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Adding geographic and location context to business information enables organizations to develop fuller understanding and optimize the activities of people that use the information. We call this location intelligence, and to achieve it requires location analytics, which focus on that context where the processing and presentation of geography and spatial aspects of data are utilized. Analysis of geographic information can provide business insights that help organizations make better business decisions. I have written about this new generation of location analytics previously and noted that it can provide fresh analytic perspectives on information collected and integrated from in-house applications and across the Internet.

In our latest benchmark research on location analytics two VentanaResearch_LocationAnalyticsout of five (41%) organizations said it is very important to have information about location to improve processes and performance. Participants in business roles (51%) insisted more on its importance than did those in IT (30%); this difference indicates the importance of location to business professional to improve activities and processes they are responsible for improving. However, the research also shows that most businesses aren’t taking advantage of this enhanced perspective. Our Performance Index analysis found the largest percentage (29%) of participants at the lowest Tactical level of location-related performance. Almost all organizations have room for improvement: Only 12 percent said they are very satisfied with the available location information and analytics. Similarly only 15 percent are very confident in the quality of their location information.

vr_LA_location_analytics_requires_experiencesBringing a new perspective, location analytics requires familiarity to deliver benefits. Users that are very experienced in location analytics most often said it has significantly improved the results of their activities and processes (62%), compared to 23 percent of those who described themselves as experienced. To achieve this value organizations must invest in skills and knowledge of this domain for their analysts and tools that can help them derive value from this type of information.

As with other new areas of technology and analysis, to improve effectiveness using location intelligence will require a business case for investment. Our research found several barriers to building the case: lack of resources and lack of awareness (each cited by 41%), no budget (33%) and the business case not being strong enough (30%). While training and understanding of the potential of location intelligence are essential, some decision-makers need better examples of its use in terms of business results to make it an investment priority. In this regard organizations said the most important factors are to increase speed of response to customers, improve the quality of business analysis and decisions, and increase the accuracy of information. Nearly all that have adopted location intelligence said this focus has improved the organization’s processes significantly (40%) or slightly (56%).

The research found several key business areas in which value can be found. Improving customer relations is a significant driver for change: Two-thirds (68%) of organizations using location analytics and a customer focus will be changing the way they use it in the next 12 to 18 months. A focus on customers is a natural use of location analytics; our research shows that for more than one-third (37%) of organizations it is the type of information for which location is most important. The benefit most often ranked first by those analyzing customer data is to improve the customer experience and customer satisfaction (20%). But customer facing areas are not the only place to apply location analytics that can be especially useful in areas: optimizing sales efforts for territory management, identifying fraud for risk mitigation, optimizing routes and customer interactions across field service, routing optimization for distribution and warehouse management for supply chain management or identify best markets for advertising effectiveness.

The emphasis on location analytics by the lines of business vr_LA_location_analytics_improves_resultsappears again in funding for initiatives. It comes not just from the general IT budget (40%) but also from the business technology budget (31%) and the business budget (28%). And the investments pay off. Those that have invested in location analytics have improved the results of their activities and processes significantly (34%) or slightly (51%). Business people, who are better-positioned to see the benefits, indicated significant improvement three times as often (48%) as did IT staff (16%).

Analysts in the lines of business should assess their existing efforts and determine how the use of location analytics could improve the results they provide to decision-makers. One key tool for this is visualization through maps, which can provide more intuitive presentation of information than more general visualization. Simplifying the presentation of location information and making it easier to identify insights are essential for business professionals, who should not have to be trained to see the insights. Location Analytics is more than just a map and pretty picture, but a method to process data to get information for delivering geographic insights that are actionable and impactful to business. Organizations not yet taking advantage of this valuable supplement to their business information should evaluate it.


