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Effective Frontier

      The definitions of ratios most commonly used in the analysis of corporate performance in this book are provided in the Appendix.

      This book is the culmination of a three-year research project to understand effectiveness. To write this book, we built a database using public sources of information. We then grouped the data by NAICS codes, and began plotting the intersections of the Effective Frontier manually using orbit charts to understand the trends. We then began to review the patterns of the plots with industry leaders to gain insights into the drivers of the trends.

      An orbit chart may seem abstract at first – like a modern art painting of wavy lines – but we have found that it is the best way to study the patterns, or progression, of operational metric performance over time.

Let's take a closer look. Figure 1.5 is an orbit chart example. This is the pattern, or progression, for Walmart for the period of 2002–2012 at the intersection of two metrics: inventory turns and operating margin. The averages for the period are shown in the box along with the stock ticker symbol. In each orbit chart, because the metrics can get confusing, we identify which corner of the chart points toward the best scenario. Note that Walmart has made great improvements on inventory, but not in margins. As we will see later, Walmart is an example of a company that has made great strides in improving the efficiency of operations, but not in driving overall effectiveness.

Figure 1.5 Example of an Orbit Chart

      Source: Supply Chain Insights LLC, Corporate Annual Reports 2000–2013 from One Source.

      I continued, “Joe, as we have mined the data, we find three intersections of the financial ratios to have the most interesting patterns. Each offers a distinctly different view, and you cannot assess improvement without looking at the three together.” I wrote the three intersections on the whiteboard in his office:

      1. Inventory turns versus operating margins

      2. Year-over-year growth versus return on invested capital

      3. Revenue per employee versus inventory turns

      Joe hurriedly scribbled them down. As I worked with Joe, I found that he was writing more and more notes to himself in his black notebook. His intensity amused me. He was such an eager and willing student.

      Details Matter: The Nitty-Gritty of the Analysis

      “It's hard work,” I continued. “In fact, we underestimated the amount of work to do the analysis of corporate balance sheet data and the determination of the Effective Frontier. When we started the analysis, we used absolute numbers, but we ended up using financial ratios. This shift enabled the comparison of companies across currencies and enabled us to better understand the trends of companies of differing sizes. After plotting the trends, we partnered with an operations research team at Arizona State University to help define the methodology to determine balance and resiliency. The data is complex, and we wanted to define a simple methodology to translate abstract patterns into meaningful insights.”

      “I have difficulty doing this type of analysis, but when I see your research, I love it. I am a fan,” said Joe. “It's one thing to talk about corporate performance, and another to understand how it transforms a balance sheet. When I get to the point when I understand this, I will feel real pride.”

      I smiled and nodded in agreement. “Let me share some insights. One of our first big insights when we started looking at performance results was the danger of using compound metrics in a vacuum. Let me explain: A compound metric is the result of a combination of individual metrics. For example, the two most commonly used compound metrics that one finds in corporate measurement systems are ‘cash-to-cash’ and ‘perfect order.’ Let's take cash-to-cash.” I then turned to his board and wrote, “Cash-to-cash (C2C) = Days of receivables (DOR) + Days of inventory (DOI) – Days of payables (DOP) outstanding.”

      Continuing, I said, “So, when you look at progress in C2C, as a leader, you must ask a series of questions:

      • What drove the change?

      • Did we change the policies with our customers, resulting in a change in DOR, or did we make the terms longer with our suppliers, increasing DOP? Or did we make improvements in inventory (DOI)?

      • How have these three elements changed over time?”

      Joe agreed, “The answer could be one, any, or even all of them. I see how a compound metric might make it hard to compare one company to another, because they could be getting a similar result for very different reasons!”

      “Yes,” I said. “For example, we found that the most common driver of cash-to-cash improvements was lengthening the days of payables and paying suppliers later.”

      Joe rubbed his hands and smiled, and said, “That sounds familiar. It worked for one quarter before it caught up with us. This is a difficult discussion to have with our financial team. When the push for cash is on, it sounds so simple to increase payables; but, I know that we end up eating it when our operating margin rises a couple of quarters after the change.”

      “Another compound metric is the ‘perfect order.’ Do you use this for customer service?” I asked.

      “We tried it a couple of years ago, but dropped it because it was too hard,” Joe said.

      I continued, “I understand. This metric lacks an industry-standard definition, and varies from company to company, but many companies try to use it. The most common definition is based on an equation using three metrics.”

      I wrote on his whiteboard:

      I spun around and continued, “Similar to the cash-to-cash discussion, if there is a change in the perfect order, the answer is not obvious. Instead, companies have to ask:

      • What drove the change?

      • How have these three elements changed over time?

      • What affected the performance in the three components of this metric over time?

      As a result, companies should use caution in using compound metrics and absolute numbers. Compound numbers can drive the wrong conclusions and absolute numbers do not allow the level of comparison needed for benchmarking between companies.”

      Joe was now pacing. “So much to learn. So much to do. How do we get started?” he asked.

      Benchmarking Companies over Time

      “There are many ways that we could work together,” I said. “The methodology doesn't just apply to the benchmarking the whole company. It can also yield valuable insights at a finer, more granular level by benchmarking divisions. In our work with clients, we find that segmentation of the business by division, and by geographies within the company, yields valuable insights. When we do this more detailed analysis – analyzing divisional and geographic data – the concepts are more quickly grasped by the team.”

Then, I showed him an example of this type of analysis as illustrated in Figure 1.6.

Figure 1.6 Example of an Orbit Chart Comparing Two Businesses within a Corporation on Inventory Turns versus Operating Margin

      Source: Supply Chain Insights LLC, Corporate Annual Reports 2001–2012 from One Source.

      “See, Joe, in this example, the patterns of the two divisions of this company are very clear. Division 1 is operating at a higher potential and making year-over-year improvement, while Division 2 is struggling to make clear headway. The use of root-cause analysis to discover the ‘why’ can help the organization drive continuous improvement and maximize the potential of Division 2 on the Effective Frontier,” I said.

      Joe then said, “I love it. I would like to talk to you about doing this type of analysis

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