What is Workman's "non-management" that achieves results through data management?

HULFT DAYS2021 was an online event held over two days, November 17th (Wed) and 18th (Thu), 2021, with the theme "Information Evolves into Knowledge - Towards the Future." On the second day, the 18th, Tetsuo Tsuchiya, Senior Managing Director of Workman Co., Ltd. (hereinafter referred to as "Workman"), a manufacturer and retailer of workwear, took the stage for a keynote speech in which he explained digital transformation strategies based on organizational transformation.

The company is well known for its data management using Excel and its "non-management" of "focusing on the most important goals and doing nothing else." How did these management reforms lead to the development of the outdoor wear market, which is said to be worth 400 billion yen? We spoke to Mr. Tsuchiya about the inside story of the management innovations.

▼Profile of Tetsuo Tsuchiya
Tetsuo Tsuchiya, Executive Managing Director of Workman Co., Ltd. and Professor at Tohoku University
Graduated from the Faculty of Economics at the University of Tokyo. After joining Mitsui & Co., he studied abroad before becoming President of Mitsui & Co. Digital. He served as Deputy General Manager of the Corporate Planning Office at the Head Office and Director of Mitsui Information Systems. He joined Workman in 2012. He became Senior Managing Director in 2019 and a Specially Appointed Professor at Tohoku University in July 2022. As Workman stores are on the verge of dominating the workwear market, he launched a new store format, "WORKMAN Plus," in 2018, which became a huge hit. In 2020, he launched the female-oriented "#Workman Girls" campaign, and in April 2022, he launched the highly anticipated "WORKMAN Shoes," which are currently on a roll. His books include "Workman-Style 'No-Hit Management'" (Diamond Inc.). In December 2021, he published his second book, "White Franchise: Workman's System for Earn Over 10 Million Yen a Year Without Quotas or Overtime" (KADOKAWA).
*Titles and affiliations are those at the time of interview.

Expanding customer base and successfully developing a second blue ocean market with outdoor wear

Since its founding in 1980, Workman has maintained the top position in the workwear market share and has always enjoyed a competitive advantage. However, as a result of expanding its customer base without changing its workwear business model, Workman has now succeeded in cultivating a second blue ocean market for outdoor wear, following workwear. In this presentation, I will explain how Workman was able to cultivate the outdoor wear market.

The reason they decided to develop the outdoor wear market in the first place was because the workwear market was a small industry, and Workman would have exhausted its market share once it reached 1,000 stores and sales of 100 billion yen. Sensing a risk of market saturation, they announced a mid-term business transformation vision in 2014, shifting their policy to expand their customer base from workers to the general public.

With the goal of expanding the customer base, the company had to change its corporate culture in order to ensure stable growth. To achieve this, the company implemented three management reforms: "Creating an employee-centered environment," "Data management," and "Non-management."

"Data Management" and "Non-Data Management" implemented for management reform

First, in "creating an employee-centered environment," we implemented four things: 1) management would not waver in its focus on what it was doing; 2) management would demonstrate its seriousness by offering a base pay increase of 1 million yen over five years; 3) employees would not be put under stress; and 4) time constraints on product development and other areas would be eliminated. Why did we focus on creating such an environment? It was because, in order for our company to maintain a competitive advantage for 100 years, it was necessary for ordinary employees to be able to bring about change through ordinary work. Also, the awareness that we in the management team are just ordinary people also supported the creation of an employee-centered environment.

"Data management" aimed to use data collected on-site to achieve optimal product lineups and supply chain management (SCM), operate new business formats with no prior knowledge, and promote data-based internal communication. A conscious effort was made to change the way the organization is managed. Moving away from the traditional management style in which it was enough to simply ingratiate oneself with superiors, we assumed that the opinions of superiors were half wrong, and defined a good superior as someone who is persuaded by on-site data and changes their opinion. This led to proactive improvements in on-site operations. Furthermore, in promoting DX, we focused on stress-free DX, such as by not setting deadlines for development.

The third concept, "non-management," overlaps with part of data-driven management, but it completely changed the way management is done. Management goals were narrowed down to one, and deadlines for achieving those goals were abolished. Planning accuracy was defined as "management has a 50% chance of being wrong (in decisions about store expansion, etc.)." This is a premise that arose from the fact that we live in an age of VUCA (Volatility, Uncertainty, Complexity), where it is impossible to predict the future. In addition, based on this premise of predictability, we have introduced a new approach to plan execution in which the field verifies and executes plans using data, as well as bottom-up leadership.

Practicing a non-industrial management style and developing blank areas in the apparel market

We have implemented these three corporate transformations, but these are merely means to achieve our business goal of expanding our customer base. Data-driven management and data-driven management are simply means to an end.

The "no-management" approach is positioned as a "positioning strategy" or "focus strategy" that selects markets that will produce results. For example, changing the way work clothes are presented and selling them as outdoor products to a different customer base is a form of positioning, while focusing on one business goal can be considered a focus strategy.

I mentioned specific methods earlier, but a data strategy is about building an organization that is resilient to change based on data. In uncertain times, information is available on the ground. Let's say sales of sporting goods fell due to the COVID-19 pandemic. In this case, it would be effective to reduce the number of sporting goods and examine how sales changed. In other words, it is important for all employees on the ground to think and make reforms based on data.