Mark Smith

CEO & Chief Research Officer

With much fanfare and a rarely seen introduction by CEO Ginni Rometty, IBM launched IBM Watson as a new business unit focused on cognitive computing technology and solutions, now being led by Senior Vice President Mike Rhodin. The announcement is summarized here:. Until now IBM Watson was important but had neither this stature in IBM’s organizational structure nor enough investment to support what the company proclaims is the third phase of computing. As IBM tells it, computing paradigms began with the century-old tabular computing, followed by the age of programmatic computing, in which IBM developed many products and advancements. The third phase is cognitive computing, an area in which the company has invested significantly to advance its technology. IBM has been on this journey for some time, long before the IBM Watson system beat humans on Jeopardy!. Its machine-learning efforts started with the IBM 704 and computer checkers in the 1950s, followed by decades of utilizing the computing power of the IBM 360 mainframe, the IBM AS/400, the IBM RS/6000 and even IBM XT computers in the 1980s. Now IBM Watson is focused on reaching the full potential of cognitive computing.

If IBM is right that cognitive computing will be the next wave VR_techaward_winnerof innovation in the industry and a new phase of computing, it has placed itself at the center of a substantial new market opportunity. Even at the most basic level to simplify the process of making information more available is what IBM Watson provides and our information optimization research finds is very important to 65 percent of organization. The company says it has invested $1 billion and placed up to two thousand skilled people in the new business unit. It also is spending $100 million on the incubation of companies that are building on the Watson platform, and has a new and dedicated building in Lower Manhattan, known as Silicon Alley, its focal point for cognitive computing ideas that IBM has unveiled to the public. There is no question that IBM Watson is innovate as we recognized in 2012 as being the recipient of our overall operation innovation technology innovation award.

These recent actions build on IBM’s announcement last fall that it is commercializing IBM Watson to enable developers and partners to innovate on the platform. Its launch of the IBM Watson Developers Cloud marketplace introduces new offerings and content essential to building its ecosystem of resources to meet existing and future demand for applications of cognitive computing. The step is essential in that it will maximize the number of products using IBM Watson and provide IBM with a springboard to exponentially grow its efforts. At the same time, IBM is working with academic institutions

IBM’s announcements included new products to complement the IBM Watson portfolio and give it a broader footprint and value to customers. The first new product announced is IBM Watson Discovery Advisor, a tool that helps pharmaceutical companies plow through massive volumes of big data. This is a good place to start, as harvesting the right information for specific roles and purposes is the foundation of cognitive computing, enabling organizations not just to access information but to synthesize it.

The next announcement was IBM Watson Analytics, a product previously known as Project Neo and introduced to the market last fall, which my colleague Tony Cosentino covered. Incubated in IBM’s business analytics group and using a spectrum of analytic and discovery technology, the product and people who worked on it and other efforts are being transferred to the IBM Watson business unit. Though it was not initially built for IBM Watson today, the discovery and exploratory technology integrates the pillars of analytics, helping facilitate a knowledge discovery process whereby you can explore data through natural language and discover new insights. The move to shift IBM Watson Analytics was unexpected and introduces new pressure to market and sell the product. It has growing potential for line-of-business analysts, who will want to examine this and other tools from IBM’s business analytics group. Only time will tell if IBM will be able to fully monetize the product’s potential through its IBM Watson effort, but the move could be its short-term method to gain customers and revenue. It definitely will be a complement when it interfaces to IBM Watson and utilizes the knowledge that Watson creates.

The next major product announcement was IBM Watson Explorer, a big data analytics tool that enables collaborative discovery, navigation and search across information in applications. Both analytics tools advance the science of big data technologies but focus on more than just the mechanics of what big data does, as described by the “four V’s”: volume, variety, velocity and veracity. Rather, they address the value of what is possible through the so-called W’s, focusing on the who, what, where, when and why. This is what we call information optimization, facilitating the business potential of not just big data but of cognitive computing. For its part, IBM is applying its big data and information management efforts to IBM Watson, categorizing them as IBM Watson foundations. This is critical as our information optimization research finds that organizations do not have enough capabilities to integrate and normalize information from disparate sources as the largest shortcoming of technology in 45 percent of organizations. By integrating and utilizing these big data and business analytics tools as part of IBM Watson, cognitive computing will from a competency perspective be more advanced even if these products are not directly needed for enabling IBM Watson.

