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Thursday 20 December 2012

Linking Enterprise Master Data with Social MediaData – Social MDM

“By 2015, 15 percent of organizations will have added social media data about their customers to the customer master data attributes they manage in their MDM systems” – Gartner

In my previous post on Collaborative Data Management we analyzed how data governance, quality and Master Data Management (MDM) can be leveraged to bring about a coherent data conscious environment within an organization. But is data that can provide business insights present within organization boundaries alone? Well with the explosion of Social Media the answer is a big ‘NO’.
As a known fact, traditionally the customer buying pattern was analyzed from data gathered from in-house systems and leveraged for selling opportunities. The information that these systems provided are essentially what the customers wanted to provide, in other words the intelligence was limited to the data collected at the Point of Sales. With Social MDM in place the whole approach changes. Following are the recommended action points as to how organizations need to go about with their Social MDM strategy:
  • Determine Attributes: Strategize on potential application of different Social Media and identify new attributes
  • Integrate Attributes: Linking MDM within Enterprise and Identity on Social Media followed by Enhancing the ‘Golden Copy of Customer Data
  • Build Social Intelligence: Take enterprise to the customer on Social Media

Do you have a vision for your Business Intelligence?


A quick search on the internet on Business Intelligence brings up a myriad of results:
a)  Big Data analytics helps to analyze large volumes of data – Is this BI?
b)  Data Virtualization brings together enterprise data from multiple, disparate sources– Is this BI?
c)   Data discovery tools offer agility and high performance for faster data exploration – is this BI?
None of this is Business Intelligence. The term Business Intelligence (BI) is often confused for a technology. However, the technologies that go by the name of BI are only a means to an end. The end still remains the information, insights and actions delivered through this technology platform. This understanding is critical to the success of Business Intelligence.
An often cited metric about Business Intelligence is that more than 50% of BI projects fail. Even as one questions the veracity of the claim, it is but common knowledge that BI projects drag on for a long period without producing concrete business deliverables. One of the primary reasons that this happens and that BI projects are not considered successful is that success in a BI project is seldom established.
It is not often that organizations make a conscious effort to create a business intelligence vision, which underlines the success criteria for the BI platform. In many organizations, BI initiatives start with one section of the business and gradually evolve to cover other areas. When this happens or when there is an attempt to consolidate several independent local BI initiatives together into an organization-wide BI platform without a clear vision and a direction, the outcome is often less than desirable.
The BI vision is essentially a set of clearly defined business objectives and a bunch of relevant metrics to track the progress towards the objectives and the final outcome. It is important to ensure that there are metrics that reflect both internal (mostly relevant at the divisional level) and external effectiveness (relevant at the organization / market level) and that they are aligned with each other and to the business objectives.
BI Vision
There are several industry-standard methodologies such as the Balanced Scorecard, the Performance Pyramid that are available to deduce strategic metrics or performance indicators in alignment to the overall strategy / business objectives.
Do you want your BI program to be success? Do you have a vision for your Business Intelligence?