Every day, in every warehouse and distribution center, managers must answer questions about performance. For example, "We're missing our target for percent of orders shipped error-free. How do we increase that number?" or "We haven't shipped a perfect order in six months. What should we focus on to improve?"
To solve problems like these, we typically consider mapping the current process, implementing lean principles, and working to continuously improve processes. Once a solution has been implemented, we use metrics to benchmark our results against prior performance and that of the best performers.
Metrics explain how effective our efforts are in achieving organizational goals. When used appropriately, they can help us to prevent disasters, correct problems, and ensure we are going in the right direction.
For this reason, companies should be very careful about what metrics they employ. In theory, the metrics they utilize should be based on the overall corporate strategy, and those metrics should provide feedback as to how well a function is supporting the overall goals of the organization.
Reality, however, often differs greatly from theory. Our research indicates that there is a widespread problem in the industry: Operational metrics do not seem to be connected to corporate strategy. We base this belief on five years of data gathered from the "DC Measures Study" we conduct with the Warehousing Education and Research Council (WERC) and DC Velocity, sister publication to CSCMP's Supply Chain Quarterly. This research, which we have conducted for more than a decade, studies operational metrics in distribution centers and warehouses.
Recently we became interested in several questions: Are operational metrics in respondents' companies aligned with corporate strategy? Could we tell a company's strategy by the metrics it used? And is there agreement on which metrics matter for a specific strategy? To find out the answers, we combined the 2,467 respondents who participated in the survey over the past five years into a single data set, from which we extracted only those who had answered all of the questions about strategy and metrics. This gave us a pool of more than 420 respondents.
We then analyzed their answers to those survey questions. Our analysis found that there is a disconnect between what managers measure at the operational level and their organization's corporate strategy. In other words, strategy has little to do with what is being measured and what is thought to be important at the operational level.
In this article, we will first outline the four main business strategies commonly adopted by companies today, and then will look at the research findings that led us to the above conclusion. We'll also give a brief summary of a five-step process that can help logistics and supply chain managers bring metrics and strategy into alignment.
The four general strategies
Strategy determines our competitive approach to the market, answering the question, "How are we going to compete?" Strategy determines the services we will provide, at what level those services will be delivered, and what types of customers we will serve. It defines the policies that will be used and how resources will be allocated. Ultimately, a company's strategy determines how it will make critical decisions to differentiate itself in the market.
A strategy's overall role is to provide guidance for the entire organization in setting priorities and goals for the key areas of products, services, the customer experience, and costs, fine-tuned for the market segment the company wishes to serve. What makes strategies differ from each other is their primary emphasis: examples include keeping costs under control, providing great customer service, or differentiating themselves from competitors in some way. The choice of strategy should require different operational methods to execute the goals of the organization.
In our DC Measures Study, we asked respondents to identify which of four generic strategies their company pursued. These are based on the strategies that Harvard Business School professor Michael Porter described in his 1980 book, Competitive Strategy. In the book, Porter focuses on three generic strategies companies can use to compete in the marketplace: cost leadership, customer service, and innovation/quality. He also identified a fourth possibility, a combination of strategies he referred to as "stuck in the middle."
Most of us are familiar with the first strategy, cost leadership. In this case, the primary driver in the purchasing decision is the price of the goods sold. Therefore, reducing and eliminating costs is absolutely critical. For distribution and warehousing, decisions about such things as automation, site selection, training, and process improvements would be driven by the cost and the offset of new or additional costs. Metrics such as distribution costs as a percent of sales and inventory turns are related to costs. Southwest Airlines and Wal-Mart Stores are examples of companies that historically have competed based on a cost leadership strategy.
The second strategy Porter identified is customer service. In this case, the primary goal is to satisfy customer requirements, ideally in such a way that customers will be willing to pay a slightly higher price for a product or service because of the value of the customer experience. Metrics that focus on internal processes that have the highest impact on customers, such as order fill rates, accuracy, and on-time shipments, are related to customer service. The Ritz-Carlton, FedEx, and Starbucks are examples of companies that compete on the basis of a customer service strategy.
The third strategy Porter discusses is innovation/quality. Using this strategy, companies offer a product or service that is so compelling that customers are willing to pay a higher price for it compared to competing offerings. Because these products or services are by nature unique, they typically require speed to market to maintain or capture market share, saturating the market as quickly as possible to gain brand awareness before competitors can copy their new product offering. Metrics that measure time, such as "dock-to-stock" cycle time, days in inventory, or percent of supplier orders received on time, would be typical key performance indicators (KPIs) for innovation and quality. In the high-tech manufacturing industry, Apple, Google, and Samsung are examples of companies that are utilizing, in a generic sense, an innovation/quality strategy.
