Business intelligence (BI), analytics and big data are the tools that many decision makers utilize to drive decision making in today’s business world. However, most organizations do not use the best or most effective methods when it comes to BI, analytics and big data. It is not that simple, as there are many forms and shapes of analytics, big data and BI. The result is this: decision making that is narrowly focused due to inadequate business intelligence, analytics and big data and/or the misinterpretation of one or all of them.
Business intelligence is not the end-all solution and approach that so many experts tout. The reason is simple: business intelligence, at its core, is no more than a very basic approach. Why? Business intelligence is all about telling us what ‘already’ happened and what ‘may’ happen. While this is also known as predictive analytics, it surely does not help a business decision maker with planning what to do if the ‘what may occur’ actually occurs. So, predicting something is of little value if it is not conjoined with an action plan to deal with the prediction coming true.
For example, let’s say you are a car rental agency. You are analyzing the car rental activity in a particular region for a period of time. You are using business intelligence and predictive analytics to give you insight to rental activity, seasonal fluctuations and car rental mix. This will give you guidance into the mix over a past period, but does it really help you with the future? Does it help you in planning the most efficient way to maximize resources? How does the decision maker determine what the rental car mix and allocation should be, since he/she does not really know what the rental car demand will actually be? How does future rental activity transpire and what should the associated fleet resources be? How should they be allocated? How should they be priced? How can he or she maximize profitability in the next 12 months?
This is where a new form of analytics comes into play, known as “Prescriptive Analytics,” also known as a ‘prescription for action.’
Prescriptive analytics are all about using a prescription, or preparedness plan, so a decision maker can maximize resources and profitability given certain business rules, customer demand and behavior. The airline industry has been a master at using prescriptive analytics to determine seat allocation to each class and the associated pricing. This type of analysis is not a simple undertaking, as it requires an organization to have an integrated analytics environment that is capable of this type of intense deep dive into data points, business rules and predictive modeling. For example, in the airline industry, margins are very thin. This requires a frequent and ongoing proactive or prescriptive analytics approach. An unexpected event like bad weather will require new resource planning as to seats and planes, i.e. optimizing the assets that are available.
The biggest problem with prescriptive analytics is that it requires the creation and maintenance of a large set of business rules; it could be thousands for a large organization. There can be immense overhead and a high error rate with so many variables. It only works if the analytics approach is integrated into every information system and every data base within an organization. It requires ‘buy-in’ from all functions and departments in an organization. The rewards can be game changing: the combination of business intelligence, predictive analytics and business rules can truly transform a company.
What does all of this mean? With advanced prescriptive analytics, along with tools and solutions, organizations can achieve an almost real time resource optimization and the resulting profitability. We no longer live in a world where pure data, or lots of it, are of any value. Data, information and business intelligence must be coupled with prescriptive analytics so that one can plan how to maximize the finances of expected and unexpected future events.
Currently, almost all analytical systems, approaches and technologies are concerned with ‘what has happened’ or ‘what will happen.’ Prescriptive analytics tell us how to best deploy resources and to optimize operational activities, all with one goal in mind: increase bottom line profitability.
In the world of inbound payments, outbound payments and treasury operations, think of how much value can be delivered to your organization with the utilization of prescriptive analytics. You will be able to allocate people and system resources and optimize all aspects of the management and control of money and funds movement. Your organization would be prepared for a new payment system/method or a new banking product/service being introduced into the marketplace, one that does not exist today. Most importantly, you can reasonably plan for the associated resources and the associated bottom line impact.