Benchmarking is the best way to explain performance gaps in B2B industrial services and find out what actions to take. Here’s how to go about it.
Most large industrial companies today operate many local or regional (after-sales) service units. And every month or quarter they look at the results and compare the businesses with each other across a range of financial or operational indicators -or benchmarks. What they usually find is a Pareto distribution in performance (e.g. 20% of the businesses account for 80% of the profits, or, inversely, 20% of the units create 80% of the problems) and significant variation across the indicators. This picture usually persists over time, often despite management efforts to effect some change or improvement. In reality, it is usually easier to get well-performing units to do even better than poorly performing units to improve towards the average. And the variation exists even though these businesses are under one central management, support the same products, follow similar strategies and adhere to the same operating procedures. And if we would compare service units of different companies in the same general industries (e.g. machine builders) we would find similar persistent variability -whether the comparisons were on the aggregate (e.g. the global service business of company A compared to the global service business of company B) or at any level below that, for example at regional, local, business area/unit or product level). Some parameters would vary more than others, for instance, profitability would range from very low or negative to very high.
What drives this variability and why does it persist? In most cases, managers do not really know (if they did the phenomenon would not exist). And looking at indicators may create problem awareness but does very little to help with problem resolution. A symptom may have many causes, but benchmarks do not usually reveal which one. And if the cause is unknown little can be done to remove it. Furthermore, if the causes of the variability were simple or common to all, they could be easily addressed, and managements could just copy-paste the solutions. But, again, the fact is they are not, in spite of companies being in the same or similar business, in the same industry or, even, under the same central management. Looking at benchmarks is therefore not enough. To get results this must be backed by benchmarking.
A benchmarking study of a group of industrial service businesses could, if the objective were to understand differences in profitability, involve four stages:
The first stage consists of a comparative analysis of the strategic choices and structural setup of the businesses: Questions, among others, would include how a company conducts its business (e.g. directly or through dealers and service partners); What is the setup of the business (e.g. field services, workshops, site contracts) and its geographic coverage; What is the scope of the business (e.g. narrow (own installed base only), or broad (competitor and other products); What is the range of its offerings (from traditional spares and repairs to more advanced services); What is its spare parts distribution model; and so forth.
The second stage compares and analyzes key (local, regional global -as the case may be) market conditions such as the density of the legacy installed base, the local competitive structure and intensity or the available engineering support (e.g. existence of own local engineering centers).
The third stage homes in on operations and compares and analyses critical performance factors, such as how robust is its pricing, how strong are its customer relationships and how effective and efficient are its primary (e.g. field service) and support (overhead) processes.
And having determined the gaps, the fourth stage is about closing them. This can be done through analysis by managers in workshop sessions or helped along by big data analytics looking at thousands of service transaction records to find patterns of good or poor contextual performance. A powerful analytics tool could also test whether different changes within or outside of given contextual settings, for example in the composition of field service teams, their training or seniority, their locations or levels of support available would make a difference.
Obviously not all stages need to be repeated at the same intervals. Stage one and two may be conducted every 2-3 years while stages three and four every year or twice a year, depending on the degree of automation built into the process and the effort needed to get it done.
As service (incl. servitization and Product-as-a-Service offerings) moves to the center of corporate strategies and business models, accounting for a larger share of revenues and becoming an engine for growth for many companies in industrial B2B sectors it is crucial that company managements get a better understanding of what drives performance and variability. In contrast to product businesses where product specifications, features, and supply chain (incl. manufacturing) decisions are, to a large extent, set centrally and fix a large part of the cost-performance matrix over time -leaving fewer degrees of freedom to execution- the situation in service is different. Execution plays, in fact, a very significant role in determining overall performance. Therefore, having a good grasp of what is causing execution gaps and how to close them is critical.
Benchmarking is about making comparative observations (within and outside one’s own industry and market), analyzing them and drawing appropriate conclusions about what to change or improve and how to do it. In business practice, it goes back a long way. It became formalized and very popular as a management tool through its inclusion in the Malcolm Baldridge Award criteria (the world’s foremost operational performance and quality award at the time) in the late 1980s. According to a regular survey of management tools, by Bain & Company, it rightfully remains one of the world’s favorite and most effective management tools. Still, many managers today understand benchmarking to be an exercise in comparing metrics, indicators and operating statistics and though that may be part of the process (provided data have been prepared in a way to make them comparable -not a trivial exercise-), it is not, as we have seen, what it is really about. Benchmarking is a process of discovery (through observation), analysis, and innovative adaptation of practices and processes as well as their outcomes. It is done in order to understand and explain the relative merits of ways of doing things and find new ones. To an extent, it is now inherently baked into product company practices. For example, many manufacturers will take apart (reverse engineer) competitive products to understand their features, design engineering, materials, and cost-performance ratio. They will derive their supply chains with high granularity. And as manufacturing processes and equipment are usually procured and fairly standardized, they don’t usually pose a mystery for competitors. Furthermore, competitive on- and offline marketing and sales activities can be easily monitored. In industrial service business, however, this is much less the case. For instance, there is a paucity of published data on service operations or performance. Companies must generally rely on hearsay from customers or reports of questionable quality from consultants. Top managements, as well as service managers, are left without anchor information on their relative performance in the market -which makes resource allocation, investment decisions, even designing incentives difficult and arbitrary. Most of all however it leaves them with limited understanding of what really drives performance or how to improve -not only incrementally, but also radically.
The drawback of benchmarking is the relative effort and time required. Nevertheless, this can be much reduced if the process is standardized or modularized, shared among participants in benchmarking groups, partly automated with analytics tools and built into the overall management process.
Legends in Benchmarking and Adaptive Innovation
Henry Ford, the founder of Ford Motor Company, reportedly observed how workers in slaughterhouses after doing their jobs gave a shove to the carcass hanging from a monorail to send it to the next station. This sparked the idea for the assembly line.
Eliji Toyoda, Toyota’s most famous CEO, observed how American grocers in the 1950s stocked their stores at night just in time for customers in the morning. That gave him the idea for Toyota’s Just-in-Time production system.
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