Introduction
Integrating Enterprise and Human Capital Analytics

“The vast majority of strategic initiatives never succeed.”

“Organizations fail not because they have the wrong strategy but because they do not execute the strategy properly.”

Statements like these have been repeated so often they have become conventional wisdom. An entire industry of management consultants exists to help companies define the right strategy so that they won’t fail. Yet failure, or at least muddling through, is still much, much more common than outright success (Worley, Williams, and Lawler, 2014).

This book is about how to use analysis to improve both strategy execution and organizational effectiveness, including the investment decisions made through the annual budgeting process. The book does not provide one-size-fits-all solutions like strategy maps, balanced scorecards, the “right” leadership behaviors, communication strategies, or any of the numerous other solutions that are supposed to fix what ails all organizations.

The focus here is on analysis. If you want a deeper understanding of why the execution of your strategy falls short because of issues with the structure and processes of your organization, then this is the book for you. Through analysis you can determine where execution works well and where it does not. With that information you can evaluate the solutions, determine which one(s) to implement, and channel incremental budget dollars where they will best support the strategy. If you are looking for a quick-fix solution, look somewhere else.

The book addresses a large gap that exists today in how organizations conduct analytics. On the one hand, we have at our fingertips access to the most powerful computers, the largest databases on organizational processes, and ever-expanding information on consumer behavior and the way commerce is conducted worldwide. On the other hand, organizations struggle as much as ever to achieve strategic objectives and improve organizational effectiveness. We need something different.

 

The power and danger of simplification. Organizations are complex places. There are tons of moving parts that have to be aligned and work well together to produce the products and services for the customers. Cognitively, people have a hard time focusing on too many things at once. We make their job objectives as simple as possible so they can focus their energy productively. If we didn’t do this, people easily could get lost figuring out what they should be doing.

A primary vehicle for reduced complexity is standard business processes—specifying how to do the work so we don’t reinvent the wheel. Standard processes promote efficiency. Once you have a process, you optimize it to lower costs and raise profit margins.

Business and HR leaders focus a lot of time and energy on maintaining processes so that customers efficiently get their products and services every day (“keeping the lights on”). Financial controls ensure that budgets are not overrun, and process controls ensure efficiency of operations. Human capital policies and procedures ensure that talent is available when and where the business needs it and that employees are motivated to do the work.

Unfortunately, simplification and standard processes are not enough. You have to recognize and manage the organizational complexity for successful strategy execution. There are always multiple strategic and operational objectives that are in conflict with each other. Increase market share, but don’t spend too much money doing it. Innovate, but make sure the prices are affordable for the customer. Provide high quality customer service, but don’t spend too much time on each customer. Minimize warehouse inventory, but don’t create shortages for the customers. Attract new customers, but don’t cut prices too much. And so on.

The challenge for frontline and middle managers is how to deal with the competing strategic and operational objectives. If you follow one process too zealously, you take time and energy away from other operational and strategic goals.

Consider the following exchange between Michelle, Operations VP, and Trent, her HR business partner.

Trent: “Michelle, your team really needs to follow the performance management process. We’re seeing lots of gaps in compliance, and the HR leadership team is giving me a hard time. And next week don’t forget about our quarterly review of your direct reports’ career plans and the succession plans for key roles.”

Michelle: “I keep telling them to get the reviews done. But we’re just so crazy busy with all the business priorities. Unless the company makes more money, all this HR stuff is going to be irrelevant. We’ll have to start cutting headcount.”

Exchanges like this occur every day worldwide in companies in all industries. The specific business and HR priorities vary, but the essence of the problem is the same: they are not aligned. Business leaders focus on strategy execution and don’t pay enough attention to organizational effectiveness, while HR leaders do the opposite. The consequence: bottom line results suffer.

The key to strategic success is striking the right balance between competing priorities. Doing Strategic Analytics helps you determine that balance.

 

The problem with doing only business analytics or only HR analytics. A thousand things can be improved in existing programs and processes, but only a handful are truly strategic. Using business analytics to focus on refining existing processes misses the larger picture of weaknesses created by the work design, the annual operating plan, and the budgeting process. Human capital analytics that focus on improving HR programs face huge challenges of knowing where to start.

