Understanding prescriptive solutions

Prescriptive Solutions

Prescriptive solutions: Get the Rx for your right course of action

By now, everyone is familiar with the phrase “big data” and what it means. As more and more data is generated, businesses need solutions to help analyze data, determine what it means and then assist in decisioning. In the past, solutions were limited to simply describing data by creating attributes for use in decisioning. Building on that, predictive analytics experts developed models to predict behavior, whether that was a risk model for repayment, a propensity model for opening a new account or a model for other purposes.

The next evolution is prescriptive solutions, which go beyond describing or predicting behaviors. Prescriptive solutions can synthesize big data, analytics, business rules and strategies into an environment that provides businesses with an optimized workflow of suggested options to reach a final decision.

Be prepared — developing prescriptive solutions is not simple. In order to fully harness the value of a prescriptive solution, you must include a series of minimum capabilities:

  • Flexibility The solution must provide users the ability to make quick changes to strategies to adjust to market forces, allowing an organization to pivot at will to grow the business. A system that lacks agility (for instance, one that relies heavily on IT resources) will not be able to realize the full value, as its recommendations will fall behind current market needs.
  • Expertise Deep knowledge and a detailed understanding of complex business objectives are necessary to link overall business goals to tactical strategies and decisions made about customers.
  • Analytics Both descriptive and predictive analytics will play a role here. For instance, the use of a layered score approach in decisioning — what we call dimensional decisioning — can provide significant insight into a target market or customer segment.
  • Data It is assumed that most businesses have more data than they know what to do with. While largely true, many organizations do not have the ability to access and manage that data for use in decision-making. Data quality is only important if you can actually make full use of it.

Let’s elaborate on this last point. Although not intuitive, the data you use in the decision-making process should be the limiting factor for your decisions. By that, I mean that if you get the systems, analytics and strategy components of the equation right, your limitation in making decisions should be data-driven, and not a result of another part of the decision process. If your prescriptive environment is limited by gaps in flexibility, expertise or analytic capabilities, you are not going to be able to extract maximum value from your data. With greater ability to leverage your data — what I call “prescriptive capacity” — you will have the ability to take full advantage of the data you do have.

Taking big data from its source through to the execution of a decision is where prescriptive solutions are most valuable. Ultimately, for a business to lead the market and gain a competitive advantage over its competitors — those that have not been able to translate data into meaningful decisions for their business — it takes a combination of the right capabilities and a deep understanding of how to optimize the ecosystem of big data, analytics, business rules and strategies to achieve success.