Monday, August 25, 2014

Reporting Vs Analytics

I was asked to create a comparison between reporting and analytics for my customers. In my perspective, they are very different in many ways except they are integrated to each other in terms of data. Both of them created based on data from the database, but cooked in different way using different tools and consumed by different people. I would like to share the summary of them below :

Next, I add an article from a blog by Madish Desai which attract me :


I had met up with yet another prospect last week who was not aware of difference between reporting and analytical solutions. I would blame reporting tool vendor for this who has started confusing customers by positioning reporting tools as analytical solution. There are several differences between reporting and analytical solutions.

1. Business Objective
Reporting: Reporting solutions will help you measure performance of various business entities relative to business plan or target. It will help you convert data into information

Analytics: Analytical solutions will help you identify new products, customer segments, reduce cost, risk & fraud. It will help you convert information into knowledge.

Example: Reporting solution will tell you number of stock outs by items by store whereas Analytical solution will tell you about optimum amount of quantity that you need to keep in your store to minimize stock outs and opportunity cost.

2. Information Output
Reporting: Reporting solution output will help you quantify past performance.

Analytics: Analytical solution output will help you infer unknown facts and relationships. It will also help you quantify future probabilities.

Example: Reporting solution will tell you about best selling products in your portfolio whereas analytical solution will tell you about probability of  buying a particular product when your customer visits your store next time.

3. Output 

Reporting: Historical standard reports, dashboards, KPIs, cubes for OLAP.

Analytics: Predictive models, scores, forecasts.


  • Reporting: Top 10 products by revenue, Top 10 customers by region
  • Analytics: Cross Sell/Up Sell Model, Forecasting by Product by Region by Time

4. Queries
Reporting: Known, simple queries which can be easily optimized.

Analytics: Queries that become very complex as they evolve via iteration.

Reporting solution will help you answer the following questions

  1. What happened? When did it happen?
  2. How many? How often? Where?
  3. Where exactly is the problem? How do I find the answers?

Analytical solution will help you answer the following questions

  1. Why is it happening? What opportunities am I missing?
  2. What if these trends continue? How much is needed? When will it be needed?
  3. What will happen next? How will it affect my business?
  4. How do we do things better? What is the best decision for a complex problem?

Thomas Davenport has rightly said "Organizations that fail to invest in the proper analytic technologies will be unable to compete in a fact-based business environment."

Davenport says organizations successfully competing on analytics exhibit a set of common attributes, including:

  • CEO commitment – To use analytics as a basis for competition requires commitment from the top of the organization. It requires an allocation of resources, long-term funding and, in some cases, a shift in culture.
  • Strategic focus – Successful users of analytics don't just use analytics in general. They first define their distinctive capability and then use analytics to support that capability.
  • Enterprise application – Firms that compete on analytics don't manage it locally. They eliminate fiefdoms of data, centralize the data and expertise, and manage analytics at the enterprise level.


Source 1 : Phil Simon Blog
Source 2 : Manish Desai Blog

No comments:

Post a Comment

Share Your Inspiration...