Chapter 7
Advance
How Do We Continue to Improve?
When John McFarlane took over the ANZ bank, it was the worst performer of Australia’s big four banks, regarded as the highest-risk bank investment by the market, and in strategic disarray. It was grappling with almost A$2 billion of bad debt and a cost-to-income ratio of roughly 63 percent.1 The bank set its sights on a five-year aspiration to double its profitability and market capitalization and reduce its cost-to-income ratio to below 50 percent. To achieve this performance aspiration, health improvements were needed in relation to people development, openness and trust, risk management, and customer focus. In the Assess stage, it became clear that a raft of skills needed to be built in risk, technology, sales, marketing, HR, and so on. Mindset shifts would be required, too. For example, from “risk is the risk function’s job” to “risk is everyone’s job”; “it’s respectful not to disagree in public” to “we have an obligation to dissent in meetings”; and “process is a necessary burden on customer service” to “process is a tool to help us responsibly serve our customers,” and so on. The core architecture of the change program was a portfolio of initiatives organized around three themes: perform, grow, and breakout. In the “perform” theme, topics were tackled such as overhead cost reduction, collections management, and lean service operations. Examples in the “grow” theme were, among others, initiatives directed at customer service, sales force effectiveness, and international portfolio restructuring. The “breakout” theme included a number of initiatives related to employees such as creating an internal job market, developing a new leadership model and 360-degree review process, and creating and implementing a new diversity strategy. Each of the initiatives was hardwired to influence the desired mindset and behavior shifts, sequenced, and resourced with rigor. The plans were then implemented in the Act stage, during which a change management office (CMO) played an integration role across all of the various efforts, including providing a monthly “Perform, Grow, and Breakout” scorecard and adjusting the program over time based on the results being delivered. A robust, two-way communications program was also put in place. A unique feature of the program was the implementation of the “stupid rule button” that enabled employees to quickly eliminate standards, processes, and protocols that didn’t make sense. Influence leaders were identified and mobilized, and in total over 6,000 leaders went through Personal Insight Workshops (PIWs). In the words of the leader of the program, “We realized the program had to be an ‘inside/out’ journey. In other words, it’s the individual who transforms, and in turn, the organization.”2 Just under four years after ANZ’s large-scale change program had begun, the turnaround was declared complete. More than a year ahead of schedule, its goals had been met. But the story doesn’t end there. In the Advance stage, ANZ ushered in an era of continuous improvement. For instance, while the central change management office infrastructure wound down, a group of 180 breakout champions continued in roles designed to foster continuous improvement on top of doing their normal “day jobs.” To facilitate best practice identification and sharing, performance results from 21 specialist business units were shared broadly on an ongoing basis via an online “executive desktop.” Investments were also made in a customer management system that enabled cross-functional teams to regularly convene, reflect on, and improve the end-to-end customer experience. The internal job market was enhanced to ensure the most value-creating roles were known and the best talent was placed in those roles. During the six years of McFarlane’s CEO tenure after the change program that turned around the company was complete, ANZ steadily continued its upward trajectory. Profit after tax grew at a cumulative average growth rate of 15 percent, market capitalization doubled again, and customer satisfaction soared from 65 percent to 78 percent. Further, the bank was receiving over 10,000 applications annually for its 250 graduate leadership program positions, indicative of how its continued health and high performance made it a talent magnet. At the end of McFarlane’s 10-year tenure as CEO, the bank that had been called the “lame duck” by the Australian press a decade earlier was now referred to as “a highly polished money-making machine.”3 ■ ■ ■ Not all companies fare as well as ANZ in their post large-scale change program era. We recall talking to the executives of a North American engineering business when they were in celebration mode. They had taken their company from being characterized by stalled momentum and restive shareholders to one that had increased EBITDA by more than $100 million, and its cash flow by $150 million—all in 18 months! A few years later, however, the company was filing for bankruptcy. Once the intensity of the change program was over, slowly but surely the company slipped back to old ways, siloed thinking again prevailed, and a hierarchical and political culture flourished and slowed the gears of good decision-making to a halt. Unfortunately, this engineering company isn’t