Chapter 9 A View over the Horizon
“The most important … contribution of management in the 20th century was the fifty-fold increase in the productivity of the manual worker in manufacturing. The most important contribution management needs to make in the 21st century is similarly to increase the productivity of knowledge work and the knowledge worker. The most valuable assets of the 20th-century company were its production equipment. The most valuable asset of a 21st-century institution … will be its knowledge workers and their productivity.
“Knowledge-worker productivity is the biggest of the 21st-century management challenges. In the developed countries, it is their first survival requirement. In no other way can the developed countries hope to maintain themselves, let alone to maintain their leadership and their standards of living.”
—Peter Drucker, Management Challenges for the 21st Century
Being in the business of helping companies leverage business intelligence (BI) to improve profit, we find it encouraging that such an esteemed management philosopher as Peter Drucker has devoted a third of Management Challenges for the 21st Century to the topics of the information managers needs and knowledge worker productivity. Drucker clearly understood that information and its effective use by managers and other knowledge workers is crucial for business success—”the creation of value and wealth” (Drucker, 1999). Because BI can deliver the business information and analytical tools that managers and knowledge workers need to improve knowledge worker productivity, what can we and should we expect from BI over the next decade? Equally important, what can we and should we expect management to do with BI over the next decade?
Just as the Internet, cell phones, and instant messaging have changed our way of life and enabled us to work smarter, BI holds great potential to revolutionize organizations by enabling them to become smarter about their business, compared with their competitors, to achieve a competitive advantage. Some of the real-world examples have been presented in this book:
Some organizations, such as Wal-Mart, recognized and captured the opportunities presented by BI. Other organizations, such as First American, used BI to help them combat external threats. Finally, some organizations, such as Whirlpool, used BI to further strengthen their positions in the marketplace, based on core competencies. Although many organizations have been slow to exploit BI opportunities, models of BI excellence clearly illustrate opportunities that are there for companies to capture.
It remains to be seen whether businesses in the future will take the lead of BI visionaries to craft BI strategies that enable them to improve their bottom line. Businesses have always looked to information technology (IT) to develop applications to automate and streamline operational processes in order to improve profits, and have been willing to make the business process and organizational changes needed to reap the benefits. In contrast, businesses have been generally slow to recognize the potential that data warehousing approaches afford to put in place BI programs that enable knowledge workers to recognize opportunities to improve business performance. Even in companies that aggressively move to improve operational performance through technology, process, and organizational change, it is not uncommon that their data warehousing investments have amounted to little more than Web-enabled legacy reports and providing databases so that business users can produce ad hoc reports. To reap the true potential of their investments, it will be necessary to move beyond this to craft BI strategies and employ BI programs that have the potential to have bottom line impact. The advantage that BI can bring is there for those who recognize and exploit its potential.
The ideal would be that, similar to the wholesale adoption of the Internet, most organizations recognize and capture the opportunity that BI affords over the next decade. This would markedly change the nature of business, adding a new type of competition—one that relies on companies outsmarting their competitors by coming up with new and innovative ways to use information for competitive advantage. Although hard to imagine, it was not long ago that few companies conducted commerce over the Internet. From a business strategy perspective, the issue that will determine the future of BI is not the lack of BI opportunities for profit improvement or a dearth of the technical and business know-how required to design and deliver BI applications that can improve profits. Rather, we see the strategic issue as a lack of top management recognition that business information and its exploitation by knowledge workers via relevant analytical techniques can be a core strategic competency that can make the difference between success and failure in the marketplace. We will present our ideas about underlying causes of this later in this chapter. Before that, however, we’d like to present our views on where we see BI heading over the next decade. With that as the foundation, we will then return to the reasons we believe management has not yet stepped up to the plate in many cases when it comes to leveraging BI for profit improvement.
9.1 Business Intelligence Moves into the Mainstream
As we noted throughout this book, there are more and more documented cases of BI bottom-line successes and these successes are increasingly being published in business publications. In addition, there is more of a focus on business performance measurement, including the popularization of Balanced Scorecards, dashboards, and the use of key process indicators (KPIs) in the marketplace. Although led by vendors, the need for performance-based management is being increasingly recognized and adopted by businesses. We believe that as business executives increasingly recognize how improved BI capabilities can lead to improved business performance, there will be more business attention paid to BI and an increased willingness to make the changes needed to achieve it. As we discussed throughout this book, business leadership is essential to achieving BI and is currently lacking in many companies.
