The CEO was coming to visit, and the senior plant manager at a large biotech production facility was uneasy. The latest numbers from the Finance Department hadn’t been good: the plant’s labor costs were rising, while margins were slumping. When the CEO asked what was going wrong, the manager could only describe his difficulties getting his hands around the problems.

As he explained, standard accounting measures based on the cost of goods sold meant that he couldn’t tell for sure whether margins were declining because fluctuating production volumes were reducing operating efficiency or because variations in the mix of high- and low-margin products were bringing down the plant’s average margins—or both. He thought the numbers should be better, given his knowledge of what was happening on the plant floor, but he had no way to dig into the operating details to explain quarter-on-quarter changes in productivity. That would require a much finer-grained understanding of the many components of product costs. The CEO gave the plant executive three months—until the next operating review—to come up with a better answer.

The plant manager knew he faced a devil of a time parsing the many activities of the biotech facility. For starters, the plant had seven distinct production areas and thousands of stock-keeping units (SKUs). In one laboratory-like section, PhDs mixed customized chemical products by hand. Elsewhere, fermentation and cracking lines processed biologic inputs. In another wing, staffers surveyed a continuous stream of capsules and vials as they passed through a fully automated production line. An assembly line for medical instruments occupied one wing; other areas housed testing and packaging lines. Some product families had hundreds of SKUs because of slight differences in key ingredients or concentrations. Swings in the monthly volumes and mix of production compounded the difficulty of pinpointing cost problems.

Imprecise cost accounting and its distortions

This plant was complex, but its problems are common. The issues facing its managers resemble those bedeviling myriad processes used in the fabrication of semiconductors, the production of specialty chemicals, and other applications with thousands of SKUs and complex production environments. Similarly, in our experience many managers who oversee shop floors consider traditional cost-of-goods-sold accounting—the widely used measure of operational performance—a blunt instrument. Fixed costs for capital equipment and inventory charges, for example, are averaged across SKU groups, masking changes in variable costs. When products are scrapped, that could often be due to poor forecasts by the marketing and sales functions, an issue that should be recognized in productivity measures. In most factories, multiple products often pass through the same production lines and share the same workers, making true cost assignments difficult, so the averages applied distort the true cost picture. Volume and mix swings accentuate the problem. Finally, when output volumes rise or fall, costs often don’t follow in lockstep, since there’s a time lag in consuming inventory.

The effects of getting measurements wrong can be substantial. Without good cost data, it’s hard to decide how to price products or even how much to produce. A hazy understanding of which production areas in a plant perform poorly leads to bad investment decisions. Multiplied across a large corporation’s manufacturing footprint, even minor plant-level miscalculations can have a significant impact. That’s a serious handicap in the current economic climate, since slower growth and more intense competition put a premium on operating efficiency. In plants we have examined, true costs vary from those assigned by traditional cost-accounting methods by 30 to 100 percent.

A new basis for measuring costs

The plant manager, knowing that he had no time to waste, quickly put together a team of experts, from a variety of functions, with the best knowledge of the plant’s processes and costs. The members of the team divided up the tasks facing it. Some undertook full-day fact-finding missions across the plant to get a more detailed understanding of the way processes flowed and the production staff was configured. Others pored over data on the cost of materials, labor, scrap, and overhead. After two months, the group had a plan for tackling the issues.

Clearly, the key was developing a radically detailed understanding of what happened to costs as the product mix and volumes shifted. The team mapped out three steps to accomplish this goal. First, it would define new product pathways and subpathways—granular “factories within factories” that made it possible to assign costs more accurately. Next, using a regression analysis of historical data, the team would detail cost drivers for each subpathway, an analysis based on past relationships between input costs and output produced. Finally, to account for dissimilar products, as well as for changes in the product mix and volumes, the team would define standardized “manufacturing units” (see below) that would allow productivity to be measured across time periods.

Using pathways to fine-tune product segments

The team grouped the plant’s product lines into pathways according to their common characteristics, such as the types of workers handling them and the processes used to manufacture them. In some cases, different pathways share labor or machinery. These high-level pathways, for example, separated biologics from chemical solutions and from instrument assembly. To delineate costs clearly, each pathway had its own measure of output: grams of gel for biologics, milliliters for chemicals, and pieces for instruments. The result was a set of distinct product families, each comprising several narrowly focused lines that shared common traits.

