Human Factor of Analytics

Analytics is not just about process but it is about people too. I feel, it is actually more about people than process. I have seen many companies complaining about the low ROI for Analytics Investments. Many companies have stopped doing any Analytics and has rather moved the investments to other process areas like Sales, Operations etc. It might be the right thing to do for them, but is the conclusion justifying?

Definitely not. The problem with most industry leaders in the industry is not understanding the basics of Business Intelligence and Analytics (BI Blog may help here). They just expect too much and too fast from it when they implement it. The most general problem I see are:

1. Heavy Initial Investments on BI Software : The Enterprise Editions of Analytics Tools costs in millions, and getting trained people and/or training people on those tools adds more to it. This simply puts too much pressure on the Analytics Division to function profitably.

2. Lack of Knowledge for Business Application : Analytics can never earn money. It can only facilitate to make more money. So through understanding of Analytical concepts and their business application needs to be taken care before actually implementing it.

3. Improper Mix of People : Companies tend to forget that Analytics is Knowledge Process and not a Business Process. It needs a mix of everything from strong statistical concepts to business understanding, from time efficiency to high quality assurance. So having people on board with similar profile and interests can only weaken Analytics output. More diversified the better.

Here I have tried to capture some of the Human Roles in Analytics Life-Cycle. Analytics Team needs to be aware of these people and know their profile, understanding, business role and aspirations.


• Customer: Customer is the initial and better data source. Any customer could be internal (organization staff) or external. Customer transactions produce huge data volumes daily. Customers buy, pay, deposit, order, register, allocate, cancel, navigate, have needs, have opinions, work, live, marry, study and make many other actions that have new data production or current data transformation as results.

• Business Analyst: Analysts must be qualified with business process knowledge and data manipulation skills. He is the person who links Business Managers to the Analytics Team.

• IT Staff: IT people contribution is necessary because they are the most appropriate to design in cooperation with business analysts the data repository and implement it. Also they could help in the ETL process design and its automated operation.

• Business Managers: Departmental Managers receive information about crucial metrics via different systems, like MIS, CRM, etc. In addition they receive clear and steady information for their customers, in order to plan next actions. They are the ones who are always worried about business functions, and they make sure strategic and tactical decisions are implemented and successfully executed.

• Departmental Heads: Information received by Departmental Heads or Directors differs than information get by functional departmental staffs. It is not so detailed, but contributes is a safe and real representation of business value. Heads belong to decision-makers group and mostly take tactical decisions.


• Data Mining or Business Intelligence Analyst: This specific analyst has to know data mining and business intelligence techniques and methods. He is the one who add value in business chain by establishing models and patterns for hidden information.

• CEO or Top Level Management: CEO, President, General Director are those who take the critical decisions for a company. They make strategic decisions based on company vision and values.

• Company Shareholders: Company’s Shareholders also have their own place. They are those who gains benefits from company’s revenues. They are but more worried about stable performance and continued growth of the company.

Ending Note:
It is very important to think about people while thinking about Analytics. So while choosing Analytics Vendor for Consulting or Outsourcing, or setting up In-House Analytics Division, I would recommend to make sure all these roles and limitations are well understood.