9.2 Decision Process Engineering: Equipping Knowledge Workers with Information and Instituting Standards and Accountability
At many points in this book, we have stressed the importance of driving the use of BI into business processes that impact profits, be they management processes, revenue-generating processes, or operating processes. This is happening in more and more companies, and we see it continuing as followers and laggards look to catch up with innovators.
Although most companies have well-defined operational processes for line workers and hold these workers to standards of performance, few knowledge workers, who are responsible for strategic and tactical decision making, are held to the same standards of performance. Operational reports that are produced by operational systems have typically provided the information needed to measure and manage the operational performance of workers. In many cases, the information needed to support strategic and tactical decision making by knowledge workers has been of low quality or unavailable. Because strategic and tactical decision making requires historical views and analyzing trends, as well as seeing views of the business that crossed functional areas or lines of business, before data warehousing this information was often unavailable. As a result, managers learned to make do with little information and to make many decisions based on their experience rather than on the numbers. In many organizations, even when the information is available to improve upon knowledge worker performance and to hold knowledge workers accountable for their decisions, ad hoc approaches still prevail. As a result, in many businesses operational processes are defined, measured, and optimized, whereas strategic and tactical decision processes are not. As a result, although a business may have achieved high levels of productivity, optimizing operational performance, they may not be doing the right things. An example is the Whirlpool case study: before their BI initiative, the manufacturing operation may have been producing their quotas of washers, not knowing that they were producing defective washing machines if they had purchased defective parts from suppliers. The management decision to use the “best suppliers” based on quality and price is now possible because this information is available. Now that information is available on both price and quality of supplier parts, how that decision is made can be defined and measured as a knowledge worker decision process. Ensuring that these knowledge worker decisions are optimized will lead to improved business performance.
Looking ahead, we see an opportunity to re-engineer knowledge work by marrying BI, business processes, and structured fact-based decision making—the latter aimed at measuring, managing, and improving the effectiveness of key strategic and tactical decisions that impact profits.
Historically, this type of decision making has been predominantly an ad hoc, idiosyncratic process in many business contexts. That said, there are readily defined business processes for making decisions for recurring, well-structured business problems, that is, problems for which there is a clear consensus on objectives, alternatives, and impacts (Marakas, 1999). For example, pricing decisions in asset-intensive businesses such as commercial aviation and lodging are made dynamically by revenue optimization systems. More broadly, a decision process is simply a specific type of business process and thus is amenable to process specification, standardization, and improvement via business processes re-engineering techniques. In effect, companies can leverage BI and existing technologies and methods to
Effectively, by blending BI with “decision process engineering,” we can reengineer aspects of knowledge work that can have a substantial profit impact. We can think of this endeavor as expanding the number of business situations within which structured, fact-based decision making can be brought to bear. Technically, decision process engineering employs BI, business process modeling, business rules, and workflow software.
Although many industries have in place highly defined day-to-day operations that are under process control and build in worker accountability, this same standard is not used for management decision making. Too often acquiring business information and analyzing it to improve the effectiveness of business decisions is still an idiosyncratic, ad hoc process. We believe that for every leader in the use of BI there are dozens who have fallen behind or who are stuck in the earlier stages of BI maturity (see Chapter 5). Based on the magnitude of business value that successful BI investments have created, we believe these companies are leaving tens of millions of dollars in profits on the table. That said, evidence suggests that companies are capitalizing on BI, business process engineering, and workflow to automate routine operational decisions, and thus we believe this concept will be extended to a much broader set of decision processes over the next decade. For example
The above examples show the degree of structured, fact-based decision making that is possible for well-structured operational business processes. By use of the same concepts and technologies, companies can re-engineer decision processes that occur within the context of management processes, revenue-generating processes, and operating processes. An overview of some of the possibilities is provided in Table 9-1, which builds on the examples of BI applications described in Chapter 7.