Building profiles of cost drivers

The next step was to identify cost drivers for each subpathway to help estimate input costs by the amount of output produced. Team members mined data on materials, labor, capital costs, scrapping charges, and other costs for each subpathway’s finely tuned production units. The team used statistical estimates to build these profiles, because materials and labor costs don’t rise and fall in linear fashion as output changes. (A 15 percent increase in the output of chemical solutions, for example, raises total hourly wages by only 10 percent, thanks to scale economies.) To estimate these cost and volume relationships, the team performed hundreds of regression analyses on historical cost data.

With the pathways and information on cost drivers in place, the factory team could accurately assign the amounts of chemical and biological compounds, labor inputs, and in-process scrap that went into, say, the creation of a vial. Take the example of a shop floor area that processed both vials of chemicals and biologic capsules. Traditional accounting averaged labor costs for this area across all the biologic and chemical products that passed through the line; only minor adjustments were made for variations in the mix or in volumes. The new data on cost drivers, by contrast, made it possible to measure labor costs down to a fraction of a penny for each of the more precisely defined product pathways.

Standardize output with manufacturing units

These new metrics gave a highly accurate picture of how costs varied within each pathway when volumes or the product mix changed. But the team still had no way to get a broad picture of productivity fluctuations across the entire facility and across time periods as mixes and volumes changed. This was an apples-and-oranges problem: as the mix of vials and capsules fluctuated, there was no meaningful way to add vials measured in milliliters to capsules measured in grams across time periods to get a baseline output figure.

With pathway and cost driver analysis, the team could assess productivity change across periods by modeling the predicted production costs of each pathway and comparing them with actual incurred costs. To solve the apples-and-oranges problem, the team denominated these input costs in standardized manufacturing units, which allowed costs at the most granular levels to be rolled up to pathways and, critically, to the site level. This approach provided the big picture on costs and changes in productivity (for a before-and-after example, see the interactive exhibit, “Product pathways reveal true costs”).

Product pathways reveal true costs

Pathways and standardized manufacturing units reveal how costs vary when volumes or product mix change.

Here’s an illustration. In a base quarter, the biologics pathway might produce 1,000 grams of gel at an expected cost of $500 (in direct and indirect labor), the chemicals pathway 500 milliliters at an expected cost of $1,000 (also in direct and indirect labor). The computation assigns a value of 1 manufacturing unit for every $50 in production costs, so the first pathway earned 10 manufacturing units ($500 divided by 50), the second pathway 20 ($1,000 divided by $50), for a total of 30 manufacturing units. If in a subsequent quarter, the actual cost of producing 1,000 grams of gel fell to $450, the cost per manufacturing unit would fall to $45, from $50—for a productivity gain of 10 percent. Similarly, changes in total costs in other pathways can be compared with regression-expected costs and the totals rolled up across pathways for a view of overall productivity change at a site.

Applying the lessons

At the next quarterly meeting with the CEO, the new metrics were in force. Repeating the pattern of past meetings, the Finance Department reported numbers that seemed to show persistent problems. Labor costs and the number of labor hours worked had fallen, indicating a falloff in business. Meanwhile, raw-material inputs had skyrocketed. Using the newly developed pathway cost numbers, however, the plant executive showed that production volumes rose substantially in the instruments line but had dropped significantly for chemicals. The production of instruments involves high costs for materials but not much for labor—the exact opposite of the pattern for chemical products. That explained how the cost of goods sold could climb in the face of declining hours.

What about productivity? An analysis based on manufacturing units showed that it had risen by 5 percent. While the product mix had shifted substantially, total output, as measured by manufacturing units, had risen by 3 percent; the inputs used to produce those manufacturing units had fallen by 2 percent.

The CEO incorporated the new metrics into company-wide reporting practices, and the gaps between operations and financial-performance measures diminished across the organization. A clearer picture of product margins allowed management to drop a range of poorly performing SKUs and to shift resources to higher-margin products. A more detailed understanding of costs led the company to realize further economies by shifting some production to sites where higher volumes would help absorb high fixed costs. The new measures also entered the company’s performance dashboards, and factory managers began tracking leading indicators of productivity, such as in-process materials scrap and labor utilization rates, on a daily basis.

