. “It’s powerful because it’s already informing or measuring a specific business outcome.”

    And when this data is warehoused and accessible to business partners to make key decisions, you already have a chance to quickly prove this outcome-first data strategy. You’ve immediately created an experiment to win.

    Another piece of advice that Charles talks about in his “Hacking the Analytic Apps Economy” video series is where the innovation factory should live. Namely, not in a mature business unit, but in an agile, fast-reacting department that reports to a Chief Innovation Officer or similar highly-placed exec. This team can deliver on new ideas quickly and won’t get bogged down in pre-existing frameworks or goals that don’t work for what the new data experiments are trying to achieve.

    Create an innovation factory at your company

    “Creating an innovation factory for your company results in faster innovation. You can do these smaller experiments more cost-efficiently, saving money over the traditional data strategy. This also should help your team prioritize projects for the data warehouse that deliver the greatest value, as opposed to the department that screams the loudest.” 

    And while any experiment can fail, but here are some solid tips to help improve your likelihood of success and to maximize the impact of triumphant experiments: 

    • Start by listening to the frontline employees who use the data to make decisions, this will improve the odds of success for your experiment out of the gate.
    • If your experiment works, find other departments that can benefit from that same data, this is where it is key to have a good semantic layer on top of your data warehouse (courtesy of your data analytics software) so you can repurpose the same dataset for different ends.
    • If your experiment fails, see if you can tweak the dataset or use case to apply elsewhere in the company.

    Regardless, approaching data strategy with a focus on business outcomes will put you on the right course.

    “Everything else in the company is business-centered. It just seems counterintuitive not to approach data strategy in the same way.”

    Author: Jack Cieslak

    Source: Sisense

     

  • Predicting Student Success In The Digital Era

    Predicting Student Success In The Digital Era

    I had the pleasure of moderating a webinar focusing on the work of two Pivotal data scientists working with a prestigious mid-west university to use data to predict student success.It’s a topic that has long interested me as I devoted a good deal of time trying to promote this type of project in the early 2000’s.

    That could reflect on my skills as a salesman but on consideration it also illustrates how fast and how far our big data technologies have brought us. So after hosting the webinar (which I recommend for your viewing, you can see it here) I did a quick literature search and was gratified to see that in fact many colleges and universities are undertaking these studies.

    One thing stood out just by examining the dates of the published literature.Prior to about 2007 what predictive analytics was performed tended to focus on the sort of static data you can find in a student’s record: high school GPA, SAT scores, demographics, types of preparatory classes taken, last term’s grades, and the like.That’s pretty much all there was to draw on and there was some success in that period.

    What changes in the most current studies is the extensive use of unstructured data integrated with structured data. It wasn’t until about 2007 that our ability to store and analyze unstructured data took off and now we have data from a variety of new sources.

    Learning Management Systems 

    One of the most important new sources. These are the on line systems used to interact with students outside of the classroom. From these we can learm for example when they submitted assignments relative to the deadline, how they interact with instructors and classmates in the chat rooms, and a variety of click stream data from library sites and the like.

    Sensor and Wi-Fi data 

    Show frequency and duration on campus or at specific locations like the library.

    Student Information Systems 

    These aren’t necessarily new but greatly improved in level of detail regarding classes enrolled and completed with regular grade markers.

    Social Media 

    What is standard now in commerce is becoming a tool for assessment of progress or markers for concern. Positive and negative social media comments are evaluated for sentiment and processed as streaming data that can be associated with specific periods in a student’s term or passage through to graduation.

    The goals of each study are slightly different.Some are seeking better first year integration programs which are so important in student long term success. Some are focused on the transition from Community College to four year institution. But universally they tend to look at some similar markers that would allow counsellors and instructors to intervene. Some of those common markers are:

    • Predicting first term GPA.

    • Predicting specific course grades.

    • Predicting reenrollment.

    • Predicting graduation likelihood, some focused on getting students through in four years, others getting them through at all.

    As in any data science project, each institution seems to have identified its own unique set of features drawn from both the traditional structured and new unstructured data sources. Paul Gore who headed one of these studies at the University of Utah had a nice summary of the categories that’s worth considering. He says the broad categories of predictive variables fall into these six groups:

    Measures of academic performance:

    Academic engagement 

    Also known as academic conscientiousness: in other words, how seriously does the student take the business of being a student? Does the student turn in assignments on time? Attend class diligently? Ask for help when needed?

    Academic efficacy

    The student's belief and confidence in their ability to achieve key academic milestones (such as the confidence to complete a research paper with a high degree of quality, or to complete the core classes with a B average or better, or their confidence in their ability to choose a major that will be right for them).