Table 9-1 is designed to illustrate the concept of decision process engineering and, hopefully, spark your thinking about how the concept can be applied at your company. As a general proposition, the state of the art in business process management (BPM) is advancing to the point at which recurring multi-step business processes such as order processing, claims processing, campaign management, inventory management, materials management, and many other knowledge work processes are being standardized via the use of flexible, configurable BPM applications. BPM applications allow companies to specify reusable process patterns to improve the quality and efficiency of recurring processes (Smith, 2003). Our view is that the same technologies and methods will be applied to fact-based decision making, leveraging BI in the context of business processes that impact profits.
Table 9-1
Opportunities for decision process re-engineering
9.3 Re-engineering Knowledge Work: Releasing the Power of Business Intelligence
The Peter Drucker quote at the start of this chapter communicates his position that the “most important contribution management needs to make in the 21st century is … to increase the productivity of knowledge work and the knowledge worker.” Our view is that BI know-how is the core competency needed for this crucial management task. BI marries business information, business analysis, and fact-based structured decision making, all of which have the potential to dramatically improve knowledge worker productivity. More broadly, BI provides a systematic way to do knowledge work, and to quote Drucker (1999) again, “productivity of the knowledge worker will almost always require the work itself be restructured and be made part of a system.”
Building on these thoughts for our view over the horizon, and consistent with the leadership and general management challenges we described in Chapter 5, we can predict that improving knowledge worker productivity will require companies to
In effect, management will be pushed by economic circumstances to re-engineer its own work—to do to its own work what it has done to manual work over the past 100 years. Needless to say, this will be a daunting task, and it will demand BI competencies that are not widely distributed among top executives and managers today. To understand the magnitude of the challenge, let us examine some of the tasks that are involved.
9.3.1 Creating a Vision of How Knowledge Work that Impacts Profits Should Be Performed
In factory settings or large-scale service operations, industrial engineers and business process analysts can directly observe business processes, apply automation where appropriate, create specialized jobs and tasks, train individual workers, measure process performance, and continuously improve results. We have a century-long tradition of doing so, the latest manifestations of which are off-shoring and outsourcing. There is no such tradition when it comes to knowledge worker productivity, in which the tasks are less defined, the desired outcomes are less specific, and the optimal means of getting the work done is more a matter of art than science. Recent developments in the field of BPM are starting to change this state of practice, but key management processes, revenue-generating processes, and operating processes that are the core processes of knowledge work remain largely ad hoc and idiosyncratic in many companies. To re-engineer knowledge work and knowledge worker productivity, companies will need to develop a vision of how knowledge work should be done, which presupposes a good understanding of the current state and an informed sense of the possible and desirable future state.
9.3.2 Making Specific Decisions About Management and Analytical Frameworks for Core Business Processes That Impact Profits
Advances in management thinking and technological capabilities drive innovation in management processes, revenue-generating processes, and operating processes. These innovations have an adoption cycle and a useful life, and they are typically marketed to businesses by consulting firms and software vendors. To re-engineer knowledge work and knowledge worker productivity, companies must understand what the actual state of the art is for a given core business process, whether so-called “best practices” are really best practices or only common practices, whether adopting prepackaged “best practices” will actually advance their cause, and whether they would be better served to continuously improve their own practices. Volumes of information about just about any aspect of business are available, and thus, company managements must sift through the information and make choices about how they want their knowledge workers to think about and analyze business information. For example, would the company be well served to adopt a balanced scorecard approach as a key management framework, or would some other management control system approach work better?
9.3.3 Determining What Business Information Is Needed to Apply the Selected Frameworks
The BI opportunity analysis technique we described in Chapter 2 ensures alignment between drivers, business strategies, and core business processes, as well as the business information and business analyses needed to support fact-based decisions in the context of those core business processes. There is an implicit assumption that a given company has mature management and analytical frameworks with which to align BI in the form of business information and analytical applications. To the extent that this assumption holds, the task of determining business information needs is straightforward. On the other hand, the task of re-engineering knowledge work by unleashing the power of BI may require changes to existing management and analytical frameworks. In either case, the business information required for re-engineering knowledge work is a function of the management and analytical frameworks used or to be used by a given company.
