What is Happening?
In a Digital Business world, analytics is the lifeblood of the enterprise. Profit line managers use it to meet objectives, while finance use it to help manage the business. Wall Street demands it to make money from it. While money is the language of business, analytics is its handmaiden. The practical contributions of traditional statistical analytics and data modeling are seen in econometrics, scientific modeling, landing a man on the moon, six sigma, lean manufacturing, and are used in every industry and operating function, including sales, marketing, finance, talent management, sourcing and procurement, customer service, productions, logistics and product service among others. However, the uses of traditional computational analytics to support business operations are nothing compared with the competitive advantages from the uses of advanced predictive analytics, machine learning and intelligent machines.
As a new Leadership Report published for clients of our Business IT Strategy & Transformation research View indicates, we are on the cusp of a revolution in analytics that will have a far-reaching impact on businesses, governments and our daily lives. Advanced analytics with the digitization of our world will forever change the face of work, business models, and industrial markets as known today. The new advanced analytics – including data mining, machine learning, big data analytics and machine intelligence – while built on a foundation of statistical analytics, differs from it considerably. The new advanced analytics are not limited to numbers; but work on any data. The new advanced analytics are not limited to delivering fact-based descriptions; but go on to predict, prescribe, reason, and behave; in short, like an intelligent and sensing businessperson. Continue reading New Research Report Spotlights Advanced Analytics for Digital Business
In 2016, the reality of business, and therefore of business IT, is global. Digitally-driven disruptive change happens everywhere with few or no markets left untouched. With that in mind, a new Strategic Perspective published for Saugatuck’s subscription research client summarizes and present four globally disruptive forces of change that will shape and reshape business IT throughout 2016. All of these are examined in greater detail across the Saugatuck subscription research group; check our Lens360 blog for highlights, and search the Saugatuck research library for in-depth analysis and guidance by topic area.
The four overarching global and inter-related disruptive IT trends examined in this new Strategic Perspective are as follows:
- The challenges of “Ubiquitous Intelligence” resulting from the convergence of IoT, AI, automation and robotics
- Intelligent super-hacking, as business process infrastructure tools are also applied to malware and intrusion
- Globalization and dispersed workforces, affecting employment, recruitment and innovation
- Asian exceptionalism and its impact upon global IT
Continue reading Four Disruptive Trends in 2016 – The Normalcy of Global Disruption
The beginning of the year is a traditional time for prognostication. In a recently published Strategic Perspective Saugatuck takes a look through the looking glasses at some of the most likely significant challenges of 2016 that will influence enterprise IT directions and shaped the IT market. We labeled these as:
- Transforming IT. Saugatuck projects that 2016 will bring a rapidly increasing percentage of traditional IT environments being transformed to reduce costs, improve service delivery, and accelerate responsiveness to new requirements. IT environment transformations will consist of two separate but interrelated sub-transformations that will both enable and require each other. Within the IT environment the two sub-transformations are IT infrastructure transformation, and IT process transformation.
- Evolving Decisions From Intuitive to Informed or Insightful. Analytics will be integrated into a rapidly increasing number of business and IT processes in 2016. This will enable a transition from decisions based on intuition to decisions based on meaningful metrics. For an increasing number of processes, the adoption will go one step further and utilize cognitive analytics to move to decisions based on insights.
- Transforming Applications for Digital Business. A rapidly growing number of enterprises will embark on transformations to Digital Business during 2016. As Saugatuck has previously explained, the transformation to Digital Business entails changes in key functional areas ranging from product offerings to customer relationship. And, the Digital Business transformation is enabled by and requires changes in the IT environment ranging from IT infrastructure to IT processes to application solutions.
- Governing and Securing. As enterprises adopt Cloud-based offerings, the need for strong management practices and security increases. However, few enterprises are well equipped to deal with the new requirements. Cloud providers will find that the demand for both solutions and services will grow significantly in the coming year in the area of workload management, governance, and security.
Continue reading Welcome to 2016…the Beat Goes On!