The fourth strategy, which Porter termed "stuck in the middle," is what we call "mix—be all things to all people." In this case, a company tries to do everything well. Porter wrote that this strategy would not be successful because the other three strategies would be more effective in finding profitable niches to serve, and that it "possesses no competitive advantage."1 When Porter wrote Competitive Strategy 30 years ago, he observed that in most industries, many companies were "stuck in the middle." It appears not much has changed. While it was the most frequently cited strategy in four of the last five years in our survey, the "mix" strategy has begun to decline in popularity, perhaps due to the difficulty of successfully executing it.
A review of survey participants' responses regarding which strategy their company uses can be found in Figure 1.
Theory meets the real world
In most companies, senior management is responsible for developing corporate strategy and then communicating it throughout the organization. However, if the strategy is not communicated or understood in a way that helps employees to implement it at the operational level, results will be mixed at best.
Once an organization identifies the strategy it will follow, the operational functions should be aligned to support and achieve the objectives set forth by that strategy. At least, that is what theory—as well as academics, consultants, and leading-edge firms—would suggest. However, responses to our DC Measures Study show that companies are not putting this theory into practice.
The annual DC Measures Study is a survey of prior-year performance on 45 key operational metrics for warehouses and distribution centers that have been identified by practitioners over the past 13 years. The study asks practitioners to provide information about their facilities' prior-year performance for each of the 45 metrics that they actually use to assess performance. The metrics that receive the greatest number of responses are deemed to be the top measures. We identify the overall top 12 metrics in use each year.
The 45 operational metrics are divided into five categories, plus two additional groups focused on the perfect order and cash-to-cash cycle time. The five categories are customer, operations (inbound and outbound), capacity/quality, financial, and employee/safety.
In addition to reporting performance, respondents are asked to answer basic demographic questions, such as industry, operations, strategy, customers, sales, and geographic location. For the analysis described in this article, this data was segmented by each of the four strategies, and the most frequently used metrics were identified for each strategy. Further analysis was completed to determine if the differences noted were statistically significant.
Prior to analyzing our data, we formed three hypotheses. All three were built around the expectation that the data would support the theory that a company's decisions about which metrics to track would be influenced by its overall corporate strategy.
Our first hypothesis was that each strategy would have a metrics profile that was different from the others. For instance, respondents employing a cost strategy would utilize a different set of measures than a company that is focused on innovation/quality. This makes sense because there will be different expectations, costs, and outcomes associated with operationally supporting each strategy. Yet in comparing the sets of metrics for the four strategies, we found more similarities than differences. In fact, the top 10 metrics utilized within each strategy were basically the same, as illustrated in Figure 2.
Our second hypothesis was that firms employing the same strategy would utilize a similar subset of metrics that is unique to that strategy. In other words, a specific strategy would dictate the use of a subset of measures directly related to that strategy. For example, a cost leadership strategy would use more cost metrics, whereas a customer service strategy would utilize more customer-focused metrics. We expected there to be some variation within each strategy; after all, even within a market segment there are different niches to be served. However, we believed there would be agreement on what the top metrics were.
First, though, we had to define "agreement." What percentage of the respondents would have to utilize a particular metric for us to be able to say it was core to the strategy? We chose two thresholds: 70 percent and 60 percent. If 70 percent or more of the respondents for a specific strategy used the metric in question, then we considered it to be core to that strategy. Because there are different niches being served, as well as differences among industries, we set a secondary level of agreement at 60 percent.
Except for those respondents whose companies are using a cost leadership strategy, there seems to be disagreement as to which metrics are key within a strategy. In the case of cost leadership, 70 percent of the measures were used by at least 70 percent of the respondents who identified cost leadership as their company's chosen strategy. This is in stark contrast to the customer service and mix strategies, where only 20 percent of the measures were agreed on by at least 70 percent of the respondents who identified the customer service and mix strategies as their firm's primary focus. Moreover, only four measures were agreed on by 70 percent or more of the respondents utilizing an innovation/quality strategy, and just four measures met the minimum threshold of 60 percent, leaving this strategy's "Top 10" list of measures two short. This lack of agreement as to what measures should be employed for a particular strategy was unexpected.
In summary, we found few differences in the metrics for different strategies; each of the strategies essentially used the same subset of measures. This finding led to our third hypothesis: that respondents' level of performance on similar metrics would be statistically different for each strategy. We wondered if the differences among strategies could be discerned based on overall performance—not on which measure was used, but on the actual outcome of using that measure. Would, for example, respondents using a customer service strategy perform better (have better outcomes) on a particular metric than those respondents using a cost or innovation strategy?