9.3.4 Determining How Key Decisions Should Be Made and by Whom
Picking up again on the concept of decision process engineering, the technologies and methods exist to re-engineer the decision-making processes that are a key component of knowledge work. This brings us into the realm of organizational design and decision support systems. Essentially, organizations are designed to meet the needs of their customers and in accordance with structural archetypes, which results in specified spans of control and accountability for organizational units (Simons, 2005). Along with control and accountability come delegated decision rights, which can be implemented in a variety of ways. Some companies have taken a very structured approach to decision rights. For example, Duke Power created a formal decision rights matrix, which describes the role of each manager for various key decisions, specifies the decision maker and who must be consulted before the decision is made, and specifies who receives what information after the decision is made (Hammer et al., 1999). At the other end of the spectrum are companies with decision processes that are less transparent. In general, the possibilities exist for decision-making processes that vary in terms of formality, the number of persons involved, the manner in which those involved participate, the subject matter, and the type of BI (decision support) used to inform decisions. From a BI perspective, the key is to design BI that meets the needs of different decision styles (Marakas, 1999). Once that has been done, the decision process can be engineered such that it enhances knowledge worker productivity and contributes to more effective decisions, that is, decisions that have a positive profit impact.
9.3.5 Infusing Accountability and Process Metrics into Business Processes and Decision Processes
By restructuring knowledge work to leverage BI, we can make such work part of a system, as suggested by Drucker. Specifically, we can leverage BPM technologies, coupled with BI, to create systematic approaches to core management, revenue generation, and operating processes. This in turn will allow greater transparency into key elements of business process and decision process performance. For example, if we know that a business process is supposed to follow steps 1 through 8, we can use BPM software to ascertain that those steps were in fact followed, determine how long each step took, identify who performed the various steps, and measure other aspects of process performance. Just as we can improve manual work by automation and process improvement techniques, we can re-engineer knowledge work in the same way.
9.3.6 Investing in Business Intelligence and Business Process Management Competencies, Methods, and Tools
Much of re-engineering knowledge work can be built around BI. Simply, just making the right business information and analytical tools available to knowledge workers will go a long way toward improved productivity and profits. Today, companies who are at the earlier stage of BI maturity struggle to bring information to bear in support of key business decisions. As they mature in their use of BI, these companies will have the opportunity to take the next step of re-engineering knowledge work by leveraging BPM technologies and methods. To gain the full benefits of increased knowledge worker productivity, companies will need to invest in BI and BPM competencies, methods, and tools.
As noted previously, Wal-Mart is one of the most outstanding examples of how investing in BI can increase the power and productivity of knowledge work. From its headquarters in Bentonville, Arkansas, Wal-Mart uses BI to manage a world-wide supply chain that includes thousands of vendors and millions of products. A nonstop convoy of trucks brings products from all over the world to Wal-Mart’s 1.2 million-square-foot distribution center, where real-time BI systems track each product and send it on its way to the shelves of Wal-Mart stores. Inventory management BI systems tell Wal-Mart which stores need which products, when, and in what quantity (Friedman, 2005).
Wal-Mart has not only invested in BI but has also aligned BI with its strategic goals, has aligned its business processes to use the information BI makes available, and has even helped its suppliers align their systems and processes with those of Wal-Mart.
None of that would have been possible without both investing in BI and using it with common sense and business acumen.
9.3.7 Managing the Changes Required to Redirect Knowledge Work from an Artisan Model to a Systems Model
Unlike with manual workers, where the company owns the means of production, knowledge workers own most of the means of doing their work, that is, the education, knowledge, and expertise they have accumulated over some number of years. Accordingly, we believe that they must be enlisted in any effort to re-engineer their work. In addition to possessing the knowledge of how the work is done, knowledge workers value the opportunity to exercise their analytical and problem solving skills. As we re-engineer knowledge work, the case needs to be made that the resulting knowledge work system will not replace individual creativity but rather will augment creativity and individual initiative by providing business information and analytical applications that allow knowledge workers to consider more scenarios, evaluate more options, analyze more specific information, and apply more sophisticated tools. In effect, the combination of BI and business performance management can afford knowledge workers relief from the drudgework of basic data accumulation and manipulation and instead offer opportunities to have a far greater impact on company profitability. To reach this point, companies will have to manage the change from the artisan model to a systems model.