alone in their experience. As we described in Chapter 1, where we introduced the “big idea” of performance and health, there are plenty of companies who hit the financial targets of their change programs only to find that a year or two later, results have slipped and they are in need of yet another major change. Back to our caterpillar to butterfly analogy, real transformation eluded them. It’s not hard to see how this could happen at the end of a program. The CMO role winds down such that the previous cadence of weekly scrutinizing initiative progress gives way to the old monthly budget reporting and quarterly review process. Resources become more hardened into roles with an annual talent assessment being the only clearinghouse for rotations. Performance transparency diminishes into PowerPoint presentation-led dog and pony shows. New ideas don’t have anywhere to go to get funding and people behind them. And so on. When asked what they wish they had done differently, a full 39 percent of change leaders reflect that they should have spent more time thinking about how to make the transition to continuous improvement a success.4 The good news is that if you’ve followed the Five Frames process up to this point, you’ve already done the vast majority of the work required to avoid this fate. Not only will you have achieved your performance aspirations, but new skillsets will have been built, limiting mindsets will have been irrevocably shifted, leadership capacity will be increased, and overall health will have improved greatly—the organization is now run in a way that makes it easier than ever to align itself, execute without friction in the system, and renew itself as needed to shape and adapt to its environment. To ensure that the performance and health trajectory continues to improve after the formal change effort is wound down, however, change leaders are well advised to put a few final pieces of the puzzle in place by establishing a continuous learning infrastructure and ensuring the right leaders are placed in the roles that are most critical to value creation going forward. Making the transition from the intensive work and constant upheaval of a transformation to a period of continuous improvement requires transitioning from a programmatic approach to change to one that, as ANZ’s John McFarlane puts it, “unleash[es] the potential of some very talented people by giving them a lot of freedom to take their businesses where they’ve got to go.”5 This doesn’t mean simply stepping back and letting leaders do as they please, however. Just as freedom in a society requires a legal infrastructure, so the kind of freedom in organizations McFarlane describes requires a learning infrastructure. Change leaders are wise not to leave this to chance, even if pushed by line leaders to leave everything to them. To borrow a phrase from the father of modern continuous improvement processes, W. Edwards Deming, “A bad system will beat a good person every time.” So what does a good system look like? One that embeds knowledge sharing, institutionalizes improvement processes, and facilitates continuous learning. Systems for sharing knowledge and best practices ensure that relevant improvements in one area are quickly adopted across the organization. Microsoft employees are familiar with the phrase that sums up the power of getting such systems: “Knowledge shared is knowledge squared.”6 In Germany, Volkswagen has created its own Lean Center, a model factory designed to spread best practices in manufacturing efficiency, ergonomics, and quality, and educate employees about lean, clean process flows that can be applied to all nine brands in the carmaker’s group. P&G operates a web-based knowledge repository, stages regular reviews to share best practices between brand managers, and constantly updates its international training programs to reflect best practices. In industries characterized by partnerships with customers and suppliers, approaches like these are often extended beyond the company to allow knowledge to be shared and leveraged from one end of a process or relationship to the other. Although the approaches used for knowledge sharing vary widely, the research is clear that the systematic sharing of knowledge and best practices matters: change programs that put them in place are 4.2 times more likely to be considered a sustainable success.7
Processes and expertise to enable continuous improvement allow employees at any level to change things for the better. Toyota’s manufacturing environment is a great place to see this at work. If employees spot a problem on the production floor, they are expected to sort it out there and then: stop the line, get into a huddle to identify the cause, take corrective action, and track progress until the problem is resolved. Such processes can be adopted in any business setting. Paradoxically, the companies that excel in making continuous improvement everyone’s job tend to charge certain people and groups—often former members of the CMO—with helping it to happen. Estimates suggest that two-thirds of Fortune 500 organizations have dedicated expertise whose mandate it is to foster, enable, and drive continuous improvement, typically a core team of skilled individuals who direct and coordinate improvement