For years we have been told that data needs to be treated as a strategic asset, yet few organizations have demonstrated a native ability to do so. As information piles up like never before, the data-as-an-asset challenge comes with added urgency to manipulate huge volumes of data through a business intelligence platform that mines like a front-end loader, lifting, transforming and analyzing with scale and efficiency.

In reality, we know the majority of BI platforms operate like creaky steam shovels, or worse, like hand tools that pick away at huge stockpiles of data in the hunt for answers.

For many organizations, shovels and lesser tools might be the best we currently have to address business intelligence needs, but as your organization's missions (or management's questions) change, will you be able to find the answers before they, and you, become irrelevant?

Information as Competitive Advantage

Meaningful information can do more than suggest relevant actions to management; it can improve corporate health and growth. Forty-eight percent of today's Fortune 500 companies were not on the list 15 years ago. Many of the newer CEOs credit their information resources as a key strategic asset and differentiator in their ability to compete.

How are these firms ensuring that their current information needs are met and that their systems are flexible enough to meet future, unanticipated needs? At an increasing rate, they are finding the answer in a solid information framework of components that informs business decision-making on several levels. These include:

  • Operational metrics that serve to improve organizational processes.
  • Environmental metrics that measure external factors, such as competitive activity or other trends affecting your customers.
  • Strategic metrics that provide the snapshots used by senior management to understand the company's health and financial options.

Too often, individual departments look at their own operational metrics without respecting the need for an overall strategy for broad analysis. The same can be said for environmental and high-level management measurements - if they are developed without a framework to ensure the right metrics are created across the organization and the right data is going into them.
Most firms use organizational data to answer two questions that might be expressed as, "What has happened?" and "What is happening right now?" To do this, they usually select tools that provide hindsight and insight, but seldom consider the missed opportunities that could arise from a framework that enables foresight.

Consider this example of how an information framework can provide foresight that generates competitive advantage. In the 1990s, a major American car company began looking at metrics that measured the specific options customers wanted when they preordered new cars and what mix of features were selling the fastest from dealer lots. This information had been collected for years to streamline component ordering and operational efficiency, but had not been compiled into a framework for overall analysis.

Eventually, the company built an information framework to pull previously isolated metrics together and create the kind of data-mining front-end loader I referred to earlier.This information framework took the hindsight of past orders and the insight of the current product mix and looked across departmental metrics to compile options into packages for which customers would pay a premium. They were one of the first American car companies to determine what features created the most popular package groupings and planned manufacturing accordingly.

The information put to use increased profit per vehicle when compared with the previous mix of cars produced, giving the manufacturer a significant competitive advantage. In fact, this automaker is the only major American car company that did not take government funding during the recent economic crisis.

Dangers of Not Having a Framework

"I have metrics that work today for my organization. Why do I need to bother with a framework? It seems like a bunch of theory without practical return on investment."

Not only do many firms miss out on the benefits of foresight, but some even discover that data can become a liability when information frameworks are not in place. And the status quo approach to metrics may meet the immediate needs of the line manager, but it can create organizational blind spots. Let's consider some high-profile examples where metrics tracking was in place but a framework was not.

When MCI WorldCom collapsed, CEO Bernie Ebbers claimed he had been misled by incorrect financial information that arose from inconsistencies across financial systems after the merger. Despite this defense, he was ultimately sent to jail because he should have known something was wrong. It is easy to dismiss Ebbers as someone who was disconnected from his organization and should have asked tougher questions. But without a metrics framework to ensure the most visibility is derived from organizational data, gaps like the one Ebbers faced are likely to happen.

A few years ago, while defining a new framework of organizational metrics for a client during an enterprise resource planning implementation, a startling discovery was made. The existing systems and processes of the company relied on a series of financial reports that came from both unique country divisions and corporate headquarters for financial reporting. Unfortunately, while developing the information framework for the new ERP system, it was discovered that certain account accruals were being double counted to the tune of about $300 million. This oversight resulted in a charge against earnings and penalties from Wall Street regulators.

Reporting systems that don't have a solid information framework foundation are like a ship in the fog without radar; it is possible that everything is fine but there could also be some nasty surprises lurking just beyond the searchlights.


Creating an Information Framework

In the hope of avoiding dangers like those just described, many organizations begin to build a business intelligence system by selecting a technology and applying it across the entire business. Only later do they realize that the metrics and dashboards they developed do not help answer new questions that have arisen or address the information gaps hindering the business.

In practice, the technologies supporting business information are helpful, but they are only enablers of a framework, and as such, they should be addressed last. The value in business intelligence arises from raw data that is turned into information, and it is the framework we keep referring to that should contain the process from beginning to end.

An information framework establishes a process to figure out the current state of your organization's analytic capabilities, sets goals for where you'd like it to be and decides how to get your business analytics there.

Step 1: Assessment

In order to build a framework for the enterprise, it is important to know where the organization wants to go. To do this, it will be important to look at:

  • Overarching company strategies.
  • Business group objectives, processes and key requirement priorities.
  • Risks, constraints and assumptions.
  • Key metrics and key performance indicators already defined for the organization and any additional ones desired.
  • Data requirements and IT architecture.

Step 2: Discovery

Gather the assessment results to identify:

  • Assumptions under which the organization is operating with regard to data and information.
  • Gaps in the KPIs between what the organization would like to have and what is currently available.
  • Constraints in the data, processes or legal issues that may impact the available information.
  • Risks to the goals of the organization that can be addressed with the proper metrics.

Step 3: Roadmap

Determine and document what the implementation blueprint looks like:

  • Document the design solution.
  • Specify new systems/processes.
  • Conduct ROI analysis.
  • Define next steps.

To understand how this process works, consider the example of one longstanding Fortune 500 company, a high-tech business that realized the value of information to its operations early on. The firm had numerous lines of business with overlapping data requirements and saw the need to build an information framework consisting of metrics, KPIs and business drivers. It was only after a robust, flexible information framework was understood and constructed that the business could determine which technology platforms would best support it. During this process, they designed a framework that allowed them to determine what had happened (assessment), what the current state looked like (discovery), and the elusive roadmap that allowed it to analyze the information and decide where the organization wanted to go.
Throughout such a process, it is important to understand areas where business information needs are growing in order to develop a framework flexible enough to respond to future needs. Harnessing correct, current data and turning it into information in a timely manner to enable business decisions is a key differentiator that can have a dramatic impact on an organization's bottom line. Using an information framework to define your business metrics and how data relates across operational, environmental and financial areas will help your organization leave the picks and shovels behind for an efficient front-end loader.


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