Table 1 summarizes the strengths and weaknesses of the enterprise and human capital approaches to analytics and decision making. People like Michelle, who use only the enterprise analytics approach, often mistakenly assume that people will behave a particular way just because they are told to. However, people are not robots to be programmed or widgets that can be effortlessly moved from one task to another. The complementary human capital approach is needed to shed light on what drives behavior for individuals. The solutions are almost always more nuanced and complex than senior leaders want to believe.

People like Trent, who use only human capital analytics, frequently have the mistaken belief that showing a financial impact is the same as improving strategic capability. Saving money by being more efficient with current HR processes says nothing about whether they are the right ones for strategic success. The complementary enterprise approach is needed to ensure alignment with strategic objectives.

 

Strategic impact or ROI? The fact that HR is challenged to justify the return on investment (ROI) of its programs is just one part of a larger problem with the way ROI is used in organizations. ROI focuses on cash flow. The only benefits that can be included in ROI have to be expressed in monetary terms.

The organizational capabilities that create competitive advantage ultimately increase cash flow. But their effect is not always direct or immediate. Building the capability to deliver on strategic goals, such as better customer service, quality, innovation, and others, can have very strong impacts on business success, which is why they are part of the strategy. However, the immediate effect on ROI is usually negative: you spend money to invest in the capabilities, with no guarantee of financial payback.

For example, Facebook for years focused on building an enormous user base even though it hadn’t figured out how to monetize that base. Their strategy was very clear: they knew exactly what organization capabilities they needed to execute the strategy, and they invested very heavily in those capabilities. Ultimately there was a huge financial payoff after they deployed advertising. However, when Facebook initially built their user base support capabilities, there was no way to either calculate or forecast ROI in a meaningful way.

Facebook is an extreme example that nonetheless proves the point. Building organization capability to execute the strategy is not equivalent to showing increased financial ROI in the short term; they can be in opposition to each other, at least in the initial stages of capability building. Strategic Analytics focuses on what it takes to build that capability, not ROI.

 

Get your strategic priorities straight. Strategic priorities can have conflicting impacts on profitability: there is tension between the strategic priority and the need to keep costs down to make money. For many consumer products companies, the priority is low finished product cost and high quality. For technology and pharmaceutical companies, it’s cutting-edge innovation that doesn’t cost too much to create. For many consumer and financial services firms, it’s cost-effective customer service. Safety is a primary concern in manufacturing, mining, and construction—but you can overspend on safety to the point where you see few to no additional safety gains while margins erode. And so on.

The tension often gets translated into “do more with less.” Problems in strategy execution arise when the benchmarks that senior leaders use to set productivity and quality targets cannot be attained within the allocated budgets. In most organizations, that’s close to a daily occurrence. Figuring out why productivity or quality is falling short, or why costs are exceeding budgets, takes up inordinate amounts of time for middle and frontline managers. They rarely arrive at the best diagnoses and solutions because they don’t know how to incorporate what’s going on with the people.

The answer is an integrated approach that looks at the entire system—the business and HR processes, the strategic and human capital objectives, the way work is organized and carried out, all of it—to determine the root causes of the problems. For example, boosting productivity and quality typically happens one of two ways: through substituting technology for people or redesigning the work (or both). Work redesign that boosts productivity and quality usually is most successful when done using high-performance work design principles (chapters 5, 6, and 10). Successfully designing, implementing and managing a system like that requires looking at business and people processes together.

 

Strategic Analytics one step at a time. Before you decide I’m asking you to do the analytics equivalent of climbing Mount Everest, please know the following: you don’t have to climb the highest mountain to get better insights into virtually all the strategic and performance issues facing your organization. The Strategic Analytics framework provides a practical, step-by-step guide to deeper and more actionable insights than the analytics currently practiced in most corners of your organization. Just by defining the problem and identifying the most likely causes—building the causal model—you will be in a position to make better decisions, even if you don’t have enough time and resources for high-powered statistical analysis. In fact, in most cases there often is no justification for rocket scientist level statistics. Qualitative analysis alone, using stakeholder interviews, often is the only thing you need to get actionable insights.

