Monday, August 11, 2014

Big Data Harmony

The critical step to solve analytics puzzle is to build people power and create Big Data harmony.

Big Data has big potential to help business grow revenue or satisfy customer, however, it takes both strategy and tactics to create such Big Data harmony, and unleash full potential of data analytics.

Data integration: Big Data effectiveness is certainly proportional to the degree of organizational integration. Big data – why breaking down the silos between marketing and IT is essential. One of the key factors driving the success or failure of a customer implementation is the degree to which marketing and IT work as a single team, but not just between marketing and IT, where the implied assumption is that all the organization's data is already clean and snug in the group data warehouse or dumped in a Hadoop environment, for example, ready to use, this is often far from the truth. Thus, the need to find an effective collaboration between the business and IT is an old challenge which is no different with big data. That said, getting this right is literally the battle ground and is therefore very critical. 

Mutual understanding: The deeper issue about the separation is between 'users' and 'developers'. There is a tradition of users asking for something, IT developing a large monolithic 'solution', and then the usual blame game where users claim IT didn't understand what they asked for and IT claiming users didn't specify it correctly! There is always a contradiction between users and developers. The better approach is to cascade as a combination of technology and philosophy that allows more users to easily and intuitively adopt the approach; the components could satisfy users and keep developers busy, give users the ability to create their own solutions from a suite of components: Building complex software that does the job they want done as easily as they draw an org chart. Then you have things done, users happy, IT happy, business operating, and accountants ecstatic! Though it is a long way to go. The point is IT shall work that allows users to dynamically construct their own software systems (including ones for fast, big data and real time analytics!), leveraging discrete components built by IT. It turns out that they makes users happy - they get what they want without delay - and also IT - they get to be more productive because they are building components rather than monoliths. That type of approach breaks down the artificial barriers between techs and non-techs and, for once, actually serves the business at hand.

Data quality: Clearly one of the top big data spending areas for these organizations is customer analytics. This is such a great fit for big data. So, you've got customers with omni-channel data points relating to customer behavior - past and, presumably, present trending to future. A kind of double-helix model of the relationship between customers and products/services which, theoretically, is going to illuminate potential -sell opportunities? However, consider the issue of data quality, which is critical in the success of any data initiative, big data or otherwise. Think of the data captured in the channel network. That's a lot of fast data sources - passing into predictive analytics with historical data temperance - leading to insight canvasses. Using 'fast data sources', not 'big data sources' is because - from observation of other operational areas such as compliance, end-of-day calls, operational resilience, etc. - this needs to be done as close to the point of observation as possible in order to respond as proactively as possible. Therefore, create a set of components (modules, micro-services, blocks) and make those available to the various bits of the operations under observation so that they can exploit validated code to build bigger, more immediate solutions that address dynamic questions. Components would include access to data sources, different analytical models, different alarm / alert outputs, recommendation services, etc.

People magic: IT is a key enabler. Marketing is a key user. But they're not the only stakeholders involved in making data valuable. So there are certainly more stakeholders at play than just marketing and IT in ensuring the sustainability of any sort of data intervention. While we may all agree that the silos need to breakdown, but how, is it about people magic? People with acute organizational smarts; people with well-developed relationship skills; people with the mandate to create a data environment as a strategic asset for the organization. It's these people that create a win-win environment between ALL relevant stakeholders to drive a well-governed, high-quality enterprise resource that the organization can use with confidence, subject to the reigning legislative landscape of course.

Big Data is a big puzzle, the critical step is to build people magic and create big harmony, in order to explore the untapped opportunities it can bring to grow business and improve organizational maturity.

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