activities.8 Motorola, for example, has three such teams: kaizen teams that address relatively simple challenges; lean teams that focus on cross-functional projects; and Six Sigma teams that perform deep process analytics to resolve complex challenges. Methods that facilitate continuous learning give an organization a chance to pause, step back, and take stock of what’s working, what isn’t, what it means, and what to do about it. The U.S. Army’s After Action Reviews (AARs) serve precisely this purpose, and involve interested observers as well as soldiers from all ranks. They turn training activities into a learning process that asks what was planned, what actually happened, why, and what could be done better next time. The aim is not to judge success or failure, but to focus on learning from the experience so that the organization is better equipped to meet similar challenges in the future. Such sessions don’t necessarily have to take place after the event: “pre-mortems” can also be held to challenge assumptions (managers ask members of their team to play devil’s advocate and compete to articulate plausible ways that a project might go wrong). Continuous learning should also happen looking outside the walls of an organization. One international airline studied how pit stops were orchestrated in the Indianapolis 500-Mile Race to help it develop a more efficient luggage-handling system. In much the same way, a construction company took route-planning lessons from a pizza-delivery chain and was able to raise its rate of on-time cement deliveries from 68 percent to 95 percent.9 All three elements of a learning infrastructure we’ve described will be highly tailored to your organization’s context; some will need to stress particular elements more than others. The key to success is to ensure that all are thoughtfully designed and mutually reinforcing. Take Google’s approach to continuous improvement. When a significant mistake is made within the engineering group, such as a visible service disruption or a slow customer resolution, a postmortem is undertaken to identify what happened, why, its impact, how the issue was resolved, and what will be done to prevent the problem from recurring (continuous learning). However, the postmortem doesn’t stop there. The postmortem is stored in a Google Doc that allows for open commenting and annotations, e-mail notifications, and real-time collaboration. The report is further shared to the organization through a monthly newsletter and through postmortem reading clubs (knowledge sharing). Finally, select postmortems are treated to a “Wheel of Misfortune” exercise where a previous postmortem is reenacted quarterly with newer site engineers who try to determine the root cause of the problem and generate even more novel and effective solutions (improvement processes). Consider also how a heavy equipment manufacturing company moved through the Advance stage of their large-scale change program by creating what was referred to as the continuous product improvement (CPI) process. The process enabled dealers and service representatives to communicate issues raised by customers to the wider organization. When a problem arises, a CPI team from the company contacts the customer to understand its scale and impact, launches an investigation, and in due course, reports back to the aggrieved customer with its findings and solutions (improvement process). It also shares the information with dealers worldwide to assist other customers facing similar issues (knowledge sharing), and with new product development so that relevant findings can be used to improve future design and manufacturing (continuous learning). Putting in place a learning infrastructure requires as much energy and focus as any other stage in a change program. It’s well worth the effort, however. Companies that build the capacity for continuous learning into their organization are 2.6 times more likely to report their success is sustained long after the change program ends.10
As you near the end of the change program, you’ll face the question of where and how to place initiative-dedicated talent back into more permanent roles. The question is a vexing one on many dimensions. Consider an initiative leader, Svetlana, who has been driving the supply chain rearchitecture and digitization effort for the company full-time for the last 18 months, and is wrapping up her efforts. Thanks to her leadership, delivery time frames will no longer be jeopardized by single-source suppliers, and margins will be improved due to the vertical integration strategy of which she has led the implementation. Everyone feels great about the impact achieved, but what’s next for Svetlana? The head of the Supply Chain function is a good 10 years from retirement, and thanks to the great job done, there are far fewer senior positions available in the function and those left have been recently filled as part of the initiative work. And what of the 20–30 Svetlana-equivalents who have been working on other initiatives, and whose technical, relational, and adaptive leadership skills you’ve invested in heavily throughout the course of the change program? Getting the leadership placement aspect of the Advance stage right typically involves an approach that echoes the one used in the