How to get your Social Media data operational in your strategy plan!

To get the proper use of your Social Media Data (SMD) in the enterprise structure, it is vital how good you are to crunch the unstructured SMD and make them operational.

This is not an easy task to make SMD operational as you as an enterprise have several parameters which you have to take into consideration;

1.      You have to match your SMD investments priorities with your business strategy- this is part of doing a strategy plan for your SMD.

2.      It is important to balance the speed, cost and acceptance in the enterprise organization to get success with implementing your SMD and get benefit from them.

3.      To secure focus and engagement from operation and at the same time have the proper capabilities you must have a plan to train the staff.

You have to match your SMD investments priorities with your business strategy- this is part of doing a strategy plan for your SMD
 
Integrating SMD with your business strategy calls for choices. Integrating of data and information can provide powerful insight but the cost of new data architecture and use and development of models and tools can be immense. In our world of scarce resources it is vital to prioritize our investments in SMD models and tools and make sure that we will get the best business strategy to work.
On very common problem working with your SMD is when the marketing function works in a siloed approach and have not been able to get the communication out to the individual business units in the enterprise. It is important for the enterprise that it works with one common approach. What is often seen is individual business units do send multiple offers across the enterprises entire base of customers, regardless of their profile or preferences.
Therefore top management must act towards the individual approach and decided that solving the problem would require pooling SMD in a cross-enterprise warehouse with data on income levels, product histories, risk profiles, and more. This central SMD database allows the enterprise company to optimize its marketing campaigns by targeting individuals with products and services they are more likely to want, thus raising the hit rate and profitability of the campaigns. A robust planning process often is needed to highlight investment opportunities like these and to stimulate the top-management engagement they deserve given their magnitude. 

It is important to balance the speed, cost and acceptance in the enterprise organization to get success with implementing your SMD and get benefit from them.

A natural impulse for executives who “own” enterprises SMD and analytics strategy is to shift rapidly into action mode. Once some investment priorities are established, it’s not hard to find software and analytics vendors who have developed applications and algorithmic models to address them. These packages (covering pricing, inventory management, labor scheduling, and more) can be cost-effective and easier and faster to install than internally built, tailored models. But they often lack the qualities of a killer app—one that’s built on real business cases and can energize managers. Sector- and company-specific business factors are powerful enablers (or enemies) of successful SMD efforts. That’s why it’s crucial to give planning a second dimension, which seeks to balance the need for affordability and speed with business realities (including easy-to-miss risks and organizational sensitivities).
Finally, some planning efforts require balancing the desire to keep costs down (through uniformity) with the need for a mix of data and modeling approaches that reflect business realities. But to develop a more sophisticated model to predict regional and seasonal buying patterns and optimize supply-chain operations, the enterprise has to gather unstructured consumer data from its SMD, to choose among internal-operations data, and to customize prediction algorithms by product and market approach. A balanced big-data plan embraces the need for such mixed approaches. 

To secure focus and engagement from operation and at the same time have the proper capabilities you must have a plan to train the staff.

When enterprises start investing in new tools for working better and more efficient with their SMD they often find that the productivity of its revenue management analysts is below expectations. This problem arises when enterprises neglect a third element of Social Media big-Data planning – engaging the frontline managers in the enterprise organization. But planning for the creation of such worker-friendly tools is just the beginning. It’s also important to focus on the new organizational skills needed for effective implementation. Far too many companies believe that 95 percent of their data and analytics investments should be in data and modeling. But unless they develop the skills and training of frontline managers, many of whom don’t have strong analytics backgrounds, those investments won’t deliver. A good rule of thumb for planning purposes is a 50–50 ratio of data and modeling to training.

The success with your Social Media big data depends on how good you are to make a strategy plan.

When a plan is in place, execution becomes easier: integrating data, initiating pilot projects, and creating new tools and training efforts occur in the context of a clear vision for driving business value—a vision that’s unlikely to run into funding problems or organizational opposition. Over time, of course, the initial plan will get adjusted. Indeed, one key benefit of SMD big data and analytics is that you can learn things about your business that you simply could not see before. The sooner executives change that, the more likely they are to make data a real source of competitive advantage for their organizations.