In the wake of the recession, the demand for increased operating efficiency remains high. But disparities between financial and plant measures of costs and productivity exist at many manufacturing facilities. A better alignment, based on the enhanced gathering and analysis of data, can improve efficiency and provide a stronger foundation for pricing and product strategies.

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The key is identifying and addressing the barriers workers face in their daily interactions.

Are you doing all that you can to enhance the productivity of your knowledge workers? It’s a simple question, but one that few senior executives can answer.

Their confusion isn’t for lack of trying. Organizations around the world struggle to crack the code for improving the effectiveness of managers, salespeople, scientists, and others whose jobs consist primarily of interactions—with other employees, customers, and suppliers—and complex decision making based on knowledge and judgment.¹ The stakes are high: raising the productivity of these workers, who constitute a large and growing share of the workforce in developed economies, represents a major opportunity for companies, as well as for countries with low birthrates that hope to maintain GDP growth.

Nonetheless, many executives have a hazy understanding of what it takes to bolster productivity for knowledge workers. This lack of clarity is partly because knowledge work involves more diverse and amorphous tasks than do production or clerical positions, where the relatively clear-cut, predictable activities make jobs easier to automate or streamline. Likewise, performance metrics are hard to come by in knowledge work, making it challenging to manage improvement efforts (which often lack a clear owner in the first place). Against this backdrop, it’s perhaps unsurprising that many companies settle for scattershot investments in training and IT systems.

Since knowledge workers spend half their time on interactions, our research and experience suggest that companies should first explore the productivity barriers that impede these interactions. Armed with a better understanding of the constraints, senior executives can get more bang for their buck by identifying targeted productivity-improvement efforts to increase both the efficiency and effectiveness of the interactions between workers.

Among companies we’ve surveyed (see sidebar, “About the research”), fully half of all interactions are constrained by one of five barriers: physical, technical, social or cultural, contextual, and temporal. While individual companies will encounter some obstacles more than others, our experience suggests that the approaches to overcoming them are widely applicable.

Physical and technical barriers

Physical barriers (including geographic distance and differences in time zones) often go hand in hand with technical barriers because the lack of effective tools for locating the right people and collaborating becomes even more pronounced when they are far away. While these barriers are on the wane at many companies given the arsenal of software tools available, some large, globally dispersed organizations continue to suffer from them.

One remedy implemented by some organizations is to create “communities of practice” for people who could benefit from one another’s advice—as the World Bank has done to help the 100 or so of its planners who focus on urban poverty to facilitate discussions on projects to upgrade slums. The communities feature online tools to help geographically dispersed members search for basic information (say, member roles and the specific challenges they are addressing) and sometimes use the latest social-networking tools to provide more sophisticated information, including whom the members have worked or trained with. By supplementing electronic tools with videoconferences and occasional in-person meetings, communities can bridge physical distances and build relationships.

Social or cultural barriers

Examples of social or cultural barriers include rigid hierarchy or ineffective incentives that don’t spur the right people to engage. To avoid such problems, Petrobras, the Brazil-based oil major, created a series of case studies focused on real events in the company’s past that illuminate its values, processes, and norms. The cases are discussed with new hires in small groups—promoting a better understanding of how the organization works and encouraging a culture of knowledge sharing and collaborative problem solving. (To benefit further from such approaches, companies should include knowledge sharing in performance reviews and ensure that team leaders clearly communicate acceptable response times for information requests. The communities of practice described above can help too: employees are far more likely to give timely and useful responses to people in their network.)

Contextual barriers

Employees who face contextual barriers struggle to share and translate knowledge obtained from colleagues in different fields. Complex interactions often require contact with people in other departments or divisions, making it hard for workers to assess a colleague’s level of expertise or apply the advice they may receive. Think of the disconnect that often occurs between a company’s sales department and its product-development team over customer data. The two groups frequently struggle to communicate because they think and talk so differently about the subject (sales staff devote attention to customer insights while developers focus on product specifications).

To overcome contextual barriers, organizations can rotate employees across teams and divisions or create forums where specialists in different areas can learn about one another’s work. The US National Aeronautics and Space Administration (NASA), for instance, holds a biannual “Masters Forum” to share knowledge across disciplines. About 50 employees from different parts of the agency attend the meetings to hear other NASA colleagues talk about the tools, methods, and skills they use in extremely complex projects. The sessions are lightly moderated and very interactive.