Architect stage, where talent was reallocated to deliver the portfolio of change initiatives. The concept is fairly simple: ensure the right talent is in the right roles when viewed through a value-creation lens. And don’t just do it once: institutionalize the process so that you can dynamically adjust how you’re deploying talent to optimize performance as you continuously improve going forward. Be warned, however, that doing this is far easier said than done. Consider the CEO of a healthcare company who we asked to list the top 20 most talented leaders in the company. We then asked him to list the top 20 most important roles in the company—the roles that created the most value. When asked how many people on the first list were filling the roles on the second, the CEO went pale. He didn’t have to do the math to know the answer wasn’t one the board or shareholders would be happy to hear. Further, once the CEO had gone through the steps we’ll describe in the following section—prioritizing roles by value, matching talent to priority roles, and operationalizing the process—he realized both of his lists regarding roles and talent were wrong to begin with! The process for prioritizing value-creating (and enabling) roles starts with defining the value agenda for the organization—understanding how and where value will be created going forward. This process looks at the variables that drive value (in a publicly held enterprise, these include revenue, operating margin, capital efficiency, and so on), and the drivers of those variables. Once the value drivers are well defined, roles can be scored for the extent to which they impact those drivers (and any significant drivers that don’t have roles lined up against them can be flagged for new roles to be considered). Leaders who undertake this process for the first time should prepare themselves for a host of insights that will very likely make them rethink the business. One profound insight relates to the extent value creation follows hierarchy. Based on our experience working with clients to prioritize roles by value, of the top 50 value-creating roles you can expect to find 10 percent in the ranks directly reporting to the CEO (CEO-1), 60 percent at the CEO-2 level, and 20 percent at the CEO-3 level. What about the last 10 percent, you ask? Companies who put a sharp lens on understanding value creation by role often identify roles that don’t exist yet, but should. These are typically roles that capture value that comes from working across existing organizational boundaries or are aimed at capturing new sources of value driven by industry trends (e.g., data and analytics) or that couldn’t have been targeted before the change program put in place the right foundations. Another profound insight relates to the value creation role of functions versus business units. The American football film The Blind Side offers a vivid illustration of the dynamic at play. In the opening scene the viewer is asked who they think is the highest paid player on the team. Those familiar with the game typically think to themselves, “the quarterback,” because that’s the most central person in executing the majority of the plays. The narrator of the film reveals that’s absolutely right, and then asks, “Who is the second highest paid?” Most viewers’ minds go to running backs or wide receivers, as they work most directly with the quarterback to move the ball forward toward scoring the points needed to win. This, the viewer finds out, is wrong. It’s actually the left tackle (if the quarterback is right-handed), a player who doesn’t touch the ball at all. Why? Because they protect the quarterback from what he can’t see (his “blind side”), which are the things that are most likely to get him injured. In the business context, the quarterbacks, wide receivers, and running back equivalents are most often thought of as revenue-generating businesses. The “left tackles” aren’t often obvious, and most senior leaders are hard-pressed to think who they might be. In the Navy, it may be the ship-bound IT outage engineer, who prevents unintended catastrophe for the captain, crew, and humanity at large. In financial services, it may be the head of the government relations function whose sensing and shaping with politicians and regulators can dramatically alter the fortunes of the company and the industry. These are roles that create value by protecting or enabling it, the quantification of which during the prioritization process enables them to be seen on an equal playing field, so to speak! With the concepts clear, let’s talk about how all this works in practice. We once asked the CEO of an insurance brokerage to identify the most important roles in his company—those where A-players should most certainly be deployed. The CEO neglected to mention the account manager for a key customer, in part because the position was not prominent in any organizational chart. By just about any other criterion, though, this was one of the most critical to current performance and future growth. The role demanded a high degree of responsibility, a complex set of interpersonal and technical skills, and an ability to respond deftly to the client’s rapidly changing needs. As it turns out, the CEO was unaware of the incumbent account manager’s