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SmartData Collective > IT > Cloud Computing > What’s the Difference Between Business Intelligence (BI) and EPM?
AnalyticsBig DataBusiness IntelligenceCloud ComputingCRMData ManagementSoftware

What’s the Difference Between Business Intelligence (BI) and EPM?

johnnyor58
johnnyor58
11 Min Read
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business_intelligence.jpgOne of my colleagues recently asked if I could write a blog post describing the difference between business intelligence (BI) and enterprise performance management (EPM) solutions. 

I haven’t been asked this question in a while, so maybe this is a good time to revisit these terms and technologies, what makes them different, and how they complement each other.&nbsp

Contents
One of my colleagues recently asked if I could write a blog post describing the difference between business intelligence (BI) and enterprise performance management (EPM) solutions. One of my colleagues recently asked if I could write a blog post describing the difference between business intelligence (BI) and enterprise performance management (EPM) solutions. 

business_intelligence.jpgOne of my colleagues recently asked if I could write a blog post describing the difference between business intelligence (BI) and enterprise performance management (EPM) solutions. 

I haven’t been asked this question in a while, so maybe this is a good time to revisit these terms and technologies, what makes them different, and how they complement each other.  So here goes.  

Let’s start with a little history lesson.

Business Intelligence Emerges From Decision Support

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Although there were some earlier usages, business intelligence (BI) as it’s understood today evolved from the decision support systems (DSS) used in the 1960s through the mid-1980s.  Then in 1989, Howard Dresner (a former Gartner analyst) proposed “business intelligence” as an umbrella term to describe “concepts and methods to improve business decision-making by using fact-based support systems.”  In fact, Mr. Dresner is often referred to as the “father of BI.”  (I’m still trying to identify and locate the “mother of BI” to get the full story.)

The more modern definition provided by Wikipedia describes BI as “a set of techniques and tools for the acquisition and transformation of raw data into meaningful and useful information for business analysis purposes.”  To put it more plainly, BI is mainly a set of tools or a platform focused on information delivery and typically driven by the information technology (IT) department.  The term “business intelligence” is still used today, although it’s often paired with the term “business analytics,” which I’ll talk about in a minute.

Along Came Enterprise Performance Management

In the early 1990s, the term “business performance management” started to emerge and was strongly associated with the balanced scorecard methodology.  The IT industry more readily embraced the concept around 2003, and this eventually morphed into the term “enterprise performance management” (EPM), which according to Gartner “is the process of monitoring performance across the enterprise with the goal of improving business performance.”  The term is often used synonymously with corporate performance management (CPM), business performance management (BPM), and financial performance management (FPM). 

CRAMP_cycle.png

These slight variations aside, the concept of performance management, in a business enterprise, is a set of processes and applications that help the enterprise link strategies to plans and execution in a continuous management cycle in order to achieve desired goals and objectives.  An EPM suite or platform typically includes prebuilt applications and tools to address the key steps in the performance management cycle:

  • Modeling – defining high-level goals and objectives, and business models.
  • Planning – annual financial and operating plans and budgets, periodic forecasts.
  • Financial Close and Consolidation – monthly, quarterly, and annual closing of the books.
  • Reporting – delivering results to internal external stakeholders for review.
  • Analytics – comparing actual results to the original budget or plan, prior periods, comparing results across divisions or product lines, etc., gaining an understanding of “why” the results vary from the benchmark, and deciding a course of action to correct course.

BI tools play an important role in the EPM process and system, enabling the organization to package and deliver financial and operational performance results to managers, the CEO, the board of directors and other stakeholders.  The results can be delivered in a variety of formats:

  • Formatted financial statements, such as the income statement, balance sheet, and statement of cash flows.
  • Divisional or product line profit and loss reports (P&Ls).
  • Actual vs. budget reports by cost center.
  • Balanced scorecards with key performance indicators (KPIs).
  • Management dashboards with graphs and charts depicting performance.

