Much of the publicity around Big Data has boomed its power to capture large amounts of data and aggregate the results to make operational decisions. Admittedly there is value in this and many organizations are already realizing that value. However, these are mainly operational applications that need specialized computer systems and well-trained data scientists. Their decision makers must know ahead of time which operational variables to collect data about. Their data scientists must know where that data can be found and how to visualize it so meaningful decisions can be made.
At CIMS we concentrate on a different approach, one that we expect will have a much greater payoff for industrial organizations. We are developing tools and methods to use Big Data for making strategic and innovative business decisions in what we see as the next-generation decision: the data-driven decision.
In data-driven organizations, decision makers will formulate strategic questions such as which markets to enter, which products to develop, how to position the company, and whom to partner with. Unlike operational decisions where data type and location are known, strategic decisions cannot assume ahead of time what information is important or where it is located.
Staffing Decisions for Kelly Services
Kelly Services is one of several industrial organizations we have been working with on this approach. The global staffing services firm wanted to know if flexible staffing in healthcare was a commercially viable new service offering.
To answer Kelly’s key question we had to begin by looking broadly to determine what information was critical even if it was not presently known. Variables such as state-by-state payer regulations, the supply of healthcare professionals qualified to offer services in a flexible and/or distributed fashion, the demand for flexible healthcare workers, healthcare trends, competitor actions and their level of market penetration must all be assessed.
If you want to determine whether or not a new line of business is viable you cannot simply add up existing operational information and visualize it in some kind of dashboard.
Gather Unrelated Information
Making strategic and innovative decisions requires gathering seemingly unrelated information from disparate sources. Unlike operational data, critical information for strategic decisions is often qualitative in nature. For example, knowing that state legislatures are considering bills for telemedicine might impact flexible healthcare where staffing is critical, but you can’t add, subtract, multiply, or divide that information or render it on a traditional dashboard in any meaningful way.
Strategic and innovation decisions require information from a variety of sources not always knowable at an early stage of decision making. These types of decisions require a variety of inputs such as competitive environment, market attractiveness, trends, customer drivers, patents, regulations, competitor actions, etc. The inputs are usually a mix of information that may or may not be able to be mathematically aggregated.
The CIMS Big Data Process
Working with Kelly and other CIMS member companies, we developed and tested a process to use Big Data to help make strategic and innovative decisions (Figure 1). The process still requires specialized computer systems to handle large data sets as well as conduct natural language processing. But rather than just aggregating large amounts of information, we search through large amounts of data to isolate the critical information.
To read the full article on the CIMS Big Data Process click here
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