With this much at stake IBM was not going to leave customer endorsements to chance, and while it has taken some criticism that customer commitment might not be as high as it has claimed, that question was answered at the IBM Watson event. For one, the medical and healthcare industry was front and center to validate its commitment to IBM, represented by organizations such as the Cleveland Clinic and Memorial Sloan-Kettering Cancer Center. Most interesting was an early peek at the potential of mass consumerization of IBM Watson. The first example was presented by e-commerce facilitator Fluid: Its Fluid XPS is focused on changing the digital experience of consumers by gaining access to information about their needs for products and services in a holistic manner. The example it promoted cold weather gear for camping by asking a question as a front end to the North Face website. A second example was the potential to have IBM Watson be the natural language interface for finding a vacation destination, specifying certain criteria like class, price, type and climate of location; today this requires repetitive tasks such as filling out forms and making your own comparisons to determine where you want to go and for what price. The concept was presented by Terry Jones, the former CEO of Sabre and Travelocity and chairman of Kayak. He has more than 40 years of experience in the travel industry and now consults about business innovation through his company, called Essential Ideas. IBM also demonstrated how cognitive computing can provide the next generation of marketing can synthesize the interactions and psychology of individuals to more effectively market to them. These examples point to the potential of enabling natural-language recognition technology to discover relevant responses that guide users’ actions and decisions.

As part of my analysis over the past couple of years, I’ve been following this step forward and wrote about the new category of cognitive computing. In 2013, IBM brought forward IBM Watson Engagement Advisor and focused on smarter customer service through a simpler engagement approach to improving the customer vr_NGCE_Research_01_impetus_for_improving_engagementexperience, a topic my colleague Richard Snow has assessed. This effort by IBM is as our customer engagement research has found is centered on improving the customer experience as found in 74 percent of organizations. I have also seen IBM demonstrate similar solutions for employees and managers as part of human capital management. More important, these solutions embrace mobile computing whereby devices can be used as input and response tools anywhere, at any time which our research finds smartphones accessible to be used in 73 percent of organizations according to our information optimization research. Intellectually, IBM continues to advance its research and scientific developments to ensure that it can transition its work into products that customers can use. At the launch of the IBM Watson business unit, IBM Research’s Dr. Guruduth Banavar brought forward some of the latest thinking on cognitive science and the ability to teach machines to reason and what is called neurosynaptics, a discussion that is available on IBM Research’s cognitive computing page. The material is fascinating; it provides insight on the future of computing and how it will impact roles and businesses in the next decade.

As it begins to scale its offering, part of IBM’s challenge is to manage the continuous information feeds that effectively make IBM Watson smarter. While IBM does not talk much about the content aspects of what is required, it is clearly more than just loading files, and these efforts are just as important as librarians are to libraries, whereby they are not just stewards to a collection of books but ensure the value and improvement of the library. There is still a level of mystery on the technical mechanics and readiness of the platform that the company needs to address before the natural-language interface is ready to work its magic. In addition, IBM is still using a natural-language form of text and working through how it can make voice mainstream with IBM Watson, as Apple and Google and others have done. IBM has been working on speech in research for some time and more recently with Nuance, who IBM announced a partnership with back in 2011, but it has yet to demonstrate this capability to the mainstream public, which indicates hesitation on how fast it plans to use voice and speech as the interface. While IBM was not able to fully monetize its early efforts in speech technology, it is now becoming mainstream in the consumer market but has yet to evolve significantly in the business markets as part of enterprise software. I am looking forward to seeing more of what it can do in terms of voice and speech input and Watson talking iteratively to help expedite what is truly natural language for humans.

IBM does not often create new business units and elevate them to this level of commitment and investment for the future. While the business goals for IBM Watson are lofty from both revenue and computing perspectives, no other company – not even Microsoft, Oracle or SAP – has both the established technology foundation and the people and financial resources that IBM has to make this a reality. IBM should be congratulated for making the investment in cognitive computing and helping create new jobs and opportunity that will incubate not just in Silicon Alley but across the globe as others realize the full potential. Our technology innovation research finds that increasing the value of an organization is very important to over half (56%) of organizations which is exactly what IBM is hoping will increase its business opportunity. If you want to catch up on the dialogue and resources related to this topic, you can search #IBMWatson on Twitter and follow @IBMWatson. If you want to learn more about IBM Watson and cognitive computing, go to and you will find more information about the technology, our research on the topic and the value of this new computing paradigm.


Mark Smith

CEO & Chief Research Officer

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