10 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


    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

  • 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%)


    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 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


  • 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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