growing dissatisfaction, and there was no succession plan in place. When she suddenly took a job at another company, the move stunned the senior team. As performance suffered, they scrambled to cover temporarily, and then to fill, this mission-critical role. In light of her departure, the CEO and top team decided to get serious about taking a value-creation lens to prioritizing roles. They realized that given their strategy centered on building their small business platform and achieving disproportionate growth in China, the value at stake in roles related to those areas looking forward was far greater than roles it currently considered to be its core businesses and geographies. It also discovered that what was previously considered more of a “second-class” function, Service Operations, would require first-class innovation to enable needed efficiencies to be achieved to provide investment in the company’s growth platforms. Further, they realized that a global sales and marketing role was needed to drive the sharing of best practices across regions and business lines, a role that didn’t exist in the organization today. Once you’ve got a handle on what roles the most value will hinge on into the future, it’s time to ensure you have the right talent in those roles. Doing so happens in two steps. The first is to be clear on the jobs to be done (JTBD) to deliver the value. For example, let’s say the head of a product line role is a priority role and is expected to deliver value on the order of $150 million, which translates to year on year 10 percent growth for the next 3 years. The JTBD may include making operations more agile, which will reduce costs by 5 percent, delivering one-third ($50 million) of the needed value. Another JTBD may be driving improved sales and marketing that will increase revenue by 5 percent to deliver another $60 million in value. If momentum growth of the business was, say, $20 million in value, then that leaves a $20 million value creation expectation to come from breakthrough innovation. Once you know the JTBD of the 50 highest value-creating roles, you can then determine what Knowledge, Skills, Attributes, and Experiences (KSAEs) are best suited to getting the JTBD done. For example, in the product leader role mentioned above, the knowledge and skills needed may relate to business development, agile working methods, and target scanning and due diligence (assuming growth will require M&A). The attributes may be someone with global mindset, intellectual curiosity, and great team-building skills. The experience may be having run a $100 million or more P&L, led an integration, and built and executed a high-impact sales model. We suggest this level JTBD and KSAEs be drilled down to for the top 50 most value-creating (or enabling) roles. This number works because it is big enough to take an organization far beyond the “usual suspect” positions, and it means that the collection of roles will typically account for a large portion of overall value delivery for the company. It’s a small enough number, however, such that the most senior leader can play a hands-on role in relation to hiring, retention, performance management, and succession planning related to the roles in question. Once the KSAEs of each of the top 50 value-creating roles are known, the talent match process involves looking to see which leaders in the organization are the best match—regardless of where they currently sit. Conversations become very specific and fact-based. Comments such as, “Javier’s been a successful CFO in a smaller business unit; I think he’s ready to move to the bigger role” can be met with data that Javier’s current role drives value through acquisitions, and yet the vacant role requires driving value through aggressive cost-reduction—is he still the best choice? Fair warning, however, that for companies who have never gone through a process like this, it can get quite uncomfortable. The data-driven process makes it hard to ignore that some incumbents might not be up to the future demands of the job and that leaving them in place would put a significant amount of value at risk. Typically, 20 to 30 percent of those in critical roles today are not well matched. Further revelations from the process will come in the form of being able to identify systemic gaps in knowledge, skills, and attributes across the entire leadership bench. This is highly instructive for retooling the leadership development agenda to add maximum value to the organization going forward. Also, the talent match process enables significant enhancements to succession planning. Career paths can be created to develop needed KSAEs for various roles, and previously hidden candidates can be flagged through analytics as viable options to fill vacancies. Operationalizing the talent match process ensures that the talent matching isn’t a one-off or simply relegated to a once-a-year talent-review-related event. Instead, it ensures that talent is managed as rigorously as the finance team deploys capital on an ongoing basis. Operationalizing the process shouldn’t harken in a new era of giant printed binders and Excel spreadsheets. Everything we have just described lends itself to digital enablement: simple, highly interactive user interfaces, backed by a powerful