In the midst of all this, I realized something based on the analysis of my employees. When I created a position map of the apparel market, segmenting it into four categories, with high-price-low price on the vertical axis and design-functionality on the horizontal axis, I noticed that the market in the lower left, which offers excellent functionality and low prices, was blank. I applied my management know-how in not selling to anyone and focused solely on implementing a strategy to expand our customer base. Furthermore, the outdoor wear market, which is the target of this blank market, can be sold to anyone regardless of gender, so it was a win-win situation and there was no competition. This is why we were able to make inroads.

Promoting data management, such as process-focused evaluation and data utilization research

On the other hand, when trying to expand their customer base into the outdoor wear market, how did they proceed with data-driven management? First, they changed their performance evaluation criteria from one that emphasized results to one that emphasized process.

Previously, sales performance evaluations were centered on quantitative measures such as sales, inventory, and gross profit. However, with the promotion of data-based management, we now focus on process evaluations, such as the adoption rate of shelf allocation, which indicates where and how much products are displayed, and the MD (merchandising) ratio of stagnant products that have not been used for a long time. In addition, we have added the extent to which reforms have been implemented to the evaluation indicators. The emphasis is now on the attitude towards the efforts, rather than the results of the reforms.

To improve employees' data utilization skills, we held training sessions on the theme of data utilization. The analysis team training, which targeted approximately 20% of employees, aimed to use simple AI analysis tools and included exercises on BI (business intelligence) and Excel automation, as well as instruction on how to combine Excel functions. As a result of this training, most of the sales staff are now able to process data in Excel. The advanced analysis training course, which is open to 3% of employees, teaches advanced analysis techniques such as unsupervised learning clustering and natural language processing, including word clouds based on text data.

Management staff reductions and base pay increases

By the way, to explain in more detail how we are serious about creating an employee-centered environment, we have made the ability to use data and a mindset for innovation requirements for promotion to managerial positions. Anyone who does not possess these two qualities will not be promoted to department manager or higher. I don't have a say in human resources, but I do have a negative list, such as "this manager doesn't want to use data." However, because it is important to have personnel management that does not create new stress, we did not demote any personnel. We let it go by waiting for the retirement age for positions, etc.

We also worked to reduce the number of management staff. When I joined the company in 2012, there were six executives, but now there are only three. The amount of executive compensation that was cut was used to increase the base pay of employees, resulting in a 1 million yen increase. In other words, data-based management is more about changing corporate distribution than it is about numbers.

Returning to the example of data utilization within the company, we established voluntary data analysis teams in the SV (Supervisor) Department, Product Department, and Logistics Department as part of our data management. As a result, we frequently saw cases where the analysis team promoted the use of convenient tools such as Excel and Python to routine analysis.

A typical example is the "Cannibal Product Discovery Tool" developed by the Product Department. This tool has the function of finding cannibalism (where one of the company's products encroaches on other products), and when you enter a product number, it will list the cannibalized products. Another tool created by the SV Department called "Unintroduced Products" has the function of finding popular products that have not yet been introduced, and is extremely useful for product lineup, which is the SV Department's main job. This tool was created by a very energetic sales person.

Another example of data utilization is the store's fully automated ordering system. Already in its third development phase, this system is equipped with algorithms that use AI to forecast demand, maintain optimal inventory levels, and optimize ordering calculations. By simply pressing a bulk ordering button, ordering time can be reduced from the previous two hours to just five seconds. It also helps prevent stockouts, and stores that have introduced the system have seen a 5-6% increase in sales compared to stores that have not.

Creating a winning position is essential to achieving DX management that will maintain a competitive advantage for 100 years

The key to data management is not just to create a vision, but to instill it throughout the organization. As part of its efforts to instill this vision within the organization, Workman has made a "reform mindset" and "ability to utilize data" prerequisites for executive appointment. As a result, all ambitious employees have started using data. Now, the company president is able to utilize data, having attended training alongside first-year employees.

In the process of spreading data utilization throughout the organization, we undertook a variety of measures. In addition to actively praising data users, we positioned data as the most powerful means of communication, and we continue to do so to this day.

In conclusion, to achieve DX management that will maintain a competitive advantage for 100 years, you need to create a winning position. A winning position means focusing on a business where employees can achieve 120% results when they give 100% effort. In the case of Workman, they changed their business domain from workwear to selling outdoor and sportswear, and as a result were able to win in the market.

Positioning cannot be achieved if you have too many business goals. First, narrow it down to one. Even then, the success rate is probably around 30%. I think it will take another 15 years to achieve the goal.

Additionally, in DX management, it is also important to build a system that allows for on-site data-based decision-making. One example of building a system for validating data is evolving stores to take customer demographics into consideration. Store improvements include installing pink-themed swings in-store and creating shadow puppets using RGB (red, green, blue) light, which has led to an increase in female customers posting on Instagram with the hashtag "#WorkmanGirls."

The key to implementing business strategies is thorough non-management

Finally, just as with data management, the key to executing a business strategy is to decide what not to do and what not to change, and thoroughly implement "non-management." This will encourage employees to take the initiative.

Even so, there are still management issues to be addressed, such as a lack of analysis items, but we plan to continue implementing IT smoothly by running the new database and the old database in parallel.

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