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There is no doubt the amount of customer generated data in the social media these days are huge, to put it mildly. One of the main challenges that the organizations are faced with today is management of data. Managing data across the enterprise in the most efficient way is a challenge that can send shrills down the CTO's spine. The MDM guys will vouch for it. And all this, is for structured data. When it comes to unstructured data, as generated from social media sites like Facebook and Twitter, one can imagine the complexity of the data management technology. Traditional CRM systems are mature enough and they classify, transform and store data in a way that is not easily compatible with data generated from SCRM which is in its growth phase.
This post aims to bring in a thought process and stress the importance of having a data management policy that provides for ways to embrace the tons of data generated from SCRM in conjunction with the traditional CRM data. I'm sure we have heard about the Natural Language Processing (NLP) techniques used to analyze the unstructured and data and provide meaningful inputs. Semantic Web (anybody for Web 3.0 yet???) is another technology element being used for this purpose. Apart from this, parsing, mapping, pattern recognition and other techniques are used to make sense of a single line of unstructured data to a combination of inputs provided by a user at different times. The technologies exist and are being used by the current crop of SCRM application developers. What makes the management of this data difficult is the data classification policy that the organization wants to adopt. Starting from questions like 'what will be the best technology to get classifiable data' to 'where and how am I going to structure and store the data' to 'How to feed this into my BI apps and use this data for decision support', there is a lot of work to get done in this arena.
Data, as it was with CRM, will remain the main pillar even in the social era. The data management policy apart from other thing, should strive to maintain the accuracy of data, privacy (especially in closed door communities or gated communities), quality and master data maintenance. One should also make sure the data management policy is in sync with the social business strategy. Companies cannot afford to have one part of the organization socially enabled and leave the other part traditionally managed. This is applicable to the org wide data as well which will ensure feedback reaches the back end operations and will close the loop leaving no loose ends. The policy itself should undergo changes periodically and strive to evolve as a comprehensive plan. Without reforming the existing traditionally oriented data management policy to accommodate the social media, the enterprises will find themselves overwhelmed with the deluge of data the social era is going to throw at them.
Please add your valuable suggestions and point of views to take this discussion forward.
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