Application Data Mining

"A President's hardest task is not to do what is right, but to know what is right." Lyndon Baines Johnson

Knowledge is an appreciation of the possession of interconnected details which, in isolation, are of lesser value.

What do state of the art technologies, business growth initiatives, mergers and acquisitions, and business process reengineering all have in common?

Where they all represent typical activities of business expansion and cost cutting initiatives, they all face major realization barriers due to legacy applications and legacy databases.

Well, why not just rip and replace or rewrite?

Legacy applications entail many years of priceless knowledge and organizational values, key to driving your business forward. As such, they are a major organizational asset, albeit requiring some refurbishment.

The problem is, these assets tend to be entwined in a maze like application landscape, entailing huge amounts of bolt-ons, quick fixes, isolated applications, and redundant applications and data fields.

Sounds like a dilemma?

Don ™t rip and replace, don ™t rewrite. Instead, shed the shackles and realize the full potential within your assets.

Due to their longevity, Mainframe environments have survived organizational restructuring, mergers and acquisitions, and generations of differing management objectives. These, and other major organizational changes, logically imply the organic evolution of enterprise applications to address specific business needs spanning many years.

Notoriously poorly documented, non adherence to standards, focused mainly on hardware assets, and applications being developed in a reactive mode, there is a grave lack of transparency in organizational application environments, so the decommissioning or removal of any part of an applications is generally avoided due lack of visibility of the consequences. This in turn results in obsolescence, redundancy and sluggish development environments. This is the point where an asset becomes a part of an excess inventory, which is a non contributing financial burden. Tidying up these inventories, results in trimming off unnecessary cost “ up to 80% of IT Maintenance and Licensing, whilst creating a more agile environment.

The first step is a thorough audit and developing a corresponding application strategy.

At HTWC, we adapt both œTop Down  and œBottom Up  approaches to Application Data Mining.
Our methodology and tools are geared to firstly strategically position each application in terms of its potential asset value ( œTop Down ) and then to measure and record in the lowest levels of granularity ("Bottom Up"), the usage, dependencies and interdependencies of each single measurable unit. Finally, with the data, we are at the very least, in a position provide an application strategy, implementation plan, and roadmap along with the corresponding ROI forecast; information which in itself has an immediate positive effect upon shareholder value.

Both paths enable to review the application portfolio, determine the real business value of the various applications, understand how to reduce complexity and optimize utilization of key resources through consolidation of platforms, tools, and languages through which it can be understood how to shift resources from current maintenance to future innovation in order to better align IT process with the business. Through detailed application value assessment, an objective report that identifies areas where action is required is achieved.

Imagine the complexity inherent within the application landscape. Dependencies, interdependencies, direct and indirect. Regular interactivities, or only sporadic. Imagine the difficulty and excess cost involved in managing myriad platforms, languages, old standards, in-house developed architectures, methods, communication techniques and customized packages (where sometimes the custom code is larger than the package itself) and more than many times we see the reality with outdated documentation or simply non-existent. Even describing the scenarios is complex.

Auditing the application landscape to a very high level of accuracy is a very specialized project, which should be carried out by experts ™ specialized tools and methodologies. At HTWC, we have developed over the past few decades the technology that enables mining of application data, creating transparency of applications at the lowest levels of granularity; Dependencies, interdependencies, regular and sporadic interchanges, processes and workflow are examples of the different perspectives of which applications are analyzed down to their lowest level of detail. Our technology also identifies coding errors and enables œon the fly  repair work, but most importantly, the output is a clear strategy for each application element.

The knowledge acquired and subsequent benefits, are defining steps in getting IT assets into the shape required for the creation of agile and cost effective IT environments. Quick wins in terms of ROI projections and isolated application migrations are also immediately apparent. This creates a dynamic momentum, which is a huge benefit for management as part of the cultural change required as part of IT modernization and the implementation of future looking strategies.

To learn about ICON, our application data mining suite, please click here or read about the benefits achieved by Audi through their APM project