6 items tagged "strategy"

  • Big Data nog weinig ingezet voor real-time of voorspellingen

    Big DataDatagedreven opereren? Bij de meeste bedrijven zijn de datatoepassingen nog relatief simpel en vooral gericht op analyse in plaats van real-time en voorspellingen. Een gemiste kans én risico voor de lange-termijnkoers van een organisatie.

    Nu al zegt 22 procent van de bedrijven achter te lopen op de concurrentie terwijl ruim 81 procent van de respondenten aangeeft dat de mogelijkheden van Big Data voor de eigen organisatie groot zijn.

    Dat blijkt uit de Big Data Survey 2015 van data-consultancybureau GoDataDriven en vakbeurs Big Data Expo. Bijna 200 bedrijven werden onderzocht om inzicht te geven in de actuele rol van big data, de mate van adoptie, intenties en mogelijke valkuilen.

    Data uit voor de hand liggende bronnen
    Wat blijkt? De data die gebruikt wordt is over het algemeen numeriek en komt vaak uit voor de hand liggende bronnen, zoals CRM en klantendatabase (18 procent), websitestatistieken (18 procent), externe bronnen (14 procent) en marketingdata vanuit e-mailstatistieken (14 procent) en transactionele data (13 procent). Toepassingen met data uit rijkere bronnen zoals tekst, beeld en geluid zijn er nog zeer weinig, terwijl hier grote winst te behalen is.

    GoDataDriven

    Meer budget voor datagedreven toepassingen
    De meeste bedrijven maken komend jaar meer budget vrij voor datagedreven toepassingen en zijn van plan te investeren in de kennisontwikkeling binnen het team. Een klein deel van de bedrijven is momenteel al bezig met het toepassen van kunstmatige intelligentie, machine learning, voorspellende modellen en deep learning.

    Maar dat verandert in hoog tempo. Binnen drie jaar verwacht 50 procent van de respondenten de eerste toepassingen met geavanceerde technologie ontwikkeld te hebben.

    Visie het belangrijkst voor succesvolle implementatie
    Wat de belangrijkste factoren zijn voor een succesvolle implementatie van een Big Data-strategie? Visie, aldus 28 procent van de ondervraagden, en ondersteuning vanuit de directie (19 procent). Maar ook ondersteunende systemen en processen (18 procent), budget (14 procent), talent (11 procent) en training (10 procent) spelen een belangrijke rol.

    GoDataDriven2

    Data als strategische pijler
    Tegelijkertijd geeft een opvallend groot deel van de ondervraagden aan dat het binnen het eigen bedrijf wel goed zit met de strategische rol van data. 37 procent vult in dat de bedrijfsdirectie data als een strategische pijler ziet, terwijl 27 procent het hier gedeeltelijk mee eens is. Bij bijna een kwart van de bedrijven (23 procent) is er binnen de bedrijfsdirectie op dit vlak juist een grote winst te halen.

    Ruim 67 procent van de bedrijven zegt dan ook dat de mogelijkheden van big data voor de eigen organisatie groot zijn. Nog eens 14,5 procent is het hier gedeeltelijk mee eens. Slechts 9 procent is het in meer of mindere mate oneens met deze stelling.

    Meer highlights:

    • Hadoop is het meest populaire dataplatform: 21 procent heeft een of andere Hadoop-implementatie (Hadoop, Horton, Cloudera).
    • Terwijl bij de licensed software SAP (8 procent), SPSS (7 procent) en SAS (6 procent) het beste scoren.
    • Datatoepassingen worden het vaakst gebruikt binnen marketing (19 procent).
    • Informatietechnologie is bij 13 procent een toepassing, terwijl fraudedetectie (6 procent) en riskmanagement (6 procent) ook regelmatig met behulp van data wordt uitgevoerd.
  • Four Drivers of Successful Business Intelligence

    BICompanies across industries face some very common scenarios when it comes to getting the most value out of data. The life science industry is no exception. Sometimes a company sets out to improve business intelligence (BI) for a brand, division or functional area. It spends many months or years and millions of dollars to aggregate all of the data it thinks it needs to better measure performance and make smart business decisions only to yield more data. In another familiar scenario, a team identifies critical questions the BI system can't answer. Again, months and millions go into development. But by the time the system goes live, market and/or company conditions have changed so much that the questions are no longer relevant.

