R&D's critical role in data analytics
Data analytics is still in its infancy and has yet to become a commoditized offering, so now is the time to use research and development to gain a competitive advantage and serve your customers.
Our industry has focused research and development efforts on finding new and better ways to work with the information we receive – and agile analytics are a byproduct of these efforts.
Beneath unstructured, seemingly non-relational data lie hidden treasures of new insights and opportunities. With the right techniques, real client problems can be solved by subject matter experts who understand the semantics, rules of behavior and decision rules in a specific domain so that the data extracted is relevant and organized for use in the field.
So why is research and development important to contractors?
Because unstructured data analytics is a brand new field that hasn’t been commoditized like other fields. But we have to remember to walk before we run – it’s better to try something at the pilot level first, and then experiment with the small portions of data that are extracted.
For example, if federal departments set up pilot programs before a large rollout, then they may not run into embarrassing and nerve-wracking situations. Pilot programs also save governments money because they make it possible for the agencies to put their arms around smaller, more manageable sets of requirements.
Then they can do a proof of concept, work the bugs out and make that system ready for primetime. They can look at the return on investment, evaluate the lessons learned, and determine how to expand the initiative into a larger, more complex set of requirements.
That’s why pilot programs are important in brand new fields like data analytics.
Analyzing data at the customer service level is no different than analyzing data for any other federal project. The role of customer service is to deal with incoming information and applications to register the people with a service.
Below are a couple of run-of-the-mill customer service analytics and questions that vendors should be asking their clients.
Call Center Capacity Analytics
Big data analytics can be used by contractors to optimize call center staffing and operation by providing answers to the following questions:
- Is the call center staffed right?
- What are the occupancy rates?
- What are the changes needed to meet a certain occupancy rate?
- What automatic and predictive analytics are in place to optimize?
- What analytical tools empower operations folks?
Digital Government Citizen Web Site Analytics
Using big data analytics, contractors can help the federal government in finding answers to questions like:
- How many hits, unique visits and unique users do we get?
- Where do these come from geographically speaking?
- What are the demographics associated with the traffic?
- What are the trends associated with the traffic?
- How do we empower federal operations teams to better assist citizens?
The volume of customer data keeps expanding at a velocity that is quickly becoming unmanageable.
The biggest question of all is: How do we reference these customers’ information and manage them to better serve citizens?
That’s where big data R&D comes into play.
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