Analyse this!

Never before has there been a more important time to make better decisions based on fact-based analytics. The financial crisis revealed the price of unreasoned assumptions, and today the same urgency applies to organisations in every industry. At a time when businesses are craving security in very unsecure times, data and analytics will provide them with the strong foundation and confidence they need to excel with minimised risk.

One major multinational took this path when it ventured out to become an analytical company in 2006 by launching a global initiative to manage information as a critical, competitive asset. The initiative encouraged the company to draw on, as on executive put it, "one source of truth" to fuel better business insights and, ultimately, better business decisions. The programme grasped an important principle about analytics: the opposite of an enterprise-wide perspective isn’t a local or independent perspective, but a fractured one.

To develop an enterprise-wide view of analytics, a company must do more than integrate data, combine analysts or build a corporate IT platform. It must eradicate all of the limited, piecemeal perspectives harboured by managers with their own agendas, needs and fears, and replace them with a single, holistic view of the company. It may sound like we’re proselytising for a Far Eastern cult, but this is really just an effective management practice.

Without a broad business perspective, a company cannot address the strategic issues at the core of business performance and organisational competitiveness. Vital management questions may go unanswered if information is fragmented:

• Which performance factors have the greatest impact on our future growth and profitability?
• How can we anticipate and influence changing market conditions?
• If customer satisfaction improves, what is the impact on profitability? Is customer loyalty more important than, for instance, order volume?
• How should we optimise investments across our products, geographies, and marketing channels?
• Are managers’ decisions well aligned with our company strategy, or are they merely promoting the managers' self-interest?

Analytics can illuminate these high-level questions only if decision-makers can see across regions, business units or processes and consider information from the entire enterprise. Furthermore, an enterprise perspective ensures that analytical data and models are treated with intellectual honesty. Without strict standards enforced from the top, the temptation to filter assumptions and risks through narrower, self-serving perspectives may be too great.

Strategic concerns such as performance and risk are not the only reasons to adopt an enterprise perspective; a coordinated approach also improves analytical activities in business processes and functions, including IT. Without an analytics strategy and road map, most IT organisations will struggle to anticipate and support business requirements. Lacking direction, project managers will be assigned to initiatives that produce little value, missing opportunities to work on useful projects. IT will default to supporting the easy analytics projects, or those for which they already have the data, or those with the squeakiest wheels. Even worse, they may admit defeat and supply whatever data they can get their hands on, hoping some of it will be useful. Robin DeHaan, executive at pharmaceutical company, Merck summarises the pitfalls of this fractured approach: "The repercussions are more ad hoc activity, more fire drills, and more spin-off databases...Expediency overrides strategy."

Without central coordination, business unit or functional managers will attempt to build their own analytic fiefdoms, as was the case at one Midwestern health care provider network. A vice president and a director there told us about analytics projects that are scattered among four groups and seven hospitals, network-wide projects that lack strong ownership, and top managers in the hospitals who do as they please with little oversight. As a result, they complained, it's hard to break analytics efforts out of institutional silos: "Nobody knows who knows what. Even as basic a task as creating a central data warehouse with all that scattered information is like recreating the federal government."

Duplicated efforts also lead to conflict and errors. Infighting breaks out between executives or groups of employees using different systems and data sources, because when their numbers and analysts inevitably disagree, each side claims its analyses are right. These analytical rivals operate at cross-purposes, undermining or competing with each other instead of cooperating.

A coordinated enterprise approach also reduces complexity. Absent knowledge of the company's analytical needs – or even which projects are under way or in the planning stage – can cause business analysts to buy the same data or software that others in the organisation have already bought. Thus, hundreds of data marts, reporting packages, forecasting tools, data management solutions, integration tools and methodologies spring up like mushrooms. One firm we know of had 275 data marts and a thousand different information resources, but could not pull together a single view of the business in terms of key performance metrics and customer data. Often, it is harder to rein in all this activity than it would have been to coordinate it in the first place. One consumer electronics company, for example, realised that by streamlining the 293 analytical systems and data feeds that had proliferated when the company began to adopt analytics, it could improve quality and cut costs.

Two-thirds of large US companies believe they need to improve their enterprise's analytical capabilities. And even though more than half (57%) of the companies we surveyed said they lack a consistently updated, enterprise-wide analytical capability, nearly three-quarters (72%) said they are working to increase their company's business analytics usage.

Most chief information officers (CIOs) recognise that only an enterprise IT strategy will derive real value from analytics. This same study found that 75% wanted to see an end to silos of information and 76% of CIOs planned to develop an enterprise business intelligence strategy over the next three years. But while their support was strong, more than half acknowledged that their company still lacked an enterprise approach to analytics.

If you are not a CIO, it may be natural to keep your head down and focus on what is in your own sphere of control. But that approach leads to bad decisions and self-serving projects, not judicious, enterprise-serving programmes. Our advice: take an enterprise-minded approach right from the outset of your analytical journey. Even in a stage one company, it’s best to look ahead, think about the future upsides and potential downsides to the enterprise, and treat even local, departmental projects as potential bases for broader initiatives.

Reprinted by permission of Harvard Business Press. Excerpt from Analytics at Work: Smarter Decisions, Better Results by Thomas H. Davenport, Jeanne G. Harris and Robert Morison. Copyright 2010 Harvard Business School Publishing Corporation. All rights reserved.