Every business becomes a digital business and the use of big data, advanced analytics, and new digital business platforms radically reshape the nature of what it means to be a data-driven business. No longer are data-driven business those that use it to manage finance and operations. Rather, a data-driven business embeds data and analytics in digital business platforms to help customers and suppliers make their own near real-time business decisions.
Digital business footprints are obvious from the early successes of Amazon, Google and Netflix. The same is true of the digital transformations now underway in every industrial sector including those occurring at Argos, Atom Bank, Burberry, GE, Hulu, Microsoft, Siemens, Starbucks, Target, Tesco, T-Mobile USA, Uber and Walmart among many other enterprises. Digital business occurs through organic growth, spinouts, and new startups that at once challenge and support existing lines of industrial era businesses.
Digital businesses deliver competitive advantages as industry boundaries blur, coalesce, merge and as traditional approaches to data-driven business are augmented, complemented and assaulted. However, making the transition to digital business means the capabilities of data-driven business must be expanded beyond those of traditional data-driven business. Continue reading Digital Business: Not Your Father’s Data-driven Business
As Enterprise Risk Management (ERM) continues to advance as a concept, linking financial, operational, and GRC risk management across the enterprise, new opportunities are emerging from the application of Big Data. Business is about risk; and management of an enterprise is about risk management. Risk and opportunity are inextricably strictly linked, per the famous and somewhat mistaken Chinese character which has been a business management meme since the 60s.
Application of Big Data and Advanced Analytics to risk management can create enormous potential for a change in how firms are run. While current application of analytics to this area tends to remain relatively small and limited to niche areas such as fraud detection, immediate market changes, regulation and bug forecasts, and the like, the capabilities are growing exponentially. Application of Advanced Analytics directly to business processes can create a mechanism of advanced performance in which individual processes are modified in accordance with an immediate analysis of risk. Such modification and would enable an intelligent form of agility, permitting companies to respond to events where they might occur within markets, supply chains, business conditions, and other areas. This will have different effects in different industries, initially impacting financial services and other professional services that can be immediately tailored to meet changing conditions. Yet we can see the potential for integration with manufacturing, software development and the like. Continue reading Risky Business: Incorporating Analytics in the Engine of Risk
There has long been a problem in making analytics solutions available and accessible to the user. This has created innumerable trends toward simplification, and left many users with inadequate solutions. Large numbers of businesses and enterprise departments still rely upon spreadsheets to fill a significant portion of their Business Intelligence and data analytics requirements. However, the advent of Big Data and the advantages of Advanced Analytics are making simple solutions less possible and are raising the bar for analytics across all types and sizes of business.
Unfortunately, Advanced Analytics requires expertise that is not always available. While processing capabilities are becoming available on a SaaS basis from the cloud, experts are still required to formulate questions and produce understandable results. But what if we could apply Analytics to the querying process itself, and to the production of usable results?
New programs are beginning to do just that, with IBM’s Watson Analytics leading the way in providing a Natural Language Processing front-end for its Cognos analytics solution, and using analytics to provide immediately accessible visualizations to the user. All major analytics vendors are now moving in the direction of Natural Language Processing for queries, and a number of vendors are also moving into easy visualizations, as defined by market leader Tableau, that permit a naïve user to more fully grasp the implications of available data. Continue reading The Self-Aided Analytics Solution
Earlier this week, Saugatuck had the opportunity to talk to analytics provider Alteryx. Alteryx provides a tool that combines both ETL and Advanced Analytics into a single tool, which helps their primary customers – LOB analysts – get their analysis done faster.
Over the last 2 years, Alteryx has gained significant traction with a “land and expand” go-to-market strategy that targets LOB users initially and then expands internally, often with the support of IT. This strategy has helped them grow from 150 customers two years ago to just over 1,000 today (including EMC, Home Depot, Verizon, and Cardinal Health – see Saugatuck Lens360 blog post Alteryx Inspire – The Importance of Analytic Context, published 01July 2014). They have also been succeeding in deploying their Alteryx Server solution – which enables end users to schedule the analytics jobs, publish results and provide reports, on the public or private cloud, rather than just on a local machine.