    Building Better Business Intelligence Systems
    Today's challenges cannot be met by throwing more dollars into the marketing budget or by building more, or bigger, data warehouses. Ultimately, navigating today's complexities and generating greater value from data isn't about more, it's about better. The good news is that other industries have demonstrated the power and practicality of analytics at scale. Technology has evolved to overcome fragmented data and systems. We are now observing a real push in life sciences for a BI capability that's smarter and simpler.

    So how do we build better business intelligence platforms? In working with life sciences companies around the globe, IMS Health has observed a recurring journey with three horizons of business intelligence maturity: alignment of existing KPIs, generation of superior insights and customer-centric execution (see Figure 1).

    What does it take to advance in business intelligence maturity?
    No matter where a company currently stands, there are four fundamental steps that drive BI success: the ability to align business and information management strategy, improving information management systems integration and workflow, engineering BI systems to derive more value and insights from data, and making the most of new cloud computing technologies and Software-as-a-Service (SaaS) models for delivery.

    Step 1: Align Business and Information Management Strategy
    Many IT and business leaders recognize that the traditional "build it and they will come" mentality can no longer sustain future growth in agile and cost-efficient ways. To be successful, companies need to focus upfront on developing an information management strategy that begins with the business in mind. Through a top-down and upfront focus on critical business goals, drivers and pain points, companies can ensure that key insights are captured to drive development of commercial information management strategies that align with prioritized business needs. Leading organizations have achieved success via pilot-and-prove approaches that focus on business value at each step of the journey. To be successful, the approach must be considered in the context of the business and operational strategies.

    Step 2: Improving Information Management Systems Integration and Workflow
    Although technology systems and applications have proliferated within many organizations, they often remained siloed and sub-optimized. Interoperability is now a key priority and a vehicle for optimizing commercial organizations-improving workflow speed, eliminating conflicting views of the truth across departments and paring down vendor teams managing manual data handoffs. Information and master data management systems must be integrated to deliver an integrated view of the customer. When optimized, these systems can enable advanced BI capabilities ranging from improved account management and evolved customer interactions (i.e. account-based selling and management, insights on healthcare networks and relationships with influencers and KOLs) to harnessing the power of big data and demonstrating value to all healthcare stakeholders.

    Step 3: Engineering BI Systems to Derive More Value and Insights from Data
    Life sciences companies compete on the quality of their BI systems and their ability to take action in the marketplace. Yet existing analytics systems often fail to deliver value to end users. Confusing visualizations, poorly designed data queries and gaps in underlying data are major contributors in a BI solution's inability to deliver needed insights.

    By effectively redesigning BI applications, organizations can gain new insights and build deeper relationships with customers while maximizing performance. Effective BI tools can also help to optimize interventions and the use of healthcare resources. They can drive post-marketing research by unearthing early signals of value for investigation, help companies better engage and deliver value to their customers and contribute to improve patient outcomes. This information can advance the understanding of how medicine is practiced in the real world-from disease prevention through diagnosis, treatment and monitoring.

    Step 4: Making the Most of New Cloud Computing Technologies and Software-as-a-Service (SaaS) Models for Delivery
    Chief information officers (CIOs) are increasingly looking to adopt cloud technologies in order to bring the promise of technology to commercialization and business intelligence activities. They see the potential value of storing large, complex data sets, including electronic medical records and other real-world data, in the cloud. What's more, cloud companies have taken greater responsibility for maintaining government-compliant environments for health information.

    New cloud-based BI applications are fueling opportunities for life sciences companies to improve delivery of commercial applications, including performance management, advanced analytics, sales force automation, master data management and the handling of large unstructured data streams. As companies continue their journey toward BI maturity, getting the most from new technologies will remain a high priority. Leveraging cloud-based information management and business intelligence platforms will bring tremendous benefits to companies as approaches are revised amidst changing customer demands and an urgent need for efficiency.

    The Way Forward
    While each organization's journey will be unique, advancing in business intelligence maturity-and getting more value from data - can be achieved by all with these four steps. It's time for BI that's smarter and simpler and that realizes greater value from data. With focus and precision-and the support of business and technology experts-companies can hone in on the key indicators and critical questions that measure, predict and enhance performance.

    Source: ExecutiveInsight

  • How Big Data is changing the business landscape

    jpgBig Data is increasingly being used by prominent companies to outpace the competition. Be it established companies or start-ups, they are embracing data-focussed strategies to outpace the competition.

    In healthcare, clinical data can be reviewed treatment decisions based on big data algorithms that work on aggregate individual data sets to detect nuances in subpopulations that are so rare that they are not readily apparent in small samples.