data and analytics engine. There are many such solutions available to organizations, one of which is McKinsey’s Talent Match, which has been developed precisely for these purposes. By populating it with the KSAEs for your priority roles and your people, and by combining it with additional information about their performance and preferences, a dynamic model of your leadership bench is created. With a swipe of a touch screen, you can see the domino effect of moving one person into a new role in terms of impacts on other roles (e.g., is the succession plan robust—would we be willing to put person x into role y?), people (e.g., does anyone become a retention risk?), and overall human capital metrics (e.g., diversity, depth of capability sets). There’s little doubt that in the third edition of Beyond Performance, this section will be greatly expanded to incorporate many further advances in people analytics. The field remains in its infancy as only 8 percent of companies report that they are capable of predictive modeling when it comes to human capital. But it’s advancing quickly: only a year earlier, the figure was 4 percent. It won’t be long before organizations will be able to use sophisticated algorithms to anticipate and mitigate key talent departures, find otherwise “hidden” talent in the organization that is likely to be successful in key roles, and create development pipelines with dramatically increased precision. Consider that when the National Bureau of Economic Research pitted humans against an algorithm to hire candidates for more than 300,000 high-turnover jobs across 15 companies, human experience, instinct, and judgment were soundly defeated. Those picked by machines stayed longer and performed as well or better—a result that held whether picking frontline, middle management, or C-suite positions.11 Regardless of how sophisticated or digitally enabled, once you have information on JTBD and KSAEs for the top 50 value-creating roles (or more), an operationalized process typically involves revisiting the data monthly. This is typically done by the HR leadership team, who meet to identify trends across business units—for example, the lag in certifications of certain role-specific skill requirements, such as digital fluency. Working alongside leaders, the team might also assess changes in the performance of individuals in critical roles, asking questions such as, “Is this individual delivering the value expected? What interventions (for instance, coaching, training, or better-aligned incentives) can support this individual?” Or, conversely, “This individual has been flagged as an attrition risk, what’s our save strategy?” Meanwhile, the question of, “Do we have the right people in the right roles?” is typically discussed and acted on quarterly by the most senior team. The rewards of prioritizing roles by value, matching talent to those roles, and then turning it into “how we do things around here” going forward are significant. Based on our research, those companies that are characterized as “fast” talent reallocators are 2.2 times more likely to outperform their competitors on total returns to shareholders (TRS) than are slow talent reallocators.12
Celebrating the successful accomplishment of a change aspiration is a very special feeling. The feeling of achievement is coupled with a deep sense of belonging to a winning team—one that has accomplished far more than the sum of its parts. There is confidence for the road ahead and a humility gained from the many course-corrects made along the way, prompted by the numerous cycles of action and reflection. The significant skills built are linked to a new level of wisdom that can only come from experience. Above all else, however, there is a new level of trust. We did what we said we’d do. We were transparent with one another. We learned from our mistakes along the way. We did what was authentically us—we didn’t copy someone else. This base of trust is the ultimate foundation on which to drive continuous improvement in performance and health, and one that is exceedingly difficult for competitors to match. Don’t take it for granted! There’s an old adage, “Trust arrives on foot and leaves on horseback.” Of course, on many fronts you will have built the goodwill with employees such that they will generally give the organization the benefit of the doubt and seek information to clarify if things don’t feel right. Two scenarios, however, cause the trust horse to bolt at champion thoroughbred speeds. The first scenario is obvious: steer clear of any violations of honesty and integrity. The second, however, can be easily violated unwittingly, as it comes from our “predictably irrational” relationship with fairness. Take, for example, a bank that had gone through a major change program to increase revenues. It had rationalized its product portfolio, simplified its product set, strengthened the value proposition of those products that remained, revamped incentives, provided sales training, and so on. Once the revenue targets had been hit, the bank declared victory and pushed the responsibility for continuous improvement in sales to the channels and in pricing to marketing. As the marketing department drove toward its continuous improvement targets, it created more sophisticated