This book shows how to use Strategic Analytics to get better alignment between the business and HR. You will find specific details on the different parts of both enterprise and human capital analytics that have to be conducted for successful integration. Guidance on the specific questions to ask is included, along with examples of how to do the analytics. Strategic Analytics is a team sport. You can’t get to the deepest insights without both the business and HR perspectives on the team doing the analysis together.

 

It’s all about the system. Strategic Analytics is a type of systems analysis: you look at the entire system to determine what’s driving behavior. When you understand the link to the larger system, you can properly diagnose the root causes of behavior and motivation. It’s also the surest way to find changes to solve the problems instead of temporary solutions that only paper over the root causes.

A key to Strategic Analytics is doing the analytics in the right order. Both business and HR leaders tell the story of how organizational performance occurs by starting with people’s contributions (human capital performance). Their contributions combine with others to create business processes (enterprise performance), and this combination in turn leads to strategy execution. If strategy isn’t executed properly, we look for the things specific people and roles could do differently. This chain of events is shown in figure 1: the causation runs from human capital to enterprise performance and ultimately to strategy execution.

The challenge is figuring out what to focus on. There are so many things that can be improved at the job level, including screening, training, promotions, performance management, coaching, integrating jobs with each other, goal setting, and so on. It’s easy to tell a story where improving on any of those dimensions could help improve human capital performance and thus enterprise performance and strategy execution. The challenge is identifying which ones matter most. For that, you have to order the analysis the other way around.

A complete Strategic Analytics diagnostic follows the sequence outlined in figure 2. There are three steps:

• Step 1—Competitive Advantage Analytics: The process starts with the strategy. What creates your competitive advantage—how do you make money and preserve your position in the marketplace? In the first step you (a) identify the organizational strengths and weaknesses that define competitive advantage, (b) build a causal model that lays out the details, and (c) get alignment with key stakeholders on the need for analysis. A key part of this step is figuring out where people get too wrapped up in focusing on specific business processes and lose sight of the strategic objectives.

• Step 2—Enterprise Analytics: For the second step you test the causal model at the appropriate level of enterprise analysis: at the organization-wide level, at the business unit level, or at the business process level. At this step the analytics use metrics and stakeholder interviews to understand where the organization is falling short on meeting its strategic objectives. High-powered statistics are rarely, if ever, needed here.

• Step 3—Human Capital Analytics: The third step augments the enterprise analysis with human capital analysis as needed, doing diagnostics at the role, individual, or HR process levels. The analytics at this step can include advanced statistics if the data are available and that type of analysis is relevant. More than half the battle in getting to actionable insights is defining the right questions and making sure you don’t focus on the wrong data, not applying advanced statistics.

Step 1 is the most straightforward and most important—and it’s precisely what people fail to do all the time. If you jump straight into either enterprise or human capital analysis, you can easily miss the critical link that ties business and people issues together. You need step 1 to tell the difference between insights that offer only marginal improvements in operations and the ones that truly advance strategy.

For those of you who like to think mostly in terms of what goes on with individual workers, Strategic Analytics boils down to the following. Do the people who are responsible for delivering the organization’s products and services have the responsibility, skills, motivation, coordination, and support to keep the system going and simultaneously advance the strategy? If the answer is yes, then the system is designed properly. If no, then Strategic Analytics identifies what needs to change.

 

Do as much as you can, and you still will benefit. The Strategic Analytics approach does not have to be onerous, just comprehensive. Depending on the issue you’re investigating and the time and resources available, you can easily adapt the framework and achieve deeper insights than you’d get otherwise. The benefit of the approach is better informed decision making, even if you don’t have permission to make changes to address structural issues.

The first main benefit of Strategic Analytics is avoiding solutions that won’t work due to factors beyond your control. For example, suppose the strategy execution problem is low productivity in a role. You are asked to improve the employees’ morale and engagement under the assumption that productivity will also improve. Suppose further that you are told to focus on solutions that don’t involve increasing pay. Faced with those restrictions, most people in organizations would exclude compensation from the analysis. After all, if you can’t increase pay, why focus on it as a potential cause? The answer is that pay may matter a lot. If it does, then leaving it unchanged could keep you from achieving the productivity goals.

