The Case of the Struggling Health-Care Company

To better appreciate the kinds of problems that result when companies focus on people strictly as a cost, consider the story of a health-care provider we refer to here as HealthCo. That organization was struggling to reduce its costs. Like other companies in its industry, it was being squeezed. Insurance and government payouts were reducing reimbursements even as the cost of operating was going up every year. The only way HealthCo could maintain profitability was to hold the line on some costs and reduce others. One of the ways it aimed to do that was by reducing its employee outlays, a major segment of its total cost structure. For example, the organization focused on how it staffed its facilities, especially with regard to the use of part-time employees, the amount of overtime worked, and managerial headcount.

Asset Scrapping

The notion of people as a variable cost may have outlived its usefulness, particularly in knowledge-based enterprises in which the skills, customer relationships, and inventiveness of employees are the primary source of competitive advantage. In those enterprises people are the obvious source of value creation. In contrast, the enterprise’s buildings, computers, and filing cabinets are commodities that provide only moderate value and no competitive differentiation. In these companies laying off people is analogous to a farmer dumping his seed corn in the trash or a steel producer leveling part of its production operation. Both actions sacrifice future earning power and don’t even recoup the “scrap value” of what they’ve thrown away.

What is the scrap value of the furloughed people a company has trained and developed at great expense over the years?

The growing recognition of the value of human capital undoubtedly explains why knowledge-based companies such as Schwab, the U.S. financial services giant, was so reluctant to furlough people during the most recent recession. Forced by shrinking customer demand to reduce headcount, the company nevertheless went to great lengths to keep discharged people in its orbit through six-month leaves, the use of rehiring bonuses, and other mechanisms. It recognized that layoffs were robbing it of firm-specific knowledge it had spent heavily to develop and would need again as soon as customer demand returned.

After some deliberation HealthCo decided to look for every opportunity to reduce overtime. It also reduced the number of managers in its facilities. Further, it decided to replace many full-time employees with part-timers who cost less per hour in base wages and received fewer or no benefits. This tactic was abetted by the practice of obsessive benchmarking, which encouraged HealthCo to compare its ratio of part-time to full-time employees with those of others in its industry. That comparison told HealthCo management that it could save money by having a higher percentage of part-timers.

The choice to rely on more part-time employees appeared to give HealthCo both greater flexibility and lower costs. The work schedules of part-timers could be shifted with rising and falling patient censuses, and their pay and benefits would be measurably less than those of their full-time counterparts. This strategy appeared to be a workable solution to the company’s financial problems.

Unfortunately, the company understood only half the equation. It knew its wage costs but had no information about the value generated by its staffing policies. Consequently, HealthCo initially celebrated the cost savings produced by its new workforce. However, when it ultimately assessed the impact of the new scheme on value creation, it found that excessive use of part-timers was hurting overall productivity, as is shown in Figure 3-1.

Figure 3-1: The Most Productive Units Used Full-Time Employees

Our analyses revealed that the organization’s interests were not well served by its growing reliance on part-timers. At the time of the analysis roughly 45 percent of HealthCo’s employees were full-timers, far short of the optimal level identified through statistical modeling. Through that modeling, the influence of other variables that could affect productivity was controlled, including differences in facilities, labor markets, wages, capital investments, case mix complexity, employee turnover, and percentage of total hours worked as overtime. By measuring and plotting the relative productivity of full- and part-time employees at this company, as shown in Figure 3-2, we established the optimal mix of part-time and full-time employees as slightly over 60 percent full-time employees and slightly under 40 percent part-time employees. By deviating from that optimal mix, HealthCo unwittingly destroyed revenue worth five times the anticipated savings, an amount equal to 3 percent of the company’s annual revenues.

Figure 3-2 is a result of what we call Business Impact Modeling^SM, an approach that is described more completely in Chapter 6. The heart of the approach is the disciplined analysis of how key business outcomes such as productivity are affected over time by human capital attributes and practices.

Figure 3-2: Too Few Full-Timers Reduced Productivity

Why did having too many part-timers hurt productivity? One factor may have been the impact on long-term career incentives for full-time employees. As the number of part-time employees in a facility increased, full-time employees experienced slower earnings growth, fewer promotions, and in some cases higher turnover. The reduction of full-time people also cut into the development of the firm-specific know-how HealthCo needed to operate effectively, especially in its tertiary-care hospitals that provided more complex services.

Further analysis showed that part-time employees were not being deployed in ways that created the hoped-for flexibility. The evidence indicated that short-term changes in caseloads were not matched with commensurate changes in the use of part-time employees. The potential gains expected from part-time employees did not materialize because HealthCo deployed them as if they were full-time employees.

Still further analysis showed that the cost-cutting strategy of reducing overtime also had backfired. Intuitively, reducing overtime hours seemed like a sure way to reduce personnel costs, but that commonsense idea didn’t hold. We found that productivity at HealthCo actually increased 3.3 percent for every 1 percent increase in the ratio of overtime to regular hours worked by current employees. Apparently, HealthCo managers were using overtime to get more value out of their full-time employees, an increasingly scarce resource. Of course, overtime hours cannot be increased without limit, but within the range of “normal practice” in this system overtime appeared to represent a very effective utilization of spending on human capital.

This case vividly displays the systems concept of unintended consequences. Here a company’s noodling with one people practice produced consequences in other, related practices. Indeed, facts about the complementary effects of staffing and overtime needed to be understood in order to get the right practices in place.

Lessons

In summing up the HealthCo case, the company made three mistakes in its human capital strategy that one sees repeated in different companies and different industries:

1. Placing too much reliance on benchmarking. Many companies purchase data that, among other things, indicate such things as the average ratio of full-time to part-time employees at so-called high-performing companies. The implication is that (a) that ratio has a causal relationship with high performance and (b) other companies should follow suit. Because of contextual differences, however, there is no reason to believe that mimicking the practices of other companies will help your company.

   Lesson: Use external benchmark data to stimulate thinking and further investigation; don’t use those data to make decisions, especially strategic decisions.

2. Basing decisions about human capital on intuition. It seemed that reducing overtime and raising the proportion of part-timers in the workforce would reduce spending on employees. However, that intuitively appealing idea did not take into account the complex dynamics of the workplace.

   Lesson: What appears intuitively obvious does not always hold true in a complex system such as a workplace. Sort out important causal relationships before making any decisions.

3. Measuring costs but not value. HealthCo’s decision makers missed a big one here. Full-time employees cost more, but a dollar spent on them produced more value than did an equal amount spent on part-timers. The reason: higher productivity among full-time people.

   Lesson: In measuring costs, also measure the value that is received in return.