risk-adjusted rate-of-return models leveraging the improved skillsets, better data, and enhanced tools that had been put in place as a result of the change program. This modeling revealed that many of the banks’ products were priced in a way that did not fully reflect the credit risk it was taking on. New pricing schedules were created and rolled out, and at the same time, sales incentives were adjusted to more appropriately reward customer profitability rather than volume. The result? Customers (profitable as well as unprofitable) deserted in droves. Price overrides soared, destroying a great deal of value. So what had gone wrong? Looking at what’s called an “ultimatum game” can offer us a clue. We give player A US$10 and explain that the money has to be shared with player B. Player A has to propose how the money is split, and if player B accepts the offer, they both get the agreed shares. If B rejects the offer, though, no one gets any money. Studies show that if player A offers a US$7.50/US$2.50 split, player B will reject it more than 95 percent of the time, preferring to go home with nothing than see someone else get three times as much for no good reason. And that isn’t because the absolute sums are so small: even when the money on offer is the equivalent of two weeks’ pay, the results are similar.13 There’s a clear message here for leaders. If employees are put in a position that violates their sense of justice and fair play, they will act against their own self-interest and therefore, even against whatever formal incentives are in force. This may seem irrational, but it’s entirely predictable. This implication isn’t just speculation from ultimatum games, either. In one of business school professor Sebastien Brion’s experiments, for example, he not only found that bosses overestimate the strength of their bonds with subordinates, but also that subordinates of an unfair boss will form alliances against the boss, even when not in their financial interest to do so.14 Let’s go back to the bank. When it raised its prices and adjusted its sales incentives, frontline staff thought it was being unfair to customers—a case of executives getting greedy and losing sight of customer service. Even though they were putting their own sales targets in jeopardy, many bankers bad-mouthed the new policies to customers, choosing to take their side rather than the bank’s. They also used price overrides to show good faith to customers and take revenge on the organization. Ironically, their perception of injustice was misdirected. Customers were, after all, only being asked to pay a price commensurate with the risk the bank was taking on. The whole sorry saga could have been avoided if the bank had only paid enough attention to employees’ sense of fairness when it was developing the communications and training that accompanied the price changes. Leaders are wise to keep in mind that during a Five Frames of Performance and Health change program, there is significant scaffolding in place to guard against violating employees’ sense of fairness. There is a premium placed on employee involvement, explaining why, planning from the “receiver” view versus just from the “sender” view, and ensuring the big picture is constantly reinforced (recall the techniques discussed in Chapter 6 to overcome the “curse of knowledge”). When this scaffolding is pulled back, it’s up to leadership to hold the sense of fairness sacred and keep it in place. ■ ■ ■ The Advance stage transitions your organization from the intense period of change (the steep part of the S-curve) into a period of continuous improvement (so that the top of the S-curve is gradually rising indefinitely). It does this by putting in place a learning infrastructure that embeds knowledge sharing, institutionalizes improvement processes, and facilitates continuous learning. It also involves getting leadership placement right by prioritizing roles by value, matching talent to priority roles, and operationalizing the process. Finally, it prompts leaders to guard against violating employees’ perceived sense of fairness—doing so is a fast ticket to eroding the all-important trust base that has been developed in and across the organization during the course of the change program (Exhibit 7.1). Exhibit 7.1 A Proven Approach to Leading Large-Scale Change No doubt there will come a time when this ongoing adaptive approach to change will meet a challenge or see an opportunity that again calls for an intensive adjustment period in the form of a large-scale change program. This may be prompted by a change in the competitive landscape, technology innovations, shifts in customer needs, regulatory requirements, geopolitical events, or other shocks. When it does, you’ll be ready—in a position of strength due to having a healthy organization to start with and knowing how to use the Five Frames of Performance and Health to make the needed change happen. In the context of a never-ending journey, congratulations, you have arrived!Performance: Learning Infrastructure
Embed Knowledge Sharing
Institutionalize Improvement Processes
Facilitate Continuous Learning
Health: Leadership Placement
Prioritize Roles by Value
Match Talent to Priority Roles
Operationalize the Process
Master Stroke: Ensure Fair Process
Notes