    Banking and retail have been early adopters of Big Data-based strategies. Increasingly, other industries are utilizing Big Data like that from sensors embedded in their products to determine how they are actually used in the real world.

    Big Data is useful not just for its scale but also for its real-time and high-frequency nature that enables real-time testing of business strategies. While creating new growth opportunities for existing companies, it is also creating entirely new categories of companies that capture and analyse industry data about products and services, buyers and suppliers, consumer preferences and intent.

     

    What can Big Data analytics do for you?

    *Optimise Operations

    The advent of advanced analytics, coupled with high-end computing hardware, has made it possible for organizations to analyse data more comprehensively and frequently.

    Analytics can help organisations answer new questions about business operations and advance decision-making, mitigate risks and uncover insights that may prove to be valuable to the organisation. Most organisations are sitting upon heaps of transactional data. Increasingly, they are discovering and developing the capability to collect and utilise this mass of data to conduct controlled experiments to make better management decisions.

    * React faster

    Big Data analytics allows organisations to make and execute better business decisions in very little time. Big Data and analytics tools allow users to work with data without going through complicated technical steps. This kind of abstraction allows data to be mined for specific purposes.

    * Improve the quality of services

    Big Data analytics leads to generation of real business value by combining analysis, data and processing. The ability to include more data, run deeper analysis on it and deliver faster answers has the potential to improve services. Big Data allows ever-narrower segmentation of customers and, therefore, much more precisely tailored products or services. Big Data analytics helps organizations capitalize on a wider array of new data sources, capture data in flight, analyse all the data instead of sample subsets, apply more sophisticated analytics to it and get answers in minutes that formerly took hours or days.

    * Deliver relevant, focussed customer communications

    Mobile technologies tracks can now track where customers are at any point of time, if they're surfing mobile websites and what they're looking at or buying. Marketers can now serve customised messaging to their customers. They can also inform just a sample of people who responded to an ad in the past or run test strategies on a small sample.

    Where is the gap?

    Data is more than merely figures in a database. Data in the form of text, audio and video files can deliver valuable insights when analysed with the right tools. Much of this happens using natural language processing tools, which are vital to text mining, sentiment analysis, clinical language and name entity recognition efforts. As Big Data analytics tools continue to mature, more and more organisations are realizing the competitive advantage of being a data-driven enterprise.

    Social media sites have identified opportunities to generate revenue from the data they collect by selling ads based on an individual user's interests. This lets companies target specific sets of individuals that fit an ideal client or prospect profile. The breakthrough technology of our time is undeniably Big Data and building a data science and analytics capability is imperative for every enterprise.

    A successful Big Data initiative, then, can require a significant cultural transformation in an organisation. In addition to building the right infrastructure, recruiting the right talent ranks among the most important investments an organization can make in its Big Data initiative. Having the right people in place will ensure that the right questions are asked - and that the right insights are extracted from the data that's available. Data professionals are in short supply and are being quickly snapped up by top firms.

    Source: The Economic Times

  • How to Optimize Analytics for Growing Data Stores

    Every minute of every day, mind-blowing amounts of data are generated. Twitter users send 347,222 tweets, YouTube users upload 300 hours of video, and Google receives more than four million search queries. And in a single hour, Walmart processes more than a million customer transactions. With the Internet of Things accelerating at lightning speed – to the tune of 6.4 billion connected devices in 2016 (up 30 percent from 2015) – this already staggering amount of data is about to explode. By 2020, IDC estimates there will be 40 zettabytes of data. That’s 5,200 GB for every person on the planet.

    This data is a gold mine for businesses. Or, at least, it can be. On its own, data has zero value. To turn it into a valuable asset, one that delivers the actionable intelligence needed to transform business, you need to know how to apply analytics to that treasure trove. To set yourself up for success, start out by answering these questions:

    What Is the Size, Volume, Type and Velocity of your Data?

    The answers to this will help you determine the best kind of database to store your data and fuel your analysis. For instance, some databases handle structured data, and others are focused on semi-structured or unstructured data. Some are better with high-velocity and high-volume data.

      RDMS Adaptive NoSQL Specialty In-Memory NewSQL Distributed
    Example DB2, Oracle, MySQL Deep Information Sciences Cloudera, MonoDB, Cassandra Graphing, Column Store, time-series MemSQL, VoltDB NuoDB Hadoop
    Data Type Structured Structured Un/semi-structured Multiple Structured Structured Structured
    Qualities Rich features, ACID compliant, scale issues Fast read/ write, strong scale, ACID, flexible Fast ingest, not ACID compliant Good reading, no writing, ETL delays Fast speed, less scale, ETL delays for analytics Good scale and replication, high overhead Distributed, document-based database, slow batch-based queries

     Which Analytics Use Cases will You Be Supporting?