    Measures of academic persistence:

    Educational commitment

    This refers to a student's level of understanding of why they are in college. Students with a high level of educational commitment are not just attending college because it is "what I do next" after high school (i.e., in order to attain a job or increase their quality of life); these students have a more complex understanding of the benefits of their higher education and are more likely to resist threats to their academic persistence.

    Campus engagement

    This is the intent or desire to become involved in extracurricular activities. Does the student show interest in taking a leadership role in a student organization, or participating in service learning opportunities, intramural sports, or other programs outside of the classroom?

    Measures of emotional intelligence:

    Resiliency

    How well does the student respond to stress? Do small setbacks throw the student "off track" emotionally, or are they able to draw on their support network and their own coping skills to manage that stress and proceed toward their goals?

    Social comfort

    Gore notes that "social comfort is related to student outcomes in a quadratic way -- a little bit of social comfort is a good thing, while a lot may be less likely to serve a student well, as this may distract their attention from academic and co-curricular pursuits." (aka too much partying).

    Where the studies were willing to share, the fitness measures of the predictive models look pretty good, achieving classification success rates in the 70% to 80% range.

    From our data scientist friends at Pivotal who are featured in the webinar we also learn that administrators and counsellors are generally positive about the new risk indicators. There was always the possibility that implementation might be hampered by disbelief but there are some notable examples where there is good acceptance.

    Some of the technical details are also interesting. For example, there are instances where the models are being run monthly to update the risk scores. This allows the college to act within the current term and not wait for the term to be over, which might be too late.

    And there are examples in which the data is being consumed not only by administrators and counsellors but also being pushed directly to the students through mobile apps.

    I originally thought to include a listing of the colleges that were undertaking similar projects but a Google search shows that there are a sufficiently large number that this is no longer a completely rare phenomenon. In its early stages to be sure but not rare.

    Finally I was struck by one phenomenon that is not meant as a criticism, just an observation. Where the research and operationalization of the models was funded by say a three year grant, it took three years to complete the project. But where our friends at Pivotal were embraced by their client, four data scientists, two from Pivotal and two from the university had it up and running in three months. Just saying...

    Author: William Vorhies

    Source: Data Science central

  • The Challenges of Moving to a Cloud Environment

    The Challenges of Moving to a Cloud Environment

    While no business could have fully prepared for the COVID-19 pandemic’s impact, those with strong cloud-based strategies have been able to adapt to the remote work reality. But even for companies that have migrated to the cloud or are in the process, a dispersed workforce presents challenges when you consider the trade-off between a streamlined, cohesive work process and network security. Despite this, the move from on-premise to cloud-based solutions isn’t slowing, making cloud migration still desirable.

    In fact, recent research points to increasing public cloud adoption over the next year, even amid, or perhaps a result of, the pandemic and an overall downturn in IT spending. According to Instinet, 68% of CIOs indicated cloud services would become more of a priority for their businesses and reported a reduction in on-premise workloads, from 59% relying on on-prem assets in 2019 to an estimated 35% by 2021.

    For businesses, cloud and SaaS services offer an easy way for employees to collaborate and access the information they need outside the confines of a physical office space. For employees, these solutions are desirable in part because they’re so easy to use. When not sanctioned through an employer, all it takes is an email or credit card to sign up, and an employee can start a CRM package, open a Dropbox, or create an iCloud account, and a range of other activities. While it sounds benign, any of these services could be a place for sharing company information, from trade secrets, to intellectual property, and personally identifiable information.

    In order to enable employees to get work done and safeguard sensitive information, organizations must find a way to both connect and manage systems and access. Cloud migration is a big undertaking, and far too often organizations overlook what a crucial part identity governance plays in implementing successful and sustainable cloud migration initiatives. By baking identity governance into your plan from the get-go you can avoid some of the main security pitfalls of transitioning to the cloud.

    One major challenge is employee buy-in. It may sound counterintuitive, as the cloud is meant to streamline work processes, but learning new systems and working out permissions can be a learning curve company’s need to account for. People want to get work done as quickly and efficiently as possible, and adding another roadblock for them to access what they need can result in bypassing security protocols. Organizations who have not already should implement safeguards like multi-factor authentication (MFA), but also consider making the second form of identity something easy to access, like a code sent to a mobile device or something the person has at all times versus a security question or a physical token they need to remember.

    A good cloud migration strategy is not just about wrangling your employees, though—it’s about choosing your cloud partner wisely. When you rely on cloud solutions, you’re entrusting another party with your valuable customer and company data. Even if the information is compromised under their care, it’s your business that will pay the price at both a financial and reputational cost. Before embarking on a cloud journey be clear about your prospective cloud provider’s security practices, and don’t just make them tell you—have them show you. Ask where your data will be stored, what measures they take to protect it, and what practices they use to keep it secure.

