How CPAs Can Drive Business Intelligence

How CPAs Can Drive Business Intelligence

Man and woman discussing how CPAs can drive business intelligence

Deep insight into a company’s operations could mean the difference between merely breaking even or soaring to high profits. Although business intelligence initiatives seek to help provide this insight, when not organized or approached correctly, up to 70 percent of the budget for these initiatives can be squandered addressing people, process or governance issues (

A properly managed business intelligence program can fundamentally change the way a company looks at itself and makes decisions.

Business intelligence (BI) is an enterprise-level program focused on the analysis, distribution and contextual use of information for informed decision making and performance optimization. BI supports activities from the strategic level down to the operational level. When pervasive in an organization, BI can drive the transformation of business processes from mundane and isolated to information-rich and integrated.

BI in the Enterprise: Shifts Take Place

Because BI deals with “analysis,” many believe it is only applicable to the upper levels in an organization or isolated to a single, focused, data-intensive area. To realize the full value of a BI investment, however, it must be pervasive throughout an organization, provide information that is “actionable” and be usable by staff at all levels.
BI normally starts off as more of a passive, opportunistic activity, concentrated on the delivering information through analytic applications used by specialists or subject matter experts. After producing reports identifying high-level problems, these analysts focus on a specific problem to provide more insight. The reports are provided to senior managers who are expected to take corrective action. With this type of BI, the focus is generally more on maximizing efficiency and reducing cost. Analyses also tend to look at either one department or one problem at a time, relying on historical data and trend analysis techniques.
As senior managers start being held accountable for meeting prescribed performance targets, they, in turn, drive this initiative requirement down to middle managers who are expected to “make sure we look good.” At this point, more detailed information and timely analysis is needed, and a distinct cultural shift starts taking place. Instead of being reactive (get the report, then take action), users start wanting to be more proactive, asking questions such as, “What do I need to do to not have the report show bad numbers?”
To meet those needs, BI activities start becoming integrated into tactical planning and operations management. As middle managers use the “intelligence” provided to modify or adapt the processes they are responsible for, the focus now shifts to process effectiveness within, and among, departments.
Business strategy and execution is often defined at a very high level using end-point metrics, such as total sales and cost of goods sold, normally because this is the only level of information easily available. As greater insight into the business becomes available, metrics can be defined and gathered down to the operational level, business activities also can be modeled, and business assumptions and scenarios tested, to determine the impact of a high-level strategy to downstream processes and resources.
Consider the scenario of a company with the goal: “to increase sales of Product A by 15 percent.” Instead of merely having a one-dimensional view of the information, a comprehensive activity model can help do a “what if” analysis and determine the goal’s impact on many areas, including parts inventory, manufacturing capacity and activity levels, warehouse storage, distribution channels, and customer support. By entering different assumptions into the model – such as “increase price by 10 percent” or “increase units sold by 20 percent” – an organization can analyze the resulting data to determine what financial or operational impact different assumptions will have on the organization as a whole.
At this point, BI is now pervasive in the enterprise and provides a more holistic view of the organization and the interrelation of its activities.

The extended enterprise also can be included in a BI initiative by gathering data from customers, suppliers, business partners and other external sources. The data is used in the activity models to validate strategic assumptions and drive tactical planning. Think of this as a BI “nirvana.” Internally, the organization is working proactively and collaboratively. Externally, it is working with its value network and partners, constantly using “business intelligence” to manage the processes and optimize performance.


Enterprise Architecture for BI

BI is one of the enabling technologies for Performance Management (PM). A diagram from Gartner (Figure 1) perhaps best represents the relationship between BI and PM:

  • The foundation layer is the Information Management Infrastructure – all of an organization’s databases, servers, transactional applications, network and workstations.
  • The next two layers are each related to BI: 1) BI Platform, representing the “back-end” technical platform for storing BI data; and 2) Analytic Applications, “front-end” applications allowing users to access, analyze and report on the BI data.
  • Between the PM layer and the BI layers are People and Processes. The PM layer identifies the activities and metrics that should be monitored. It also defines the acceptable range of performance used to identify performance exceptions (e.g., significant variances or deviations from the norm). 