Strategic Analytics casts a broad net, taking into account all potential factors, which in this case includes compensation. Suppose the diagnostic reveals that low compensation creates problems in attracting and retaining high-quality talent. There may be some small changes you could make to marginally improve employee morale and engagement. But without a compensation increase, a large competency gap will exist, because you’re not paying enough to attract and retain the right people. Doing Strategic Analytics gives you the information you need to tell senior leaders that focusing on morale and engagement alone almost certainly won’t achieve the desired productivity improvement.

For another example, consider the case study from chapter 7 on evaluating the business impact of executive coaching. Most executive coaching engagements tend to focus on leadership behaviors that may help the leader to communicate and manage the team better, but they offer no guarantee of improved strategy execution. Doing the Strategic Analytics diagnostic on executive coaching can reveal which leadership competencies are more likely to improve execution.

The second benefit comes from setting the organization up for deeper analytics and insights later on. Given the short amount of time allowed (“get it done yesterday”), there are limits on how long you can take to do the analysis. Building the causal model and doing some initial analysis may be all that you can finish within the time constraints. After meeting the immediate deadline for recommendations, you can do a deeper analysis into the complete set of factors you identified as potential contributors. I have used this approach many times in my work with companies. I provide preliminary conclusions based on a partial analysis to satisfy an immediate demand for decision making. I then conduct the more in-depth analysis over a longer period and have the results ready when new urgent deadlines related to the organizational issues crop up.

One note about terminology: I use both “business analytics” and “enterprise analytics” to refer to the same thing: analysis focused on the organization, business unit, or work group (region, site, team, etc.) levels. “HR analytics” and “human capital analytics” also are used interchangeably to refer to analytics at the role or individual levels.

 

The limits of Strategic Analytics. A Strategic Analytics diagnostic addresses strategy execution challenges that arise from internal factors. The factors that are covered include the organization design, culture, allocation of decision rights, matrix structures, cross-functional collaboration, (high-performance) job design, individual competencies, motivation, and more. Because these are internal factors, in principle they can be changed and controlled. I do not claim that changing any of these factors is easy, only that it is feasible.

What Strategic Analytics does not address is the role of external factors in strategy failure, nor problems with the strategy itself. Many strategies fail not because of flaws in the organization but because the strategy itself is ill conceived. Any strategy that requires deviating from the organization’s established capabilities and market strengths carries a risk of failure because of competitive pressures beyond the leadership’s control. For example, a company that tries to enter an entirely new line of business that is very different from its core competency faces a very small chance of success. No amount of reorganization, culture change, overhaul of existing staff, or tweaking of processes will radically increase the chances of success. The best organization design can’t save a bad strategy.

 

Target audience. There are three main audiences for this book: leaders, frontline managers, and analysts.

For senior business and HR leaders, Strategic Analytics can help you better orient how your organization approaches diagnosing and solving problems with strategy execution. It can improve the approach you take, as well as the analytics others conduct under your guidance. Use the framework to push for cross-functional analysis and solutions to challenges in performance and strategy execution.

For frontline business and HR managers, Strategic Analytics can help broaden how you think about the organizational system and the behavioral drivers of strategic success. You are not likely to lead an in-depth analysis yourself, but you can challenge others to do more than just enterprise or human capital analytics. Use the framework to push back, where appropriate, when you are given predetermined solutions that are based on incomplete diagnostics.

For business and HR analysts, Strategic Analytics can be a template for doing much more comprehensive and insightful work. You are not always given permission to cast a broad net when designing your diagnostic. Strategic Analytics shows the importance of doing so for understanding all the true drivers of successful business performance and strategy execution. Use the framework to deliver actionable insights that challenge senior leadership to think, act, and budget differently than the status quo.

 

Organization of the book. The book is organized as follows. Part I addresses why Strategic Analytics is the right approach. Chapter 1 covers the importance of building and testing causal models and the dangers of incomplete data analysis. A robust causal model for diagnosing strategy execution problems is presented, tying together factors that impact business performance at both the individual and group levels.

