During my tenure at a software consultancy organization, I was part of a team that consulted for a nonprofit organization running a small t-shirt and bag manufacturing factory. The organization employed rehabilitated sex workers (who had been forced into the sex trade), trained them, and offered them an opportunity to earn a living. The organization wanted us to evaluate if a technology solution could help with their operations and manufacturing pipeline. We spent a day learning about each step of their process and talking to the women working in each section of the factory.

I clearly recall one of the problems that they brought to our attention. The bag production process involved many steps. It started with receiving bales of cloth, which then had to be cut based on the orders required. Once the bags had gone through stitching, quality checks, and printing, they would all be packed into batches of 50 bags. Another group of workers would count each pack and if there was a mismatch, the batch would be flagged. However, the workers who were packing bags in each batch were a group of older women. They didn't have the skills or the strength to handle any of the key tailoring activities, but the nonprofit organization wanted to help them to make a living. So, this part of the process (counting bags and putting them into boxes) was thought to be the most suitable for these women.

A key problem here was that the women were uneducated and didn't know how to count! So, every once in a while, a batch had a couple of bags over or under the specified count. Now, to identify these irregular batches someone had to recount every bag! The organization had tried to train these women to count, but it can be quite hard to learn when you're over 60 years of age. It was also demoralizing for the older women that someone had to re-do what they had already done. Solving the bag counting bottleneck was becoming tricky. No matter how fast the team went in the manufacturing process, the last step was slowing down the organization when it was trying to pack and ship orders on time. The organization wanted us to suggest a digital solution to this (along with the other bottlenecks they were facing elsewhere in their processes).

We recommended a simple solution: we asked the organization to try putting together a sample reference batch, with 50 bags, and had the team weigh it. Once the weight was noted, we asked them to try weighing every batch that was counted, and verified by the older women against this weight just before packing. This was a faster process, and the organization could now easily separate the batches with too many or too few bags and fix those only. The younger women, who packed the cartons with finished batches, could do this check, and it wouldn't delay them much. Now, I don't know whether they pursued this approach or not, but it did open their minds to the possibility that they could look for alternate approaches to solving problems.

If our team hadn't known the context behind the organization, we may have suggested replacing the bag counting team with better-educated women or finding alternative digital solutions to this. Even a simple counting ticker could have been proposed, but given how hard it was to train the women, and knowing that the organization's prime goal was rehabilitation, we suggested the simplest thing to address the issue at hand.

In our pursuit for optimizing everything, we tend to forget that people are central to what we do. The internal dynamics of how our teams work determine how well we can collaboratively contribute value. Setting up a process and then forcing people to follow it is usually ineffective. It is also ineffective to set up a process once and assume that we're set for life. People and context should drive processes. Also, processes need to evolve as people do and as the context changes.

What actions we take at the initial stages of a product life cycle cannot be the same as what we do once the product is live and has a thriving consumer base. Internal motivations, needs, and maybe even culture, all drive how teams work and co-ordinate with others. However, process wastes can weigh heavily on our ability to deliver product value.

As mentioned at the start of the chapter, at a broad level, there are three reasons why process wastes (activities that consume our resources, but create no value for the customers) creep in: striving for perfection, striving for efficiency, and striving to maximize throughput. Strangely, these goals don't seem like bad things to strive for. Yet, they can be quite counterproductive to how we build and launch products.