    The type of use cases will drive the business intelligence capabilities you’ll require (Figure 1).

    • Analyst-driven BI. Operator seeking insights across a range of business data to find cross-group efficiencies, profit leakage, cost challenges, etc.
    • Workgroup-driven BI. Small teams focused on a sub-section of the overall strategy and reporting on KPIs for specific tasks.
    • Strategy-driven BI. Insights mapped against a particular strategy with the dashboard becoming the “single source of truth” for business performance.
    • Process-driven BI. Business automation and workflow built as an autonomic process based on outside events.

    Figure-1-1024x449

    Where Do You Want your Data and Analytics to Live?

    The main choices are on-premises or in the cloud. Until recently, for many companies – particularly those concerned about security – on-prem won out. However, that’s changing significantly as cloud-based solutions have proven to be solidly secure. In fact, a recent survey found that 40 percent of big data practitioners use cloud services for analytics and that number is growing.

    The cloud is attractive for many reasons. The biggest is fast time-to-impact. With cloud-based services you can get up and running immediately. This means you can accelerate insights, actions, and business outcomes. There’s no waiting three to four months for deployment and no risk of development issues.

    There’s also no need to purchase and install infrastructure. This is particularly critical for companies that don’t have the financial resources or skills to set up and maintain database and analytics environments on-premises. Without cloud, these companies would be unable to do the kind of analyses required to thrive in our on-demand economy. However, even companies that do have the resources benefit by freeing up people and budget for more strategic projects.

    With data and analytics in the cloud, collaboration also becomes much easier. Your employees, partners, and customers can instantly access business intelligence and performance management.

    Cloud Options

    There are a number of cloud options you can employ. Here’s a quick look at them:

    Infrastructure as a Service (IaaS) for generalized compute, network, and storage clusters. IaaS is great for flexibility and scale, and will support any software. You will be required to install and manage the software.

    Database as a Service (DBaaS), where multi-tenant or dedicated database instances are hosted by the service provider. DBaaS also is great for flexibility and scale, and it offloads backups and data management to the provider. Your data is locked into the provider’s database solution.

    Analytics as a Service (AaaS) provides complex analytics engines that are ready for use and scale as needed, with pre-canned reports.

    Platform as a Service (PaaS) is similar to DBaaS in that it scales easily and that application backups and data management are handled by the provider. Data solutions themselves are often add-ons.

    Software as a Service (SaaS) is when back office software is abstracted through a hosted application with data made available through APIs. Remote analytics are performed “over the wire” and can be limiting.

    How you leverage data can make or break your business. If you decide to go the cloud route, make sure your service provider’s database and analytics applications fit your current and evolving needs. Make sure the provider has the expertise, infrastructure, and proven ability to handle data ebbs and flows in a way that’s cost-effective for you and, equally important, ensures that your performance won’t be compromised when the data tsunami hits. Your business depends on it.

     Source: DataInformed

  • Information Is Now The Core Of Your Business

    DataData is at the very core of the business models of the future – and this means wrenching change for some organizations.

    We tend to think of our information systems as a foundation layer that support the “real” business of the organization – for example, by providing the information executives need to steer the business and make the right decisions.

    But information is rapidly becoming much more than that: it’s turning into an essential component of the products and services we sell.

    Information-augmented products

    In an age of social media transparency, products “speak for themselves”– if you have a great product, your customers will tell their friends. If you have a terrible product, they’ll tell the world. Your marketing and sales teams have less room for maneuver, because prospects can easily ask existing customers if your product lives up to the promises.

    And customer expectations have risen. We all now expect to be treated as VIPs, with a “luxury” experience. When we make a purchase, we expect to be recognized. We expect our suppliers to know what we’ve bought in the past. And we expect personalized product recommendations, based on our profile, the purchases of other people like us, and the overall context of what’s happening right now.

    This type of customer experience doesn’t just require information systems; the information is an element of the experience itself, part of what we’re purchasing, and what differentiates products and services in the market.

    New ways of selling

    New technologies like 3D printing and the internet of things are allowing companies to rethink existing products.

    Products can be more easily customized and personalized for every customer. Pricing can be more variable to address new customer niches. And products can be turned into services, with customers paying on a per-usage basis.

    Again, information isn’t just supporting the manufacturing and sale of the product – it’s part of what makes it a “product” in the first place.

