Business Intelligence and Analytics: How to Use BI

Ask any five business executives or managers what terms like BI and analytics mean, and you’re likely to get five different answers. One recent approach to differentiating the terms holds that “analytics simplify data to amplify its value. BI mainly summarises historical data, but does not simplify data nor amplify its value.” This perspective misunderstands what BI is, and in the process it undervalues what BI can do for FP&A teams that want to substantially extend their impact on company financial results. BI is essentially business information plus business analyses used to support decision-making in the context of core business processes that impact economic results. From that perspective, analytics are a subset of BI and the various kinds of BI are used in different ways for core FP&A tasks and activities.

What is BI and how is it used within core FP&A tasks?

Within the community of BI professionals and educators, BI is broadly defined as encompassing reports, scorecards, dashboards, multidimensional analysis, user-defined queries, ad hoc analysis, advanced analytics, predictive analytics and alerts. These forms of BI are different ways for business people to understand what has happened within the business in the past and leverage that understanding to try to impact what will happen in the future. They are using business information about the past – historical data – to influence the future. Let’s explore this using a hypothetical consumer packaged goods (CPG) manufacturer to illustrate how BI simplifies data, and thereby amplifies its value to business decision-makers.

  • Planning and budgeting: The FP&A team collaborates with brand managers, product managers, category managers, and others to develop an annual operating plan. The team uses historical data and BI in the form of advanced analytics to determine product volume growth trends, thereby simplifying data from millions of customer order line items and distilling it into a growth rate – such as item X has a compound annual growth rate of 2.5%. As part of the planning and budgeting process, the team uses BI in the form of predictive analytics to forecast future product volume based on the historical growth rate. Additionally, it is used to simulate volume growth under various assumptions about promotional spending and price elasticity of demand – these assumptions being informed in part by using advanced analytics to analyse historical consumer responses (item sales) to promotions and price changes. In these ways, BI simplifies data and amplifies its value.
  • Performance evaluation and management:  The FP&A team is a key player in the monthly evaluation of performance and exploration of opportunities and course correction options.  Toward that end, the team uses performance scorecards and dashboards to quickly identify the most significant sales variances in relation to the annual operating plan and in relation to the quarterly updated operating plan. The scorecards and dashboards simplify the thousands of monthly sales transactions into three key lists: (a) top 10 sales variances by customer; (b) top 10 sales variances by product and category; and (c) top 10 sales variances by channel. These lists allow responsible managers to focus on unfavourable variances as soon as the monthly close is completed, rather than having to wait one or two weeks for the information to be pulled together using conventional methods. Once the lists are available, managers and analysts use multidimensional analysis (drill-down and slice-and-dice) to obtain subsets of the historical (last month’s) data that pertain to the variances in their areas of responsibility. For example, the sales team might learn that sales are off at a particular grocery store chain, and then drill-down to see which products have unfavourable variances at which stores. The team might then use ad hoc analysis and/or user-defined queries to explore how these products are performing at other customers’ stores.  In these ways, BI simplifies data and amplifies its value.
  • Communication of management information:  Prior to deploying BI in its various forms, the CPG company used a manually-intensive, slow, and error-prone approach to communicating management information. Today, BI in the form of alerts is used to monitor sales data as it comes into the enterprise resource planning (ERP) system and notify responsible managers when there are material variances so that action can be taken. BI simplifies the information and amplifies its value so that managers don’t have to pore through mountains of account data to see how things are going. BI is also used to automatically generate standard reports, scorecards and dashboards that communicate key performance information – providing a common frame of reference that promotes more productive and fact-based business reviews. In these ways, BI simplifies data and amplifies its value.

In the article ‘Five Barriers to BI Success’ (Strategic Finance magazine, July 2011), the point is made that confusing terminology makes the value of business intelligence (BI) hard to determine, which slows adoption. One way for FP&A teams to move forward is to understand that there are multiple forms of BI, that analytics is but one form, and that all forms of BI rely on leveraging historical data to impact future business and economic results. It’s all business information in the end, and using BI within core FP&A tasks and activities is a huge opportunity for FP&A teams to optimise their impact.


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