EPM processes and systems are typically driven out of the Finance organization and can extend into business operations.  In fact, while all of the terms mentioned earlier (EPM, BPM, CPM, FPM, etc.) generally denote the management process I described earlier, there are some subtle differences intended in the definitions.  CPM and FPM were intended to focus specifically on these processes as they relate to the office of Finance.  BPM and EPM, on the other hand, were intended to signify a more enterprise-wide approach to performance management. 

Analytics Takes Over as the Umbrella Term

“Analytics,” or “business analytics,” is the more modern term being applied to the broader domain of BI, EPM, and analytic tools and applications.  What I like about the term analytics is that it denotes a more “active” approach to consuming information.  Where BI is often viewed mainly as the process of gathering information, and formatting it for delivery to end-uses – analytics speaks more to the process of accessing, processing, consuming, manipulating, slicing, dicing, and drilling into the information to understand trends and get answers to analytic questions.  Here are a few examples of such questions:

  • Why were US sales above plan for Q1?
  • Why were compensation expenses over budget for Q2?
  • Why was last year’s operating profit below the target?

Below is the International Data Corporation (IDC) Taxonomy for business analytics, which depicts how all of these tools and applications fit together.  There are three primary segments to the market in this taxonomy. 

  1. On the upper left, you’ll see performance management and analytic applications. This includes financial EPM applications, as well as other analytic applications, such as CRM, supply chain, workforce, and others.
  2. On the upper right, you’ll see business intelligence and analytics tools. This includes query, reporting, multidimensional/OLAP, and visual discovery, as well as advanced and predictive analytics.
  3. Then underlying both of these segments is the analytics information management platform. This includes data integration tools, as well as data warehousing and management technologies that can serve up data to BI and analytics tools, or can be leveraged by performance management and analytic applications.

IDC_BA_Taxonomy.png

How EPM, BI, and Analytics Work Together

So the million-dollar question is, how do all of these tools and applications work together, and does an organization need to license all of these tools to have a complete solution?  The answer, of course, is it depends.

The nice thing is that most EPM platforms and suites include BI and analytic tools that can access the EPM data.  This includes ad-hoc and formatted reporting tools, scorecards, dashboards, as well as PowerPoint-, Word-, and Excel-based reporting tools.  So if you only need these tools to access your EPM data, you can typically get them from one vendor. 

This can be an effective approach for organizations just getting started with EPM as a replacement for spreadsheet-based planning and reporting processes.  It can also be an effective, one-stop shopping approach for organizations looking to replace legacy EPM applications. 

If your organization needs BI or analytic tools that can access multiple data sources – such as sales, marketing, supply chain, ERP, a data warehouse or other sources – then it will likely make sense to license standalone BI and analytic tools.  The good news here is that these tools can also access and consume EPM data and combine it with data from other sources if needed.  It may just take a few extra steps to export the EPM data into a format that can be consumed by the third-party tools.

A more recent development is that most of these tools and applications are now available as cloud or SaaS-based applications that don’t require any internal IT infrastructure to run.  They can be licensed on a subscription basis that includes the software, support and maintenance, infrastructure, and upgrades.  That means IT can spend less of its time setting up and maintaining infrastructure – and more time integrating applications and supporting end-user needs.

How to Learn More

Hopefully, this has helped clarify the definition of EPM vs. BI, as well and analytics, and how all of this fits together. 

Here’s a quick summary:

  • BI is a set of tools or a platform focused on information delivery, designed mainly for IT departments, and deployed to line-of-business users for general-purpose reporting and analysis across the enterprise.
  • EPM is a set of processes, supported by a suite of applications or a unified platform, that is typically driven by the Finance organization and extended into lines of business. It helps with processes such as modeling, planning, consolidation, reporting, and analytics.
  • Many modern EPM platforms include embedded BI and analytics tools, which can be used to report and analyze data from the EPM applications and other sources.

 

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