Although the challenges of re-engineering knowledge work—as described above—may be daunting to some, we believe the rewards will be substantial for those who take up the challenge. By making knowledge work more systematic, companies can ensure that the linkage between strategy, process, information, process, and action is explicit. Coupled with BI about results, the ability to determine the effectiveness of core business processes and decision processes will enable managements to ensure that successful processes and practices are consistently and correctly leveraged to increase profits.
9.4 Closing The Loop: Optimizing and Integrating Strategic, Tactical, and Operational Business Performance
As discussed above, BI provides great potential to improve on knowledge worker performance through optimizing both the information available to knowledge workers and the way in which that information is used by knowledge workers to improve profits. Once optimal decisions and actions are taken by the knowledge worker to optimize business performance, those decisions must be followed through operationally to close the loop and achieve the potential that exists for performance improvement. Going back to the Whirlpool case study, assuming that the managers that are charged with selecting suppliers based on price/quality considerations determine how suppliers will be selected and relay this decision to the purchasing department, the workers charged with ordering supplies have to actually place the orders as stipulated to ensure that the benefit is achieved. Similarly, if a company employs a customer segmentation strategy that identifies high-valued customers and determines that these customers have their fees waived, this action must be taken at the operational level when a highly valued customer order is placed. By optimizing strategic and tactical decisions and actions and ensuring that these decisions are operationalized, businesses can then measure the effect of the decisions and actions that were enabled by BI. They can also hold all employees, including knowledge workers, accountable for the decisions and actions that result in business performance.
In addition to aligning, optimizing, and measuring business performance at the strategic, tactical, and operational levels, we believe that there will be a technical alignment and optimization of the systems that are used to support this new business environment. Business users will no longer have to distinguish between business actions and systems and take conscious efforts to logon to BI applications. Rather, technology will improve such that business users can seamlessly do their work, moving between analytical and operational activities with ease.
9.5 Barriers to Realizing the Benefits of Business Intelligence
At the start of this chapter, we asked: what can we and should we expect management to do with BI over the next decade? In our view, we can and should expect management to actively and persistently drive the use of BI to improve profits and business performance. We believe this should take the form of decision process engineering and re-engineering knowledge work. The technologies, business process engineering competencies, and change management techniques are in place, and we see no technical reason why BI cannot be raised to the level where it is integral to how companies do business. That being said, we believe there are identifiable barriers to getting there, not least of which is lack of recognition of the profit and performance impacts of BI. We have attempted to overcome that specific barrier by sharing the information presented in this book. Beyond that, we see five other key barriers, which we will discuss below.
9.5.1 Noise and Confusion in the Business Tools Environment
Executives and managers are bombarded with claims about the merits of various approaches to improving business performance and profits. Strategic Planning, benchmarking, pay-for-performance, outsourcing, customer segmentation, reengineering, Balanced Scorecard, and total quality management are but a few of the approaches, and there are a host of others that fall into the realm of IT. For example, enterprise requirements planning (ERP), customer relationship management (CRM), and supply chain management (SCM) are three prominent types of enterprise applications that have been sold to businesses over the past decade. All of these approaches are sold by consultants, academics, and software vendors as ways to improve profits and performance, and the results have been mixed. Because of the well-publicized successes and failures and because of the advertising muscle of large software vendors and consulting firms, there is noise and confusion in the business tools environment, and that works against more aggressive adoption of BI and against taking it to the higher level represented by decision process engineering and re-engineering knowledge work.
