Business Analytics Implementation Strategy - Part I

I had met several senior executives last month to help them create strategy for implementing business analytics framework. I would like to address some of frequently asked questions by them in this blog.

Q: How do I embark on Business Analytics Journey?

For companies just embarking on the analytical journey, a specific business problem may be a good initial target. Perhaps customers are complaining about service or quality, or performance benchmarks show that a business process is wasting resources, or a competitor has raised the bar and you need analytics to determine and execute a response.

For any analytics initiative to be successful, there are 3 pre-requisities

1. Definition of Problem
2. Availability of Good Quality data
3. Business Domain

There are several techniques available to address each business problem. Without having specific problem in mind, it is very difficult to determine which technique to apply on data. Quite often, organizations share their data with business analytics vendors and expect vendors to suggest suitable business analytics applications on their data. This approach is very time consuming and doesn't yield expected results as there is no problem definition.

Problem definition can be as simple as

1. Share of wallet is very low with existing customers
2. Frequent stock outs at stores or excess inventory in plant
3. Transportation cost is very high

Each of the above problems can be addressed using different analytics techniques.

To increase share of wallet, you need to do segmentation & use Cross Sell/Up Sell predictive techniques.

To prevent stock outs or excess inventory, you need to use different forecasting techniques to accurately forecast demand.

To optimize transportation cost, you need to use different optimization algorithms.

Q: I am still in process of implementing data warehouse. Can I implement Business Analytics framework without having data warehouse in place?

Yes. We can implement business analytics framework without having data warehouse in place. You need good quality data to perform any analytics. Richness of data is also very important to use any analytics techniques effectively.

You need to have single view of customer in place to use Cross Sell/Up Sell predictive techniques effectively. If you have duplicate customer information then you may end up sending two different offers to same customer.You need to have customer demographic information such as birth date and occupation filled up properly in your data to use segmentation techniques effectively. You need minimum 36 data points to use forecasting techniques effectively.

I shall address the following questions in my next blog
1. How do I uncover Analytics Problem? I do not have analytics expertise in house.
2. Should I outsource Analytics work or should I build that capability inhouse?
3. How do I go about setting up Analytics CoE?

I had received execellent response for my earlier blog "Business Intelligence Vs Business Analytics". Thanks all for your encouraging commments. Do let me know if you want me to address any questions/doubts that you may have about business analytics.