Consumers of IT services in business have matured significantly in their understanding of, demands for and expectations from IT. The ease of access to data, its manipulation and ubiquitous consumption continues to increase. These are the results of a combination of industry competition driving down costs, expansion in processing power, data stored and network bandwidth. This leads to more educated and sophisticated consumers demanding technologies’ application into new areas that speed and facilitate benefit realization.
A major and rapidly evolving area of focus of this energy is the application of predictive analytics to anticipate and solve tough business and operational problems that threaten the quality of delivered services.
Enterprise business interest in the application of predictive analytics to the set of available services will accelerate as vendors compete to make the user interfaces to sophisticated analytics engines easier to access and manipulate, more flexible in application and the results easier to understand and respond to.
IT has been providing the enterprise with mountains of structured data and helping them derive information and insight from them. But, today’s world is becoming increasingly dominated by data and information that is unstructured, and comes in a heterogeneous amalgam of formats and arrives in escalating volumes and speeds. The challenge is how to rapidly develop and provide access to useful information and insight based on that data.
Operations Research, simulation and analytics have been around and in use for decades (even centuries). Yet, their use has been restricted to very large projects and deep-pocket enterprises.
Vendors are using accessible user interfaces to make predictive analytics available to a much wider audience.We recently spoke with some users about their experiences. Here’s what they told us:
In one case, predictive analytics was used to locate social service programs for the Department of Human Services (DHS) in a large city in North America. Using predictive analytics, DHS was able to locate and provide more services to more clients faster and at a lower cost.
For a global media firm, predictive analytics enabled more effective management of a development project portfolio. Using predictive analytics, periodic reviews help to identify at risk or underperforming projects earlier in the project life-cycle. As a result, management can decide whether to make changes to bring the project back on-track or terminate it. The result is to assure optimal investment of scarce investment funds.
Predictive analytics provides the capability to track and predict potential problems resulting from complex, multi-dimensional relationships between dynamic infrastructure and changing business services that overwhelm IT staff response times today. The complex relationships between changing business services and dynamic infrastructure also mean that analytical tools deliver the most value when they are utilized by a wide cross-section of IT and business users.
Making the tools more accessible to a wider audience through intelligent user-interfaces makes this possible.
Richard Ptak is a founding partner of Ptak/Noel.