Evolution of Business Analytics into Business Performance Analytics and Strategy

Fikret Sebilcioğlu

The Key Performance Indicators (KPIs) driven management has become the center of goal-achievement strategies. All operational levels in the companies generate and provide data using systems assisting them with day-to-day operations.

Business intelligence systems use these accumulated data kept in data warehouses (DW), to formulate and present KPI information to the stakeholders. Integration of these systems into a unified source of performance information and analysis capability is, however, hard to achieve.

In order to emphasize the importance of this integration, we, first, need two definitions:

  1. Business Analytics (BA) refers to the iterative, methodical exploration of analytical data (deriving from ERP, customer relationship management (CRM), big data generated in social media, open access databases, etc.) for operational and strategic purposes.
  2. Business Performance Analytics (BPA) is the control of business dynamics and performance through the systematic use of data (including micro-level data) and analytical methods.

Considering the two different definitions, it’s evident that BPA uses BA as a tool in control process of strategic execution. KPIs should be an output of BA process, and then should be an integral part of BPA tools.

Linking the BA process to unified strategy of the company and feeding the results into a unified BPA process as input help achieve an integrated guide to management of company strategy and decision-making success.

We can follow a stepwise approach to integrate our analytical systems and strategy. We need to:

  1. Define strategic targets in order to prepare a ground for all the control and evaluation activities,
  2. Model and quantify the variables of which realization constitutes a critical part for the achievement of any strategic objective – definition of KPIs,
  3. Search for data availability and evaluate the quality of data for the measurement of KPIs,
  4. Replace KPIs with no adequate data with a close substitute serving the similar purpose of strategic control and evaluation of targets,
  5. Start parallel projects in order to improve data availability and/or data quality for the replaced KPIs after cost/benefit analysis have been carried out,
  6. Construct a chain of relationship diagrams for KPIs, describe and model their cause and effect interdependence,
  7. Construct a continuous infrastructure for data to be fed into a business intelligence tool to quantify KPIs,
  8. Describe the current situation of the gap between the target and actual KPIs,
  9. Diagnose the root causes of the deviation from targets,
  10. Predict the ultimate result based on the current realizations and assumptions of the parameters in the time horizon,
  11. Communicate the results to all stakeholders, encourage prescriptive feedbacks as to the actions to be taken,
  12. Revise and, if necessary, reformulate strategy
As a conclusion, a company should take a holistic approach for managing business performance and strategy. The holistic approach enables the integration and use of operations, data, business analytics, business performance analytics, business intelligence systems, performance management systems and strategy formulation to achieve a single and complete view of the enterprise.