    Information as a product

    In many industries, the information collected by business is now more valuable than the products being sold – indeed, it’s the foundation for most of the free consumer internet. Traditional industries are now realizing that the data stored in their systems, once suitably augmented or anonymized, can be sold directly. See this article on the Digitalist magazine, The Hidden Treasure Inside Your Business, for more information about the four main information business models.

    A culture change for “traditional IT”

    Traditional IT systems were about efficiency, effectiveness, and integrity. These new context-based experiences and more sophisticated products use information to generate growth, innovation, and market differentiation. But these changes lead to a difficult cultural challenge inside the organization.

    Today’s customer-facing business and product teams don’t just need reliable information infrastructures. They need to be able to experiment, using information to test new product options and ways of selling. This requires not only much more flexibility and agility than in the past, but also new ways of working, new forms of IT organization, and new sharing of responsibilities.

    The majority of today’s CIOs grew up in an era of “IT industrialization,” with the implementation of company-wide ERP systems. But what made them successful in the past won’t necessarily help them win in the new digital era.

    Gartner believes that the role of the “CIO” has already split into two distinct functions: Chief Infrastructure Officers whose job is to “keep the lights on”; and Chief Innovation Offers, who collaborate closely with the business to build the business models of the future.

    IT has to help lead

    Today’s business leaders know that digital is the future, but typically only have a hazy idea of the possibilities. They know technology is important, but often don’t have a concrete plan for moving forward: 90% of CEOs believe the digital economy will have a major impact on their industry. But only 25% have a plan in place, and less than 15% are funding and executing a digital transformation plan.

    Business people want help from IT to explain what’s possible. Today, only 7% of executives say that IT leads their organization’s attempts to identify opportunities to innovate, 35% believe that it should. After decades of complaints from CIOs that businesses aren’t being strategic enough about technology, this is a fantastic new opportunity.

    Design Thinking and prototyping

    Today’s CIOs have to step up to digital innovation. The problem is that it can be very hard to understand — history is packed with examples of business leaders that just didn’t “get” the new big thing.  Instead of vague notions of “disruption,” IT can help by explaining to business people how to add information into a company’s future product experiences.

    The best way to do this is through methodologies such as Design Thinking, and agile prototyping using technologies should as Build.me, a cloud platform that allows pioneers to create and test the viability of new applications with staff and customers long before any actual coding.

    Conclusion

    The bottom line is that digital innovation is less about the technology, and more about the transformation — but IT has an essential role to play in demonstrating what’s possible, and needs to step up to new leadership roles.

     

    Source: timoelliot.com, November 14, 2016

  • Wat maakt een company profile een krachtige tool?

    Company profileWat is een company profile of bedrijfsprofiel nu eigenlijk en waar wordt het door bedrijven voor gebruikt? 

    Wat is een company profile?

    In een company profile wordt op een systematische wijze een analyse gemaakt van een bedrijf. Onderwerpen die hierbij aan de orde komen zijn:

    • Algemene feiten van het bedrijf
    • Historie van het bedrijf
    • Strategie
    • Identiteit
    • Doelen
    • Competenties
    • Product portfolio
    • Organisatiestructuur
    • Financials

    Maar waar wordt het nu door bedrijven voor gebruikt?

    In het bedrijfsprofiel worden zaken in kaart gebracht die u als organisatie zelf kunt beïnvloeden zoals bijv: bedrijfsstrategie, concurrentiestratie, R&D strategie, product portfolio of imago. Verschillende afdelingen binnen organisaties maken gebruik van company profiles voor verschillende doelen:

    Afdelingen Doel
    Strategie

    Ontwikkelen organisatiestrategie, concurrentiestratie of product portfolio; Beoodelen bedrijfsovername

    Marketing Bepalen imago, positionering
    Sales Voeren van acquisitiegesprekken; voorbereiden proposaltrajecten; realiseren cross-selling bij klanten
    R&D Leveranciersanalyse, ontwkkelen R&D strategie door inzicht in technologie van concurrentie
    Inkoop Leveranciersanalyse
    Finance

    Beoordelen financiele betrouwbaarheid

    Ervaring heeft uitgewezen dat het gebruik van company profiles de effectiviteit van bijv een acquisitiegesprek, cross-selling, bedrijfsovername, leveranciersselectie vergroot en verkleint de kans op verkeerde keuze voor leveranciers. Wilt u meer weten of een voorbeeld te downloaden klik dan hier.

    Bron: RK-Intelligence.nl, Ruud Koopmans, 4 November 2016

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