Similarly, managers at Ecopetrol, a Colombian gas and oil company, have found that technical forums not only break down the natural barriers between occupations but also facilitate knowledge sharing across geographic boundaries. Moreover, the forums build trust, which encourages employees to share information more freely.

The barrier of time

The final barrier is time, or rather the perceived lack of it. If valuable interactions are falling victim to time constraints, executives can use job roles and responsibilities to help identify the employees that knowledge workers should be interacting with and on what topics. In some cases, companies may need to clarify decision rights and redefine roles to reduce the interaction burden on some employees while increasing it on others.

Boston-based Millennium Pharmaceuticals, which develops drugs for cancer treatment, did just that. When it found that researchers didn’t have time to share lessons from their experiments, it created a small group of scientists to act as “knowledge intermediaries.” Based on meetings with company scientists as well as presentations, these employees summarize findings and submit them to an internal database. They also act as brokers by sharing knowledge across groups. The company reckons that this practice, combined with other initiatives, has boosted success rates for the company’s research and reduced the time needed to make key decisions.

Source:

McKinsey

Here is an article that IT and Communications providers are more regularly looking at...

 Many IT service providers are locating some operations in second-tier cities of their home markets.

Bosses matter. They matter because more than 95 percent of all people in the workforce have bosses, are bosses, or both. They matter because they set the tone for their followers and organizations. And they matter because many studies show that for more than 75 percent of employees, dealing with their immediate boss is the most stressful part of the job. Lousy bosses can kill you—literally. A 2009 Swedish study tracking 3,122 men for ten years found that those with bad bosses suffered 20 to 40 percent more heart attacks than those with good bosses.

Source: Total Executive

Many companies throw financial incentives at senior executives and star performers during times of change. There is a better and less costly solution...

Our work with companies in many sectors (among them, energy, financial services, health care, pharmaceuticals, and retailing) suggests there is a better and less costly approach to employee retention—and one that will serve companies well as they merge, restructure, and reorganize to seize strategic opportunities as the economy picks up. It starts with identifying all key players, but targeting only those who are most critical and most at risk of leaving. These people are then offered a mix of financial and nonfinancial incentives tailored to their aspirations and concerns. A European industrial company applied this approach during a recent reorganization and found that it required only 25 percent of the budget that had previously been spent on a broad, cash-based scheme. What follows are three suggestions for companies with similar hopes of keeping their top talent without breaking the bank.

1. Find the “hidden gems”

HR and line managers need to work together during times of major organizational change to identify people whose retention is critical. Yet too often companies simply round up the usual suspects—high-potential employees and senior executives in roles that are critical for business success. Few look in less obvious places for more average performers whose skills or social networks may be critical—both in keeping the lights on during the change effort itself as well as in delivering against its longer-term business objectives.

These “hidden gems” might be found anywhere in the company: for example, the product-development manager in an acquired company’s R&D function who is nearing retirement age and no longer on the company’s list of “high potentials”—yet who is crucial to ensuring a healthy product pipeline; or the key financial accountant responsible for consolidating the acquired company’s next financial report. Even if the employees’ performance and career potential are unexceptional, their institutional knowledge, direct relationships, or technical expertise can make their retention critical. In one merger we recently observed, certain sales support personnel who filled orders and took inventory turned out to be just as important as the star salespeople.

Once HR and line managers have generated a thoughtful and more inclusive list of key players (usually 30 to 45 percent of all employees), they can begin to prioritize groups and individuals for targeted retention measures—in our experience, 5 to 10 percent of the workforce. The key is to view each employee through two lenses: first, the impact his or her departure would have on the business, given the focus of the change effort and his or her role in it; and second, the probability that the employee in question might leave.

When a European industrial company conducted this exercise, it mapped the outputs on a risk matrix. The results were sobering. The company had been launching a new centralized trading unit—requiring almost all traders and their support staff to relocate, with half of them heading to another country—and was steadily losing people. The risk matrix revealed that another 104 people were likely to leave. Among them were 44 employees who were critical for the success of the trading unit. To be sure, some were traders but most were IT, finance, and administrative staff with unique knowledge of the unit’s systems.