Alteryx came at the advanced analytics market just at the time that companies were first considering Big Data solutions like Hadoop and MapReduce, but took a different tack. Initially their product aimed to Continue reading Catching Up With Alteryx
As Big Data continues to develop as a force shaping the enterprise, we can expect to see changes in business processes. Saugatuck has been monitoring the intersection between Big Data and intelligent business processes for the past several years. Developments in Big Data and advanced analytics have already had a substantial impact upon concepts of Business Process Management (BPM) including linkages with Internet of Things (IOT) and the industrial Internet; and the application of advanced analytics to analytic processes themselves. This contributes to a Big Data/Process convergence that is likely to have a continuing effect within the enterprise environment.
The application of Big Data directly to business processes such as manufacturing, finance, and supply chain processes, combined with autonomous operations enabled by real time evaluation and prediction, creates a new fabric for business operations. While much of this area has been focused upon manufacturing and is now being studied by governments and businesses, the digital business surround means that processes created within one domain are easily transferred to others. So, as rapid advances occur in linking processes to the Internet of Things through the Industrial Internet, we can expect rapid application of these ideas to other business areas such as human resources, healthcare, professional services, and the like. Continue reading In the Valley of the Blind, Autonomy is King
The importance of the API economy has been apparent for several years, and API availability and use is growing exponentially. To date, this growth has been fueled by mobility, with APIs providing a mechanism for enabling tiny apps on mobile devices to perform important tasks by invoking the capability of hosted applications. At the same time, Big Data and Advanced Analytics have been developing steadily and moving toward direct real-time integration with business processes. Analytics APIs, particularly the new machine-learning driven Predictive APIs (PAPIs), can provide the glue to bring Analytics and processes together.
Analytics APIs offer the possibility of real time access to analytics inserted directly into composite applications. This offers great possibilities for enhancement of business processes, but it also opens the possibility of combining multiple simultaneous streams of analysis on an ad-hoc basis, creating a variable and scalable artificial intelligence.
Predictive APIs are already here and are being provided by major vendors and startups alike. This includes Microsoft, which provides Azure machine learning, and Google, which provides its Prediction API currently in a beta. Emerging providers taking revolutionary steps in this area include BigML, Swift API, Datagami, GraphLab, Apigee Insights, Openscoring.io, Intuitics, Zementis, Predixion, PredictionIO, H2O, Yottamine, Lattice, Futurelytics, and Lumiata. As with many other technologies in the IT sector, a lot of the innovation is happening with startups. In this case, however, startups greatly expand their capabilities of the underlying technology by opening up a wider range of APIs for assembly to handle an ever-increasing range of data and outcomes. Continue reading API with Analytics Yet?
On the one hand, the IT function and organization for most firms has never been more about “data.” Big Data, data mining, advanced analytics, predictive analytics, real-time analytics, and so on rule media reports, analyst insights, event titles, the blogosphere, and provider announcements. The growth of Digital Business both feeds, and feed off of, data and more data. What used to be primarily a focus on software and infrastructure, many firms now see data and content providing their greatest growth.
On the other hand, data and its processing are every day less and less centered. It’s easy to see the proliferation of Cloud-based function-, application-, and group-specific analytics that accompany the parallel proliferation of Cloud-based applications and attendant data stores. And meanwhile, CIOs all over the globe are already telling us that because they can leverage Cloud capabilities, they want to never build another data center.
This has engendered some interesting discussions with the Saugatuck team and with our clients as well. If we as business and IT leaders are more and more about “data” every day, while we actively pursue non-centered uses, locations, and processing for that data, what do we do with the concept of the “data center?”
The data center concept grew because of traditional, centralized IT organizations, infrastructures, and policies that insisted that data was a valuable resource that therefore must be centrally held, controlled, processed, and secured. This version of reality became moot after the onslaught of desktop and portable computing, and has become even less meaningful to many in a Cloud-first IT and Continue reading Time to Rethink the “Data Center” Concept – and the Role of “IT?”