And that is exactly what we found—but only for a single measure: internal order cycle time. For all of the other measures, there were no statistically significant differences in performance based on strategy.
In the one instance noted above, respondents employing the innovation/quality strategy performed more than twice as well on internal order cycle time as did all of the firms using other strategies. This result was not surprising when you consider that, as noted earlier, companies with an innovation-based strategy typically focus on speed in order to maintain their competitive advantage.
Our data set reveals that first, there is not a lot of agreement within a strategy group on what are the important metrics to use, and second, that there is no difference between strategy groups in their lists of the most important metrics—both of which are the opposite of what you would expect. It seems that regardless of strategy, most logistics organizations are not differentiating their performance on the basis of the metrics they utilize to manage their operations or compare themselves with others in the industry. Managers would be hard-pressed to find where strategic choices have made operational differences in the DC.
Unfortunately, that's not what we and others have taught, or what we all thought was being implemented in companies across the globe. It appears much work still needs to be done in this area.
Building a "House of Metrics"
We believe that understanding a company's overall strategy and ensuring that metrics are aligned to that strategy is the foundation from which to build a performance management program. It's also the foundation for communicating how the logistics and supply chain functions provide value to the company while enabling the successful execution of the strategy. In fact, metrics are tools for communicating to our employees and upper management (and sometimes to our supply chain partners) what is important and what are acceptable levels of performance.
In our view, logistics and supply chain professionals should have a set of performance metrics that is appropriate to their company's chosen strategy. You can think of this as a "House of Metrics" (see Figure 3) that should be built upon the foundation of one of the four strategies—cost leadership, customer service, innovation/quality, or "be all things to all people." The strategy your company employs will determine the mix of metrics to be used within each pillar, or category, of the house.
For those companies with metrics that are not aligned to their overall general strategy, we recommend following the five-step "Validating the Value-Add" (VVA) process. This process is a simple way to ensure that the metrics you are using in your operation are aligned with strategy and are driving the desired results. It is designed to help logistics and supply chain professionals complete the following statement: We add value by supporting our company's strategy. We do this by_______. (Note: "Validating the Value-Add" is trademarked by TSquared Logistics.)
Here is a brief summary of the five steps:
Step 1. Clearly articulate the objective(s) to be met. Companies should first determine their strategy and desired outcomes. Then, those objectives must be clearly articulated and communicated so that the operational levels of the organization can align their actions to the strategy. For example, a firm following a customer service strategy might communicate an objective like "We will achieve a 10 percent improvement in shipping accurate orders in order to maintain our competitive advantage in customer service." This statement clearly links operational and functional tactics back to the overall strategy. Follow up with your people to be sure they understand not only the corporate strategy but also what their role is in helping to carry out that strategy and its related objectives.
Step 2. Develop Validating the Value-Add statements. VVA statements define how an individual employee, an area within a warehouse or DC (for example, receiving and inspection, pick and pack, or slotting), and a department or functional area of a company (logistics, supply chain, marketing and sales, manufacturing, corporate real estate, accounting, or finance) adds value in achieving the related objectives of the company's overall strategy. To validate the value that the employee, area within a warehouse facility, and department or functional area adds, it's necessary to establish a performance goal to measure against.
Here's an example. If the strategic objective is "achieve 12 percent revenue growth," then all employees within the DC should understand how the work they do or the decisions they make support that objective. Suppose the company wants to increase revenue by filling customer orders faster than its competitors do, which will bring in more business from new and existing customers. Instead of filling orders in two days, the DC will need to pick, pack, and ship orders within 12 hours of receiving the order. In this instance a VVA statement would be "We support revenue growth by picking and shipping 96 percent of our orders within 12 hours." Clearly linking a tactical measure to a broader objective in this way will help employees understand what to focus on in their operational activities.
Step 3. Measure the progress. This step is designed to help employees easily understand and track their performance against the benchmark. Once clear expectations have been articulated and the team understands the value that the activity it performs brings to the organization, then it is imperative to measure progress against the overall objective in addition to the team's or department's progress against its own goals. Make it easy to see that goals are indeed being met by summarizing data so that the results are obvious. Also, be sure to include historical data to track trends.
Research in Total Quality Management (TQM) suggests that employees who understand and can see their progress continually search for ways to improve and beat their best performance. This taps into the intrinsic motivation (pride in work, internal initiative) in a workforce. Employees who work under this management approach significantly outperform employees who need extrinsic motivation (external rewards).