A properly specified causal model identifies the leading factors that should improve strategy execution. When doing the analytics, those factors are recast as hypotheses: questions about strategy execution that need to be formally tested. The causal model narrows down the list of candidate factors (hypotheses) to the ones that are most likely to drive the desired results.

Chapter 2 addresses problems with using ROI to evaluate business and HR decisions. A critical issue is the tradeoff between short-term increases in cash flow versus longer-term impacts on competitive advantage. Competitive advantage ultimately leads to increased cash flow in the long run, but at the cost of short-term cash flow as investments are made. Additional common metrics besides ROI are reviewed and critiqued.

Part II details the steps of how to do Strategic Analytics.

Chapter 3 explains the order for conducting the analytics, plus a range of topics you should know before getting started, including (a) how Strategic Analytics is related to balanced scorecards, (b) the importance of interviews and qualitative analysis, and (c) who should construct the causal model. Qualitative enterprise analysis is often all that is needed to deliver actionable insights. And even if no in-depth analysis is conducted, laying out the causal model is very important. If you don’t have a lot of time, a properly constructed causal model still can help improve decision making.

Chapter 4 covers step 1 in the Strategic Analytics process: identifying the sources of competitive advantage, including the organization capability strengths and weaknesses, and focusing the enterprise and human capital analysis on those. A thousand things can be done that might help improve organizational performance and strategy execution. Focusing your attention on organizational capabilities that provide competitive advantage is most critical for successful strategy execution; doing so narrows the inquiry to a manageable set of truly causal factors to be analyzed.

Chapter 5 covers step 2 in the Strategic Analytics process: enterprise analytics, which diagnose performance barriers and enablers at the enterprise, business unit, and/or business process levels. These analytics focus on alignment and gaps in the organization design, organization capabilities, and culture. Specific questions to be addressed for each of the three components of enterprise analytics are provided.

Chapter 6 covers step 3 in the Strategic Analytics process: human capital analytics, which diagnose performance barriers and enablers at the role, individual, and/or HR process levels. These analytics focus on alignment and gaps in the areas of job design, individual competencies, and motivation and attitudes. Specific questions to be addressed for each of the three components of human capital analytics are provided.

Chapter 7 presents Strategic Analytics case studies. It provides examples of three different types of diagnostic: (a) cases where only enterprise analysis needs to be conducted rigorously (minimal human capital analysis), (b) cases where human capital analysis is the primary focus (minimal enterprise analysis), and (c) cases where both types of analysis take time and effort. The examples show how the type of diagnostic depends on the context and questions being addressed. It should not depend on the personal preferences and biases of the people leading the analysis: business leaders should not focus only on enterprise analysis because that’s what they are familiar with, or vice versa for HR professionals and human capital analysis.

Chapter 8 covers a specific application of the framework: customer retention and profitable growth. It provides a detailed example of how to apply integrated enterprise and human capital analytics for large commercial banks, technology companies, and retail sales companies.

Chapter 9 covers another specific application: go-to-market (GTM) strategies and effectiveness. Specific case studies from the package delivery and logistics industry and from consumer product direct-store-delivery (DSD) systems are discussed in detail.

Part III dives more deeply into specific topical areas of current practice. It reviews where common practice is already consistent with Strategic Analytics and where it can be improved.

Chapter 10 addresses critical roles, group performance, and competencies. How do we identify top talent and high potentials? What is the contribution of the employee versus the group versus the leader in driving behaviors and performance? How do organizations balance higher pay for high performance with the need to economize on compensation costs?

Chapter 11 covers making sense of sensing data. Many of the early warning signs of organizational issues arise from employee surveys and other data that raise questions about culture and organizational effectiveness. Specific examples are illustrated using case studies on speed of decision making and on innovativeness.

Chapter 12 addresses human capital development and retention analytics. How do you know if the capabilities being built will enable strategy execution? The chapter includes a critique of the two dominant approaches to evaluating human capital development activities: ROI analysis and the Kirkpatrick model. An alternative approach based on a causal model of performance is provided.

The last chapter concludes with a summary of key learning and action points from the book.

The appendix provides a diagnostic interview template for conducting Strategic Analytics. You can use it to design a diagnostic that is relevant for whatever issue you want to address. The questions and details for the diagnostic are drawn from the core chapters of the book.