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CHAPTER 1
THE DATA-KNOWLEDGE CRUNCH
Evidence-based management is a simple idea. It just means finding the best evidence that you can, facing those facts, and acting on those facts.
Professor Robert I. Sutton, Stanford University
INTRODUCTION
To use a 19th century analogy to begin a book that explains how to overcome the 21st century challenges of converting ever-increasing amounts of data into insights that drive effective decision making might seem odd. But this is exactly what I will do, and for good reason.
Think of the California gold rush of 1849. People flocked en masse to that US state with the hope of making their fortunes from unearthing more of the gold that had just been found. A core tool, or technology, used by these prospectors was a gold pan, which would sift out gravel, sand, sediment and so on, but retain the heavier gold nuggets. By panning the endless tons of worthless silt, the prospectors hoped to find those few precious nuggets of gold that would make them rich men. A few did indeed become hugely wealthy, but most returned to their homes having either expended their investments without an adequate return (if any) or worse, bankrupt.
I now fast forward more than 150 years to the end of the first decade of the 21st century. Switching attention from gold prospectors to business managers - and analysing how the latter are attempting to secure financial and other gains from their particular economic and business landscapes - leads to a quite disturbing observation: most are behaving, and deploying interventions, in ways that are in reality little different to the gold prospectors of old.
Within enterprises today, business leaders are simply expected to pan masses of essentially worthless, or background, data, with the hope that somehow they will discover those golden nuggets that increase the wealth of the enterprise.
THE DATA AND INFORMATION EXPLOSION
To explain: thanks to a decade or so of breathtaking advancements in information and communications technologies humans now live in a world in which data, in all its forms, can be transmitted simultaneously to large numbers of people across the world by a single click of a button - and at the speed of light. Moreover, as a result of equally stunning technological improvements in data storage, much of the mass of data transmitted between employees resides somewhere in the enterprise - in databases, computer systems or other devices.
Within most medium to large enterprises the amount of data being exchanged and stored on a daily basis is almost incalculable: as is its value, because this data is the core material required for forming those āgolden nuggetsā of insights that enable the enterprise leaders to make better decisions and so ultimately gain measurable and sustainable financial and other successes.
And we should not forget that having rapid access to the best information for decision-making purposes is not just about securing the obvious gains such as increased revenue, profit or market share. Today, it might be as much about ensuring survival in increasingly networked and connected globalized economies by getting early warning signals of potentially catastrophic market problems or other failings. For instance, the credit crunch of 2008 led to the collapse of long-established and venerable companies such as Lehman Brothers and many other household names would have been lost to history if it were not for large-scale financial interventions by national governments. The aftermath of the credit crunch has been the destabilizing of global markets and national economies. As much as anything these events shone a spotlight on what can happen when senior managers lack insight into what is happening in their organizations and markets and when bad decisions are being played out in fully networked, global, marketplaces.
Only the most foolishly optimistic would believe that in todayās globalized economies the cataclysmic economic events of 2008 are isolated events. The implications are clear. Decision makers require a quality and accuracy of decision-support that is quantum leaps superior to a few short years ago. The rewards from getting those few golden nuggets of knowledge into the right hands at the right time might be astronomical.
THE FAILURE TO TURN DATA INTO MISSION-CRITICAL INSIGHTS
Yet, and despite the mouthwatering benefits on offer (be that growth or survival), few organizations are deploying practical, reliable and replicable processes for unearthing those mission-critical insights. Research into the working practices of most organizations and their managers confirms that the āgold prospectorā analogy holds true. Many organizations are content to hoard data, in the mistaken belief that simply having the data available is in and of itself value-adding, leaving it up to individual decision makers to pan for those golden nuggets. Management writer David Apgar is correct when he says in his book Relevance that although new technologies, such as faster processors, bigger storage and optical fibres have made data storage easier, relevance has become less important: āCheap information has tempted us to neglect relevance and led us into some bad habits,ā he writes (Apgar, 2008).
But not all organizations have fallen into bad habits. As one example, a global study (The Hackett Group, 2006) found that those finance organizations that were judged as world-class EPM (Enterprise Performance Management) performers generate significantly less reports than the non-world-class group - namely 691 reports per year per US$ billion in revenues compared to 1474, and the reports were also much shorter.
On first reading it appears that the world-class group was less productive and less value-adding than their non-world-class counterparts. However deeper analysis tells a very different story. The finance staff of the world-class group spent considerable time ensuring that the reports that they provided to business leaders focussed on the critical information that was required for decision-making purposes. They werenāt just throwing a mass of data at business leaders with the instruction to besieged managers that somewhere in the mass of pages delivered would be something of value. So, the unwritten message is that managers should get their knowledge prospecting pans out.
The world-class group recognized that they have a core responsibility to apply their analytic skills in the translation of raw data into knowledge. And the rewards to their firms of doing so were considerable. Over a three-year period the world-class group generated industry-relative equity returns that were more than twice that of the non-world-class group (The Hackett Group, 2006).
Research by the management consultancy Accenture confirmed the likelihood of greater stock market returns as a consequence of better analytics (Harris and Davenport, 2007). A survey of 371 companies found that 65% of top performers said that they had significant decision-support or real-time analytical capabilities - versus 23% of low performers. The same study found that 40% of top performers use analytics across the whole organization compared to 23% of low performers.
Yet, if organizations are today struggling to extract the greatest competitive benefits from their available data, there is no doubt that the scale of the challenge will grow significantly going forward, as year on year our capabilities to store and communicate data increase exponentially. To illustrate, as a result of the masses of data that it can access through myriad information and communication channels, the typical weekday edition of The New York Times contains more information than the average person was likely to come across in a lifetime in seventh-century England. However, research predicts that by the end of 2010 the worldās information base will be doubling in size every 11 hours (therefore, more than twice in each and every day!).