Step 4. Find the underlying problem. What do you do if you are not meeting your goal? Establish a process for conducting a root-cause analysis that will allow you to determine the reasons for failing to meet the goal, and then develop corrective action plans that will keep the problem from recurring. For example, in a situation like those you'd likely encounter in a warehouse or DC, a Pareto chart (sometimes referred to as an "80/20" chart) could be used to list, in descending order, the most frequent sources of problems in a process, customer complaints, or defects. Because it identifies the most frequent or most common sources of problems, the Pareto chart will show you where to focus corrective efforts.
However, the obvious problem usually is not the actual root cause, and the team will have to drill down to find the underlying reasons for the failure. A good technique is to ask "Why?" five times, a technique originally developed by the Toyota Production System. Following the trail of questions can lead you to the ultimate source of a problem. For example, suppose we've missed our goal for on-time shipments. Why? Well, the orders were late getting to the shipping dock. Why were the orders late to the shipping dock? The product wasn't available to be picked. Why wasn't it available to pick? Because we didn't have any product in replenishment. Why was the product not in replenishment? Because it was still on the receiving dock. Why was it on the receiving dock? Because the supplier was late shipping the product to us.
Step 5. Take action to fix the problem. Identifying a problem, though, doesn't mean it will go away; you've only highlighted a need for change. Communicate that need for change, and how those changes align to the corporate strategy. It's important to stress that the process needs to be changed, and not necessarily the people. (But do bring in employees who truly understand the problem and its root cause to help craft action plans to fix it.)
Keep the goal in mind, and communicate regularly about progress toward that goal. This can be done with something as simple as keeping charts or reports visible by placing them on bulletin boards in the workplace. Finally, and importantly, praise your co-workers' progress when their actions lead to the needed change.
Making strategy matter
One thing that has remained consistent as we conducted our research over the past decade is companies' high level of interest in benchmarking their performance on various metrics. They all want to compare themselves to best-in-class performers and see where they stand.
But even when the data was segmented by industry, size of firm, or strategy, we saw few differences in actual levels of performance on each metric. Now we know why: there is a core set of measures that most companies use, regardless of strategy, company size, or industry. Beyond this narrow band of metrics there is little agreement as to what measures support a specific strategy.
While conducting this analysis, we uncovered a number of questions that we have not been able to answer yet. Some relate to the research itself. How do we explain our results? Could it be that strategy doesn't matter in the management of distribution networks? We don't think so. Is it possible that so few companies are linking strategy and metrics that their results are diminished when averaged in with everyone else? Or could it be that our survey questions aren't capturing the nuances that are necessary to get a clear answer? Perhaps.
Other questions reflect broader business management issues. For example, over the long term, our concern is that the failure to align metrics with strategy may undermine a company's ability to achieve its strategic goals and objectives. Executing a strategy is not as clean, neat, or easy as articulating that strategy; does this perhaps lead to muddled messaging when it comes to metrics? We believe that a lack of discipline in how a strategy is executed leads to a hazy understanding of which metrics to use and which to improve.
Here's another question. Most companies say that their employees are a factor in their success or are a competitive advantage. In addition, a scan of any industry publication or conference agenda confirms that there is a lot of concern in the industry about talent. Yet only the cost leadership strategy included an employee-related metric among its top metrics. Why have companies yet to translate that concern into a top priority inside their performance measurement systems?
Similarly, respondents using a cost leadership strategy were the only ones to include a financial metric in their Top 10 list. Given how much companies focus on costs and margin pressures these days, we expected financial metrics would receive greater emphasis among the respondents regardless of their companies' strategy. This was all the more surprising because firms typically use financial metrics to determine the success of their strategic initiatives.
Our research to date clearly indicates that today's warehouses and distribution centers are disconnected from their company's overall strategy. Can that gap be closed? It is possible, of course, to improve an organization's execution of a chosen strategy. More work needs to be done if we are to better understand not just how companies are aligning their internal processes and measuring performance, but also how logistics and supply chain organizations could apply that information to better support their companies' business strategy.
1. Michael Porter, Competitive Strategy: Techniques for Analyzing Industries and Competitors (New York: The Free Press, 1980), 16.
The objective in developing and conducting the DC Measures Study is to help companies eradicate bad warehousing practices. Each January, the survey is launched via an e-mail invitation to members of the Warehousing Education and Research Council (WERC) and readers of DC Velocity, a sister publication to CSCMP's Supply Chain Quarterly. Survey participants are asked to report their actual levels of performance from the prior year against 45 key operational metrics that are relevant to most distribution center professionals. The measures have been grouped into balanced sets—customer, operational, financial, capacity/quality, and employee/safety—plus two additional sets related to "perfect order" and cash-to-cash cycle measurement.