The CPA’s Call to Action
Business intelligence is no longer an isolated technology used by the IT department to produce reports. Since the key focus of BI is supporting analyses (a core competency of accounting) and performance management, we need to take ownership of enabling and supporting BI within our firms, companies or our client’s/customer’s organizations. 

CPAs should start by working with business units to identify the information needed to support and monitor business processes. This usually starts by looking at the information needed to support decision making – where does the data come from and how is it used? Another perspective is to look at key metrics of business processes that should be monitored and the acceptable range for each metric. We also can approach this from the internal audit perspective. What are the control points in a process and what data conditions identify an exception has occurred?

Once all of these requirements are identified, we should work with IT to develop a strategy for getting the data needed into the BI Platform. During this phase, we should review the processes and algorithms used to gather, compile and move data from operational data sources (transactional systems) into the BI Platform, ensuring that data quality (accuracy, correctness and completeness) is maintained.
To enable the business units to use the data, the proper reports or alerts must be configured in the Analytic Applications. Most modern Analytic Applications have Microsoft Excel-like functionality, making it easy for a non-techie to develop reports and wizard-type step-by-step configurations supporting the setup of alerts so that we can perform most of these tasks by ourselves.
Lastly, here’s the step most commonly forgotten and the most critical. We should work with the business units to help them understand how to work with the reports or alerts and understand the information being presented. Operational people may not have the background or knowledge to be able to understand what a report is telling them. Training them to understand what they’re reading, and helping them to understand what affect their work has the on numbers in the reports, is what really empowers them to take action. Remember that the endpoint goal is to enable people to make informed, proactive decisions, quickly, at all levels of the organization. CPAs also should partner with the IT Department to ensure the risks from the BI technical architecture are properly managed. As decision makers come to rely on the information provided by BI processes, we need to work with IT to ensure that systems are properly backed up and business continuity measures are put in place to prevent BI system downtime. And, of course, we should review the logical access controls over the BI data since the information often contains competitive intelligence that should only be accessed by those with proper authorization .

Starting a BI Initiative 
There are two different approaches to a BI initiative: top-down and organic growth. The top-down approach starts with high-level enterprise metrics and works its way down to the operational level, building the BI architecture as it branches downward. On the other hand, the organic growth approach focuses on a specific problem area first, which may be at any level of the organization. Once successful, it either replicates the BI model to other problem areas, or starts to pull in adjacent/related areas, thereby expanding the scope of its BI architecture. In either case, the key is to start with a project that is small enough to manage, but will have a big enough impact to make a case for continued funding. An organization then can incrementally build the BI architecture, bringing in additional data (either in breadth or depth) and expand the scope of the initiative.
As the scenario in the first section described, the demand for information and accountability for performance is driven down through the different levels and among the different departments of an organization. As a result, BI initiatives will grow themselves quite naturally. As this growth occurs, the key is to look at the cohesiveness and standardization of the BI architecture. The presentation of information, and the calculations and data it is based on, must be consistent for information to be used across the organization. Remember the mantra: “One version of the truth” – a goal BI shares with data warehousing, one of its supporting technologies. That leads to the last tip when starting a BI initiative: Start small, but think big. The eventual goal is to have BI pervasive throughout the organization, so even when starting with a small point project, consider bigger picture and organization-wide BI vision. This will help ensure the data structure is solid, yet adaptable (as the data collected grows), the technologies chosen are scalable to support the whole organization, and the application functionality is flexible to be used in varying analyses. 
Successful BI initiatives require a broad business perspective, high discipline and strong analytical skills, all of which CPAs exemplify. By starting small and incrementing on success, we can help empower decision making at all levels of the organization.