After my post on whether the Application Transformation is a journey or a destination, I came across HP Fellow Kas Kasravi's article on Analytics and Legacy Applications -- Friends or Foes? I figured it would be an interesting exercise to see what Applications Transformation would be like from the standpoint of Information Analytics. Kas’s article prompted me to expand my suggestions in the context of Information Analytics:
- Business Alignment – Business objectives drive the nature and frequency of the analytics being captured across the enterprise. Frequently changing market demands and consumption patterns will require continued adjustments to the volumes of data being processed and the manner in which the information is gleaned out of this data. Key performance indicators will require periodic adjustments as well.
- Destination Definition - So, how will the performance indicators be effectively tracked end-to-end across the enterprise? What are the key pools of information to be monitored and tracked at an enterprise level? Are there departmental and regional variations that need to be accounted for? Answers to such questions will better define the destination from the standpoint of analytics.
- Incremental Transformation – Applications Transformation must happen in incremental phases -- especially from the standpoint of business analytics. First, you would track a core set of indicators that would be eventually expanded and detailed in the context of key business processes across the enterprise. Next, you would identify the core channels through which such information is collected – including traditional apps that track historical data as well as social media channels that give real-time visibility into today's environment. The combination of these perspectives will yield multiple phases of transformation during this journey.
- Continuous Evaluation - There is exponential growth of social networking technologies and the data being exchanged across such media. Applications transformation must be executed lock and step with these changes while adapting to new channels and data volumes. Infrastructure must scale up to accommodate the growth of big data. The transformation process must be continuously evaluated based upon these changes to avoid rapid obsolescence of the enabling solutions.
- Environment Stabilization – As mentioned in my original post, the current machinery must always be in a well-oiled state. Enterprises are best positioned to take on new challenges when the existing environment is stable with minimal, manageable disruption of service. The impact of the existing applications has to be continually taken into account while initiating new transformation projects.
Thus, there are nuances to the fundamental considerations for Applications Transformation from the standpoint of information analytics. Enterprises can realize business benefits by context specific processing of big data through Applications Transformation.
Do you see other considerations from the standpoint of Analytics when it comes to Applications Transformation? I would be interested to know.
Check out HP’s Application Transformation Experience Workshop video and viewpoint paper to see how we’re helping clients with their step-by-step plan for the transformation journey and for selecting their desired destination … or at least the choices for desired future state.