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Measuring KPIs is Passé

Originally published November 14, 2013

Measurement of performance when aligned with organization‘s strategic goals gives rise to the concept of business key performance indicators (KPIs). To achieve comprehensive measurement of business performance, most companies have invested in data analytics and business intelligence (BI) capabilities. Measuring and reporting KPIs has proven successful in assessing goals, monitoring performance and highlighting areas of concern.

On the other hand, while consolidating data and deriving insights is a complex ongoing activity, it is just a starting point in the quest for continuous improvement. Business ecosystems are evolving. The digital revolution is causing cross-industry boundaries to fall. It is imperative that continuous improvement be based on causal analysis of KPIs and the corrective action be institutionalized.

Beyond Measurement of KPIs

What can be done to take the next step beyond measurement of KPIs? Organizations must start linking the events and transactions that establish the KPI. By creating a map of causal actions that lead to the KPI variances, and then progressively controlling each such stimuli and business events, organizations will move up on the maturity curve of business intelligence. Further, by pushing the envelope to build advanced analytics into the system, actions being taken will be taken with a view of how future outcomes will be influenced.

In effect, the maturity path for business intelligence can be seen in terms of how actions are taken to correct, influence or control the KPIs. It is well known that about a 5% improvement in customer retention will result in 25% to 100% improvement in profitability. Similar statistics exist in various industries in various areas such as supply chain efficiency, online commerce and contact center processing, to name a few.

With these benefits, it no wonder that a Gartner research at the BI and Analytics Summit in 2013 found that 73 percent of companies intend to increase spending on predictive analytics, although 60 percent feel they don’t have the skills to make the best use of their data.

To help move to the stage where business process owners can not only understand what is happening, but also why it is happening and what should be done to correct it is the emerging goal of business intelligence. This vision is increasingly being made possible through improvements in technology and data processing.

There are four clear benefits of such an approach:
  1. Drives Accountability

    The concept of linking KPIs to causal analysis drives accountability throughout the process chain. An out-of-stock situation at a retail store could be a result of many related and unrelated actions – demand planning, late ordering, transportation, unexpected consumer promotions, reaction to competitive activity, etc. Linking KPIs to the causal actions that lead to the outcome will help stakeholders understand failure patterns and take corrective, systematic actions for both short and long terms.

  2. Enables Definition of an Action Framework

    Causal analysis goes beyond understanding reasons at the top level. Owners of the respective areas can now focus on designing a framework of actions (technical, data or process oriented). This framework can only be defined if all aspects of how an outcome is to be achieved are explored. This framework is almost like a strategy map of the specific process areas and how they interact with other related areas.

  3. Framework Implementation

    Implementing the framework often requires significant change management and stakeholder alignment initiatives. By highlighting the causes of failures, and the implied business benefits and impacts, it is easier to drive changes throughout the process chain and secure investments for any technological and data initiatives. In our retail example above, a framework will help drive a coherent analysis of consumer promotions, fulfillment as well as third-party research and trends data. In a more traditional setup, the issues would be cascaded to be resolved by the respective owners without a fully comprehensive central governance model.

  4. Continuous Improvement

    An implementation of a framework to control and influence business KPIs sets the right context for continuous improvement. Improvement happens are various levels – data aggregation, reporting, causal analysis, process improvements, technology upgrades and others. As the framework evolves, the specific process area – and related ones – benefit tremendously through this program-like execution that brings together the cross-functional organization. Organizations have historically relied on projects to make point changes, and a program approach lends the execution a more strategic angle, aligning it continuously with roadmap to a future end state.

Time to Evolve

BI and analytics initiatives must now evolve from measurement and reporting of KPIs to a broader framework-based, action-oriented analysis. This approach improves mapping of accountability throughout the process chain, ultimately leading to greater business performance.

  • Saurabh JainSaurabh Jain
    Saurabh is a Senior Director with Mindtree's Data and Analytics Solutions practice in New Jersey. He has more than 13 years of industry experience and has worked in a wide range of roles in the business intelligence (BI) and the data warehousing spaces to include end-to-end BI roll outs, master data management implementation, BI consulting, requirements elicitation and analysis. In his current role, Saurabh is focusing on large BI implementations, emerging technologies and analytics.

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