There is a big difference between what someone needs to know and wants to know. For example, if you are going to walk to a destination and you see dark clouds, you need to know if it will rain so that you take an umbrella. However, what you want to know is when and where it will rain as well as how intensely and for how long. Let’s apply this “needs versus wants” discussion to the emerging analytics movement.

One can debate if there is a substantial difference between business intelligence and business analytics. I prefer to not enter this debate. My observation is that BI involves reporting from previously stored data, possibly stored from two or more sources. In contrast, analytics creates new information from the stored data. Analytics involves asking questions that lead to more complex and interesting questions, and ideally answering the questions.

Needs versus Wants with Enterprise Performance Management

I view BI as satisfying needs, in contrast to analytics, which provides and supports the wants for an organization.

Although I research and observe what organizations do with BI (and I’ve co-authored a recently published book titled “Predictive Business Analytics”), my primary area of expertise is enterprise and corporate performance management methods. EPM/CPM methods have needs that differ from wants.

Before we explore some examples, allow me to briefly clarify: EPM/CPM is the integration of many typically disparate management control and improvement methods. It integrates them. The core EPM/CPM methods are a strategy map with its balanced scorecard for strategy execution; product, channel and customer profitability analysis (using activity-based costing principles); enterprise risk management; driver-based rolling financial forecasts; and continuous process improvement (e.g., quality and lean management initiatives).

Strategy Execution – Needs and Wants

The balanced scorecard is ideally derived from a strategy map. These two linked concepts were initially written about by Professors Robert S. Kaplan and David P. Norton. They recognized that executives were quite capable of formulating a good strategy. The executives’ frustration stemmed from failing to fully execute their strategy.

The professors observed executives were over-reacting to financial results reported at the end of a time period. They suggested that executives shift their attention to non-financial metrics, commonly referred to as key performance indicators, which are reported during the time period so that the financial results would be proactively managed.

When a strategy map is properly designed, it communicates the executive team’s strategy to the organization in a way that can be easily understood. This satisfies a critical need, because if employees do not understand the executive team’s strategy, which is often the case, then they will not clearly know how their actions and decisions contribute to executing the strategy.

Related to this, an organization wants to know the efficacy of interdependent KPIs and their target amounts, which ideally should have cause-and-effect relationships to guide and steer the organization to fully execute its strategy. That is where analytics kicks in. With correlation analysis, the KPI system design can be scientifically evaluated to assess the level of explanatory value, high to low, that each KPI has on the other KPIs. Correlation analysis validates the quality of the initially selected KPIs so they can be revised and improved to provide more traction.

Enterprise Risk Management– Needs and Wants

ERM is much more than complying with rules established by government regulatory agencies, such as mandates for banks. ERM addresses three categories of risk: preventable risk (e.g., fraud, bribery, violating policies); strategic risk (e.g., risks voluntarily accepted to generate superior financial returns); and external risks (e.g., non-controllable events that are cannot be predicted or influenced, such as earthquakes or foreign currency devaluations).

With ERM, the needs are to systematically identify and define potential risk event occurrences. The wants of ERM involve determining which potential risk event occurrences to mitigate and how much to spend doing so. Analytics provides the quantitative methods to balance an organization’s risk exposure with its risk appetite.

Customer Profitability Growth – Needs and Wants

Customers increasingly view products and standard services of suppliers in all industries as a commodity. As a result, suppliers are realizing that as their competitive advantage from their products is being neutralized, they must offer differentiated services, offers or deals to various customer micro-segments. Suppliers need to know which types of customers are most attractive to retain, grow, win back and acquire – and which types are not.

This need is satisfied by progressive management accounting practices, using activity-based costing principles, to calculate the levels of each customer’s profits to the supplier.

Although this reporting satisfies the need by computing each customer’s value to the supplier, the sales and marketing functions want to know how much to optimally spend retaining, growing and acquiring each customer micro-segment. They want to know what primary characteristics and traits, other than sales volume, differentiate high from low value customers. Analytics solves this with statistical methods like recursive partitioning with decision trees and by estimating the financial return on customers as if they are investments in a stock portfolio.

Needs and Wants

Business intelligence can satisfy needs. It can report almost anything that has happened. But analytics can tell you what you want to know – which is what caused things to happen and what are possible scenarios and their impact of what can happen. Understanding cause-and-effect relationships leads to better decisions typically via modeling. In the end, the difference between low and high performance is poor or good decisions. Satisfying the needs for information is not enough. Analytics anticipates what an organization should want to know after its information needs are met.