Monday, November 30, 2009

Information Overload & BI

In these difficult times we live in, when resources seem scarce, there is still one thing that is widely and abundantly available: information. According to the most recent statistics, the amount of information created annually by businesses and organizations, paper and digital combined, is growing at a rate of more than 65%. The amount of digital information being created in the world and distributed in emails, instant messages, blog posts, new Web pages, digital phone calls, podcasts and so on, will increase 10-fold over the next five years. The one fact that stands out is this: The growth of information is relentless.

There is too much of infornation available in various forms. Is it information Overload? or is it failure of Information filter? There is so much of information out there that one can't browse through every possible bit of information. Business Intelligence systems can play a very important role here. It can act as a information filter. It can provide information which is very critical and must need your attention. In today's world when someone have hundred's of KPIs to monitor, BI system can help to identify only those KPIs which needs immediate attention.One can start his day with BI portal. Typically, one follows the following routine
  • Check Emails
  • Check Calendar(Meeting Schedule)
  • Check Important News/stocks
  • Check Most critical KPIs
  • Prepare To-Do List for a day
  • Prepare/View status reports
  • Collabrate with collegues using Enterprise messenger
BI Portal can integrate all of the above information and show them on single UI. One need not to log into 5 different systems to perform the above tasks. Business Users will start their day with Business Intelligence system. Business users will also be able to relate some of emails/news with status of most critical KPIs. BI system can be tightly integrated with content categorization tool which can ensure that only relavent information is delivered to users as per their role and choice. Content categorization tool can also categorized documents/news as per meaning of the document/news items. This can help users to weed out information which is not useful. It saves users a lot of time from browsing through every possible infomation.

Saturday, November 21, 2009

Analytical MDM Vs Operational MDM

I was having interesting coversation about MDM with one of my customer last week. It's mid sized bank and they are in process of evaluating MDM. When i asked him  " How confident are you about quality of your data?" He said "Honestly, I do not know". Then i told him that for MDM one of prerequisite is to have good quality of data. If quality of your data is not good then MDM solution implementation is bound to fail.

I have seen quite a few organizations who would like to embark on MDM initiative without having good data quality system in place. Thanks to huge amount of marketing money spent by some of large IT product vendors. Quite often organizations fall in this trap and end up investing hugh amount of money and efforts.

There are two types of MDM solutions in market. Operational MDM and Analytical MDM.

Operational MDM is used to collect customer information at front desk. This solution is used to standardize the mechanism to capture customer information at various customer touch points in organization. Typically, organizations have 5-20 customer touch points. This solution provides customer information to various operational systems in organization.It ensures that any changes made in customer information at any of customer touch point are transferred to all operational systems. It will work in organizations which are still in process of implementing operational systems and have very few customer touch points. This approach requires discipline, and huge amount of training efforts. Currently most of banks in India have operational systems in place. These operational systems are built using old technology and captures customer information specific to their application.Enhancements to these oprational systems are very time consuming and lead to performance issues. Hence this solution will not be suitable for most of the large and mid sized organizations. It also requires huge amount of training efforts to train front desk staff on this solution.

Analytical MDM is used for historical and predictive analysis. This solution sources the data from transactional systems such as CRM, ERP, CBS, LOS etc...Analytical CRM can be updated once in a day or multiple times in a day. I have seen banks updating it once a day which is more than sufficient to cater to their current business requirements. This solution doesn't require retraining of front desk staff. However, it requires tight integration with transactional systems. Analytical MDM should be SOA enabled. This will enable source system to call web service and check whether new customer is already customer of bank or not. Analytical MDM will also provide information related to class of customer(Preffered, Gold etc) and behaviour based on past transactions. This will help to take decision about loan approval or issuing credit card or giving prefferential service to your customer.

The way Analytical MDM & operational MDM store the data is also different. Analytical MDM stores data in denormalized format so that it can be retrieved easily for analysis  whereas Operational MDM stores the data in normalized format so that it can be updated quickly.

Operational MDM stores demograhic details such as age, birthdate, name, address whereas Analytical MDM stores information related to profibility, behaviour score, credit score and propensity to buy product apart from demographic details of a customer.

Both types of MDM solutions require strong data quality engine in backend. This data quality engine should be capable enough to address peculiarities in Indian addresses and names.

Sunday, November 8, 2009

Task Based Intelligence

I was working on "Task Based Intelligence" concept few years ago. The idea was to integrate BI with operational systems. E.g when someone is creating a purchase order in ERP system, he will be able to see scorecard of a supplier without going to a seperate interface or application. The supplier scorecard is embedded into PO application. This will not only prevent PO going to a black listed supplier, but also gives flexibility to users to select supplier based on priority at that point in time. The supplier can be selected based on score which is determined based on the various parameters such as lead time, On time delivery performance, price & quality of supply(Rejection Rate).

The same concept can be applicable to banking industry as well. While granting a loan or credit card to an individual, the bank officer will be able to see application and behaviour score on LOS system. This will help him take more informed decision.

Discount coupons can be printed @ATM machines based on the amount withdrawn from ATM at that point in time. Just imagine a scenario wherein a discount coupon for a digital camera is printed @ATM machine when 10000 Rs is withdrawn from ATM. Competition is increasing day by day in every industry vertical. Margin is going down day by day. I won't be surprised if the bank starts selling cricket match ticket or flight tickets in near future to share the cost of infrastructure and therefore increase profitability of each branch & ATM.

In retail, discount coupons can be printed based on items bought by customer at that point in time. This will not only increase customer satisfaction but also ensure that the customer returns to store for more purchases in near future. Customer loyalty program is in very nascent stage in India. Hence such intelligence embedded into operational system will definitely help retailer to increase revenue per customer.