Pop-Corn Theory

The other day, I was in a market and saw a pop-corn seller. It amused me how people get attracted to smell of popcorn and start buying it. It was surprising to see the similarity between popcorn business with, what I call, the key to growth in any organization.

A popcorn customer stands in front of popcorn maker and watch which corn pops more and which one remains at the bottom. The popcorn seller scoop lots of “popped-corn” and few “unpopped-corn” into a paper bag. If a buyer is looking for value for his/her money then he/she asks the popcorn guy to give only popped corns.

In almost all the organizations, this pop-corn theory is applied, employees who popped on the radar of their managers are the ones who are bought for forthcoming opportunities and employees who are quite and still are grilled are sometimes called tough nuts remains at the bottom.
The question is: Is it good to have this theory? It makes lot of sense to buy only those corns, those are popped but what about those un-popped corns who still have potential to pop but due to negligence they are burnt and those who popped are sold after putting some more spice in them with butter.
Here I heard a customer saying that he loves chewing “pop(ped)-corns” and seller saying that his “pop(ped)-corns” are crunchy because he has grilled them well.

Baks

Data Quality Management – A wild elephant or a golden goose

There is a say in India – it is easy to buy an elephant but difficult to manage it’s upbringing. Today many companies are spending fortune on buying Data Quality Management solutions or are developing tools internally. Some are hiring top notch consultants and some are learning as they go. Point here is which model should be adopted in order to avoid buying a wild elephant and having him destroy the jungle of data.

This is a concern not only to the core companies but also for service vendors as it is getting difficult for them to develop a single solution and capability. Vendors are however safer in terms of the investment they need to do, but are more prone to the risk of losing credibility and business if they do not plan it well.

In order to avoid, shortfall of so called this wild elephant, consumers (IT Dept or Data Management Unit) can think on the following ten points:

1. What do they have today? – Different areas that they are working on.
Ø Data Types, Databases and Applications
o Vendor applications
o Internal Data Repository
o Others
Ø Services
o Consulting
o Analyst (Process, Business, Data)
o Custodian/Technician
o Developer/Tester

2. Where do they stand today in DQM?
Ø Maturity in each area mentioned above, on scale of 5
Ø With respect to competitor, on scale of 5

3. What level of expertise/recognition they have achieved in DQM, till date?
Ø Within Company
Ø Within Domain
Ø Within Market

4. What is the current market size and how much do they cover? Within a company it could refer to the user base and volume of data that their company deals with.

5. What technology(ies) they own or is/are partnering with?

6. What is sustainable in their current portfolio for next 3-5 years?

7. Within their current portfolio, what has risk of being vanished:
a. Due to its own life
b. Due to lack of focus
c. Due to competency lose
d. Due to customer/user limited requirement

8. What could be taken to next level:
a. Based on volume (# of resources)
b. Based on expertise (Tech. Consulting, Vendor Management, Vendor Selection, etc.)
c. Based on model (Customer managed to Vendor Managed, Introduction of current models like CMM, Lean Sigma)

9. What could be added in portfolio:
a. Services
b. Streams (Data Types, Functions, HR, etc.)
c. Technology/Tools
d. Models

10. What kind of investments they are planning to do?
a. Fixed (Aggressive/Conservative)
b. Progressive (Balanced)
c. Need based (Conservative)

Answering these few questions could bring lot of maturity in the strategy that a company or a vendor is preparing. A wild elephant with demolishing power can be a golden goose with unimaginable benefit.