Is Analytics The Basis Of Operational Effectiveness Or Strategy?

Ajay Ohri

What type of decisions can you make with outputs of analytics? Are they only good enough to make Effective Operational decisions on campaigns, media choices, people likely to attrite etc.? Or can they be used to make the BIG, long term decisions of business?

So what is strategy?And how is it different from Operational Effectiveness?

Being operationally effective is not a strategy.  It is important and even a mandatory requirement of doing business. It is not a strategy.

Michael Porter wrote (back in 1996):

Operational effectiveness (OE) means performing similar activities better than rivals perform them. Operational effectiveness includes but is not limited to efficiency. It refers to any number of practices that allow a company to better utilize its inputs by, for example, reducing defects in products or developing better products faster. In contrast, strategic positioning means performing different activities from rivals’ or performing similar activities in different ways.”

The series of strategy questions are:

About doing similar activities in different ways:

  • Should these be activities we aim to do differently?
  • Can we do these activities differently?
  • Can we do them in a way that will give us a sustained advantage (or can they simply be copied)?
  • Should we do them at all?

About doing different activities:

  • What could we do differently to the rest of the industry/market?
  • If we did, would it distinguish us amongst our customers?
  • If we did would it position our delivery differently to our competitors?

So how can Analytics on past data be an input into Strategy which is forward looking and futuristic?

The answer is utilizing the Test and control methodologies. Using Analytics to weigh the short term differences in profitability (/ any core measure of success for a business) and project the long term expected trends of the same. In these the Design of Experiments adequate controls need to be establishes so that the variables and attributes in the data lead to valid conclusions.

In general usage, design of experiments (DOE) or experimental design is the design of any information-gathering exercises where variation is present, whether under the full control of the experimenter or not. However, in statistics these terms are usually used for controlled experiments (For instance, during drug testing, scientists will try to control two groups to keep them as identical and normal as possible, then allow one group to try the drug. ).An experiment is a methodical trial and error procedure carried out with the goal of verifying, falsifying, or establishing the validity of a hypothesis. Experiments vary greatly in their goal and scale, but always rely on repeatable procedure and logical analysis of the results.


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