9.5.2 Skepticism about Information Technology Value Propositions
Simply put, executives and managers are skeptical about IT value propositions, and rightly so. Although major investments in enterprise applications have paid off in some cases, plenty of documented cases indicate where the investments haven’t, as well as a few cases in which the applications actually caused major financial and customer relations damage to the companies who made the investments. We believe that the norm is that the investments result in advantages for early movers, parity for later adopters, and massive value transfer from the purchasing companies to the software vendors and consulting companies. As an example, we worked with one company that invested $100 million over the course of a few years to install a well-known ERP system. The major consulting firm that sold the system projected operating margin improvements that would more than cover the investment, whereas a study of the company’s Securities and Exchange Commission (SEC) filing shows that the margin improvements have not come anywhere close to paying back the investment. We hear similar stories about CRM and SCM systems, and there are enough published stories to create healthy skepticism in the marketplace. Furthermore, because major consulting companies in effect act as salespersons for enterprise software vendors, executives and managers find it hard to turn to these same consultants for independent, objective advice when it comes to IT, which exacerbates their skepticism about IT value propositions. In this environment, BI is tarred with the same brush.
9.5.3 Executive and Management Challenges Relative to Information Technology
With pervasive cost competition in the global economy and the attendant downsizing, surviving executives and managers are left with significant bandwidth challenges across the board, which often translates into not having the time to really understand IT, its value propositions, and its organizational implications. Compounding this challenge is the fact that many executives and managers are not IT savvy, and so they shy away from the jargon-laden meetings that make them feel uncomfortable. Some of this may be generational, but even today, many top business schools do not emphasize management of IT or essentially ignore the subject. And yet, IT capital spending is a huge proportion of overall business investment. This all manifests itself in the BI arena as a lack of executive and management engagement in BI strategy and the associated organizational changes, and yet it is only these business people who can drive the process changes needed to capture the business value of BI.
9.5.4 Competition for Business and Information Technology Resources
In today’s lean business environments, daily and weekly operational requirements typically consume much of the bandwidth of executives, managers, and other knowledge workers. In effect, companies are so busy taking care of today’s customers that they have limited time to help evolve the company toward a better way of doing business. This bandwidth issue constrains organizational capacity for improvement. When coupled with actual capital spending constraints and alternative potential investments, this results in internal competition for the business and IT resources needed to make any given initiative successful. One result that we’ve seen is that companies make a number of small, incremental investments rather than making more substantial investments in a few key initiatives. What this means for BI is that the initiative proceeds more slowly and takes longer to deliver business value, which sometimes results in further skepticism about the business value of BI.
9.5.5 Risk Aversion
The saying used to be that nobody ever got fired for buying IBM. That was business shorthand for saying that sticking to the tried-and-true, accepted ways of doing things is the safest for executives and managers. That fact of business life manifests itself every day in companies around the world. Whether it is a dominant consumer products company or a high-tech manufacturer, companies that regularly compete and innovate in their core products or services become followers when it comes to business tools and IT investments, waiting until they see that others in their industry or value chain have adopted a tool before following along. That said, it has been proven in a range of industries that IT innovation can lead to competitive advantage and superior profits. With innovation, however, comes risk, and thus executives and managers play it conservatively when it comes to IT. Realizing the full profit and performance potential of BI entails risk-taking, and many executives and managers are not prepared to place bets in an area within which they are uncomfortable.
Although there are a host of more tactical, BI specific barriers to realizing the full potential of BI over the next decade, we believe the five barriers discussed above combine to create the most strategic barrier—the reluctance or unwillingness of executives and managers to really go full tilt in the BI arena. This is unfortunate, because there are documented cases in which BI has delivered tens of millions of dollars of incremental profits for those companies who are bold enough to innovate with BI.
9.6 Summary
BI tools and methods have reached a state of maturity where the opportunities for companies to leverage BI are readily grasped. The innovators are already well down the road, and the followers are moving forward to try to catch up. Looking ahead, we believe BI holds the key to meeting the 21st-century management challenges articulated by Drucker, the challenges of leveraging information and improving knowledge worker productivity. Once the strategic and tactical decisions that knowledge workers are charged with are optimized and implemented, this will add to the productivity improvements that business has achieved through operational performance improvements, bringing business performance to new heights in line with Drucker’s vision. Although significant barriers exist to achieving this vision, we believe that they can be overcome. These are challenges of enormous economic import, and we would be thrilled to see companies win in the marketplace by being daring and innovative in leveraging BI.