2. Mind-sets matter

One-size-fits-all retention packages are usually unsuccessful in persuading a diverse group of key employees to stay. Instead, companies should tailor retention approaches to the mind-sets and motivations of specific employees (as well as to the express nature of the changes involved).

When executives at the European industrial company looked beyond their standard retention package (bonuses plus compensation for the costs of the move) and focused instead on the needs of individual employees, they found a more nuanced situation than they had anticipated. Among the key people at risk were two main groups with two different mind-sets.¹ One consisted of individuals who were worried about relocating because it would uproot their families. The people in the other, more career-driven group didn’t mind living and working abroad but wondered, as they faced change in any event, whether staying or searching for another employer would best further their careers.

In one-on-one conversations with the people in the family-oriented group, managers explored specific concerns and discussed how the company could add to the measures already in place to increase the likelihood of retaining these individuals. On the menu of incentives: an increase in base pay, assistance in finding schools and kindergartens for their children, career counseling for their spouses, language training, and alternative work arrangements so employees could work at home or commute instead of relocating.

Meanwhile, in the conversations with the career-driven people, managers offered them a cash bonus but focused primarily on the organizational chart of the new, centralized unit, which had been designed from scratch. For people who had held senior roles in their local organization, it was essential, for example, to learn about their new responsibilities and how many direct reports they would have; for many of the more junior people a key question was who their bosses would be. Also high on the agenda was a dialogue with each individual about his or her future career and leadership opportunities in the context of the unit’s new strategy.

This targeted approach, which cost just one-quarter as much as the broad financial incentives plan the company had previously applied, succeeded in stabilizing the new unit. One year after its launch, some 80 percent of the staff who received special attention had started to work in the new location—a significantly higher share than for the group that didn’t receive this attention. Since its founding, the unit has increased its sales by more than 30 percent and its earnings before interest and taxes (EBIT) by more than 90 percent.

3. Retention is about more than money

As the European industrial company’s experience suggests, financial incentives play an important role in retention—but money alone won’t do the trick. Praise from one’s manager, attention from leaders, frequent promotions, opportunities to lead projects, and chances to join fast-track management programs are often more effective than cash. Indeed, a 2009 McKinsey Quarterlysurvey found that executives, managers, and employees rate these five nonfinancial incentives among the six most effective motivators when the main objective of the exercise is retaining people.²

One financial services firm undertaking a recent cost-cutting initiative elected to use onlynonfinancial measures—including leadership-development programs—to retain the pivotal players it had identified as being at risk of departure. One year later, none of those players had quit.

Leadership opportunities are a powerful incentive in any sector. In a pharmaceuticals merger aimed at building the North American acquirer’s presence in Europe, some 50 middle managers from the acquired company accepted invitations to join trans-Atlantic teams with key roles in integrating the two organizations and developing business strategy. The chance to network with the acquirer’s senior people and develop leadership skills during the two-year program signaled to these high-potential employees—in many cases, people who had been slated for promotion before the merger was announced—that they had a promising future in the new organization. For the acquirer’s senior executives, one benefit was the opportunity to assess first hand a potential next wave of top management talent. The program was one part of a carefully designed communication and engagement plan that made it possible to sustain the energy of the 50,000-person strong workforce during the merger. The company ultimately needed to offer only 750 targeted employees a financial incentive.

When financial incentives are required, it is important to design them appropriately and use them in a targeted way. For example, one-third of the retention bonus during a merger might be paid to pivotal staff even before the deal is closed, with the remaining two-thirds to be paid out a year later—dependent in part on the recipients meeting defined performance criteria such as the successful transfer of systems from the acquired company.

Targeting retention measures at the right people using a tailored mix of financial and nonfinancial incentives is crucial for managing organizational transitions that achieve long-term business success; it’s also likely to save money.

Still, executives mustn’t view employee retention as a one-off exercise where it’s sufficient to get the incentives packages right. Rather, best-practice approaches build on continuous attention and timely communication every step of the way to help employees make sense of the uncertainty inherent in organizational change. Ultimately, what many employees want most of all is clarity about their future with the company. Creating that clarity requires significant hands-on effort from managers, including the ongoing work of tracking progress so that companies can quickly intervene when problems arise.