Heijunka in the Service Industry

The Banker’s dilemma.

It’s always desirable to have visibility on upcoming work to plan ahead and optimize resources. That’s why forecasts are so attractive and also dangerous: they’re equal parts trending analysis and wishful thinking [how could a business run with no predictions?].

In the Manufacturing Industry a build-to-stock model can be used to stack-up inventory based on a forecast with the purpose of leveling the load and thus gaining stability in the supply chain [what are the associated risks of a build-to-stock strategy?]. It is less common to find this scenario in the service industry as most of the work is on-demand. Either with the use of a forecasting tool or with solid customer orders at hand it is recommended to use a visual system to organize work.

Heijunka, usually translated as “level loading” is a lean system designed as a strategy to deal with “Mura” (unevenness) caused by demand fluctuation. This concept goes deep but in its basic form it can be described as follows: Sales provides demand, the demand is analyzed by Planning against Operations capacity until agreement is reached (1^st loop); the Heijunka box/board is loaded for a certain time period (shift, day, week) and progress is measured, if the target is not met then Operations adjusts capacity (2^nd loop) or/and the demand is renegotiated (3^rd loop). The loops illustrate how the System learns and adjusts.

Fig1. Heijunka (basic) System flowchart

The Heijunka box/board resides at Operations (or where the job is administrated / happening). A typical arrangement of a Heijunka box looks like a cluster mailbox. The actual set-up and appearance varies widely, depending on the needs of the people using the box, but in its basic form one axis displays the time period and the other the products or services so both the total product/service load and mix are visible for every time slot.

Fig2. Example of a Heijunka box

Heijunka is the best tool I know to organize upcoming work in a Visual Management environment but I’ve always wonder its limits in the service industry. That got me to think in the Banker’s dilemma.

Ideally, requests for service would always come “leveled”: exact amount of work for the exact amount of resources. Picture yourself walking into a bank and the customer before you leaving the cashier window right as you approach and the same occurring for the customer after you. Of course, variation happens and the banker is faced with a dilemma: hiring 6 clerks at the expense of having half of them do nothing during low demand or hiring 2 clerks and make customers wait during peak hours. I believe there are countermeasures that could make any of these approaches manageable. 

Let’s imagine that the banker decides to split the difference and hires 4 clerks. During low demand hours the extra cashiers could flex-out, if properly trained and empowered, to do other value adding activities like assisting Customers on the phone or opening accounts. It is of great importance to properly identify the streams of revenue for the Company so employees don’t get buried under wasteful tasks when flexing [what does their value streams look like?]. During peak hours one countermeasure could be to increase the comfort of the customers on their wait time by offering restful seating, free coffee, climate control or other amenities that ease the pain of been trapped at the bank. Also, another employee, like a walk-around supervisor, could flex-in whenever needed. I’ve seen employees flexing work and comfort increasing tools been partially successful (better if combined) but I will venture that the situation can be furtherly improved by reflecting on Heijunka and its connection to Visual Management.

Let’s rethink the same scenario adding a simple idea: if we could somehow identify the specific service the customer requires beforehand, and make it visible for everybody, it would be easier to balance the load!

For the sake of simplicity, let’s assume the bank reflects deeply on their value creating activities and defines four value streams for its services. To avoid entering in the financial services details, let’s call them A, B, C and D types. Again for simplicity, let’s give types A and B an average completion of 5 minutes, C of 8min and D of 12min. Now let’s install one line for each type of customer to arrive. When there is one customer on each of the lines the total workload would be of 30min. The set-up would look something like this:

Fig3. Hypothetical configuration for the Banker’s dilemma.

An important question here is: if you’re in line for a transaction that should take 5 minutes for how long will you be willing to wait? If you’re not the patient kind, 15min might be close to unacceptable [how could these be confirmed?]. Assuming less than 15min is desirable, let’s analyze some scenarios:

Scenario 1: if all lines have 2 people waiting it might be time to flex-in an extra pair of hands.

Fig4. Demand scenario 1: A=3, B=3, C=3, D=3.

Scenario 2: If line D is empty, C has one Customer in line and A and B have three Customers waiting; it might be time to convert line D to serve customers from either A or B.

Fig5. Demand scenario 2: A=4, B=4, C=2, D=0.

In the same scenario, what would be the wisest think to do if also c=4? When would it be time to flex-out an employee? What could the signal be? These situations and more can be easily simulated with real people during a lean transformation. Once the system gets optimized, better comfort tools can be planned to enhance the Customer experience.

Finally, the Lean Sigma practitioners familiarized with Heijunka might wonder where the Heijunka box is. Like those giant chess boards played with real people, you can imagine the Customers entering each line position themselves inside a square of the Heijunka box. As time advances, picture the squares been cancelled until the clock runs out for the day.

Fig6. Heijunka box view of the Banker’s dilemma.

This reflection can be extended to any Customer facing business (like Supermarkets or Hospitals). It also provides an extreme case of the use of Heijunka that challenges the general belief that this tool can only be applied to certain environments (like Manufacturing). It proves to me that when dealing with true Lean Sigma tools, because they’re grounded on sound principles, the limits of their applications are the limits of our own creativity.