Humans are experiencing an almost unimaginable information explosion. We will soon reach the stage where it will be virtually impossible to point to a subject or topic for which there is a lack of data (although that does not mean that people will have articulated answers to the pressing questions related to those subjects/ topics, which is a central argument of this book).
What we are witnessing within most organizations, and across all sectors and industries, is that decision makers are being bombarded by an ever-expanding supply of data. This is placing them and their organizations under great strain, and led to what can be termed āthe knowledge crunchā. This term suggests the organizational paralysis that is being experienced as a result of possessing large amounts of data, but being incapable of converting this data into the key information required to support effective decision making. It is safe to argue that although most organizations are drowning in data they are thirsting for the relevant information to support key decisions.
Put another way, the more data that is available the easier it is to miss the most crucial bits of information being sought. Most readers would, at some time, have completed a Google or similar search and spent a significant amount of time in an increasingly frustrating hunt through many and ultimately irrelevant links before finding that specific piece of information they were looking for. The fact is, the required information was there, it was just hidden.
INVESTMENT IN BUSINESS INTELLIGENCE
Of course, most business leaders are acutely aware that they might have somewhere in their organizations the data or information that they require and that it is simply hidden away in a system, database or some other storage facility. And most are equally and painfully cognizant of the fact that as they see their information stocks snowballing and as the amount of data that is gathered grows, there is an urgent need to be able to analyse that information in a way that can add value and bring competitive advantage.
Most leaders, however, would acknowledge that analytic skills are in short supply, as confirmed by research evidence. A recent global survey found that more than half of organizations (59%) believe that they do not have sufficient capabilities to analyse comprehensively their data, while as many as 87% feel that their analysis capabilities need to be improved (Marr, 2008).
As a matter of urgency, organizational leaders are asking themselves a question of strategic importance: how to retrieve and make strategic, competitive sense of the mass of data that they possess or could access. With an acknowledged lack of adequate business analytical capabilities, many organizations have turned to information technology (IT) solutions in the belief that this will answer the question and therefore solve their data and analytics problems. In 2007 alone, organizations spent more than $4 billion on licence revenue for so called business intelligence tools (software applications that allow people to analyse data; see Box 1.1 for a definition of business intelligence and other key terms).
Box 1.1: Defining some key terms
ā¢ Data comes in myriad forms, including numbers, words, sounds or pictures but without context (e.g., 15/3, 5, 68).
ā¢ Information is a collection of words, numbers, sounds or pictures that have meaning (e.g., on the 15th March at 5pm we were all at 68 Victoria Street).
ā¢ Knowledge is where we take in and understand information about a subject that then allows us to form judgements in order to make decisions and act on that knowledge. We do this by using rules about the world that we worked out through having lots of information from the past.
ā¢ Business Intelligence refers to technologies, applications and practices for the collection, integration, analysis and presentation of business information.
ā¢ Analytics refers to the use of data and evidence, statistical, quantitative and qualitative analysis, explanatory and predictive models, and fact-based management to drive decision making.
Indeed, the worldās leading IT research and advisory company Gartner (2008) reported that business intelligence was the number one technology priority for the third year in a row, and that it is seen as supporting the top three business priorities of improving business processes, attracting and retaining new customers. Clearly, business leaders firmly believe (or at least hope) that the implementation of business intelligence tools will resolve pressing business issues.
In spite of their massive investments into technological solutions, there is little doubt that organizations are still failing to convert data into strategically valuable knowledge. The fact is that software alone will not solve the decision-support crisis that organizations are facing, and neither should they expect it to do so. As I explain in this book, technology is simply an enabler of the data to knowledge metamorphoses.
To be fair, it is unsurprising that organizational leaders can be seduced into believing that IT can resolve many of the issues that give them sleepless nights. As far back as 1963 an article in Business Week predicted that, āthe great day - when all the information for solving a management problem is only a push button away - is closer than you think.ā More than 45 years later we are still waiting for this āgreat dayā to arrive. Although the sensible among us realize that it never will, it is easy to see from the marketing literature that supports many of the business intelligence applications why many people might believe that analytics-related questions will indeed be answered by the simple pressing of a button.
You should also bear in mind that those at the top of organizations are experiencing IT as a āsecond languageā and have had to learn how it can be most effectively applied within organizations while the relevant technologies themselves were evolving at breakneck speed. When most of todayās senior managers entered the workforce, technology was little more than a mainframe computer that lived in a big room somewhere in the organization that only a few made use of or could understand. Personal computers might have been in the early stages of appearing on the desktop, but connective technologies such as the Internet and email were still unheard of outside of limited academic and military fields.
Those entering the workforce today, however, have a different story. They are experiencing technology as a āfirst languageā, and are as fluent in the language of technology as they are in their spoken language. When these employees reach senior positions they will be well aware of the shortcomings of technology (or rather what it cannot do or should not be expected to do), irrespective of how advanced technological capabilities are at that time: and we can have little doubt that they will be extraordinarily advanced.
EVIDENCE-BASED MANAGEMENT
Rather than being deployed in isolation, to be fully effective IT and applications have to be used in close alignment with the business goals and the information and analysis needs of the people in the organization. Such alignment creates a dynamic in which it is much more likely that the right management decision can be made because technology can be used to facilitate the answering of focused performance questions and the solving of specific business problems. And the best management decisions tend to be those that are supported by relevant facts and insights. This is where Evidence-based Management (EbM), the focus of this book, comes in.
EbM is an approach used by a growing number of leading organizations (such as Google, Capital One, Harrahās Entertainment and Tesco, to name but a few that I highlight within the book) to ensur...