    Another challenge beyond vendor selection and employee onboarding is simply keeping up with the pace of technology. The last few years have looked like an arms race to the cloud, and as a result, a lot of projects fail. Migrating all your data with different levels of sensitivity and access privilege should be done intentionally, and many bite off more than they can chew. This causes mistakes and headaches in the long run, and the worst part is, it’s easily avoidable. Leverage third-party resources that have identity expertise, such as an outside consultant or an analyst firm to help you define your cloud requirements. Make sure stakeholders—leadership, investors, department heads, etc.—are involved in executing cloud projects, as they span the business.

    The work doesn’t stop there, though. Once you do have a solid strategy, select a vendor to partner with, and start onboarding and training employees, think ahead about how you’ll maintain a healthy security posture. Consider using a cloud access security broker, an independent software that sits between cloud service users and cloud applications, and monitors all activity, or an ethical hacker to help identify weak areas and enforce security policies. For highly-regulated industries, such as healthcare and life sciences or finance, managing evolving threats becomes especially important. By not complying with strict laws and requirements to protect sensitive information, you could be setting yourself up for a world of hurt.

    Security is a top reason that organizations stall their cloud endeavors—and for good reason. However, with the promise of better IT processes, increased productivity and collaboration, and a host of other benefits, the challenges of cloud migration far outweigh the risks. Success takes due diligence and a digestible strategy to prevail, so be sure to do the homework, tweak as you go, and remember, it’s a marathon, not a sprint.

    Author: Jackson Shaw

    Source: Open Data Science

  • Why agile learning is essential to your business

    Why agile learning is essential to your business

    The digital deadlock is affecting many organizations today, big and small, and across all industries. Vast amounts of technology investments are being poured into the engines of aggressive digital strategies, but are delivering little in the way of progress. In fact, many are 'stuck in their journey'. What’s holding them back?

    IDC has looked into this very closely in the past few years and has found that the ´digital skills gap´ (when demand for IT skills is not met with adequate supply) is a top obstacle for those organizations in their digital agenda. Interestingly, the challenge is not only in recruitment, but most crucially in bringing up to speed the current workforce with the new skills. Employees are not learning fast enough.

    Our surveys show that the impact of the skills gap is broadly felt across the organization, from quality performance to customer satisfaction to business revenue growth. In fact, IDC estimates it will affect 90% of all European companies, resulting in $91 billion in lost revenue in 2020.

    The skills gap is now a board-level issue, and employers are determined to tackle the problem themselves by reskilling their own workforce. If colleages and professional schools are not providing an adequate supply of IT professionals, corporate training programs and internal mobility could fill the gap.

    This is a significant shift by employers in their training practices and policies. After a decade of austerity following the global financial crisis in 2008, they have now realized that learning means business.

    Is the workforce ready for the jobs of the future? Welcome to agile learning

    IDC believes agile learning is the way forward for any digital organization because it aligns skills and required training with business value and strategy. It is permanently evolving, keeping pace with new market needs and technology developments.

    From content, format, to channels of delivery, agile learning is business relevant while driving superior employee experience.

    Agile learning has the following common traits:

    1. Employee focused: Training needs to be applied to the task and woven into the flow of work (easily digestible). It ultimately has to help employees “get the job done” and achieve better performance (impactful). This could include the consumption of bite-size content (even in minutes), any time and by multiple channels, to fit work demands.
    2. Business relevant: Training cannot be decided unilaterally by the employee, manager, or HR. It has to be a cross-functional effort to ensure that career development goals and training needs are aligned with business requirements: the right materials, to the right employees, at the right time.
    3. AI/ML enabled: Training can be enhanced by intelligent technologies in multiple ways. AI/ML can help employees by providing career pathway recommendations; for employers, it can identify training that addresses the skills gap. In the not-so-distant future, intelligent technologies will be able to measure the impact of training on performance and business outcomes, helping to make it business relevant.

    Agile learning will be ingrained in our work culture moving forward, helping us to become more competent in our jobs (upskilling) or even to move into new jobs (reskilling). It can also prepare us for the new jobs of the future, those that have not even be created yet. In this respect, IDC expects micro-degrees to become increasingly popular.

    Micro-degrees can be useful to equip employees, reasonably quickly, for new jobs such as a flying car developer or an algorithm bias auditor. Developed in partnership with academia, industry, and employers, micro-degrees complement lectures with on-the-job training.

    Agile learning affects us all. As the retirement age rises, we should be able to expect significant mobility throughout our careers. Agile learning will be part of a lifelong learning work culture, mandated by the C-suite and instilled into the organization.

    To quote the World Economic Forum’s Future of Jobs Report 2018, 'By 2025, 75 million current jobs will be displaced by the shift in the division of labour between humans, machines and algorithms, but 133 million new jobs will be created as well'.

    Your current job might be one of those 75 million. Act now to enjoy the Future of Work with the other 133 million.

    Author: Angela Salmeron

    Source: IDC UK

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