Chapter 4 Wading in the Value Stream

Articulating the Value Stream

In lean manufacturing, an organization’s value stream is comprised of all activities undertaken to provide value to the customer. Activities include everything from developing the concept of a product to its design, engineering, manufacturing, and delivery.

As we’ve discussed, the value stream in a lean enterprise includes both value-added activities (for example, assembling part of a car) and non-value-added activities (for example, forklifting parts across a warehouse floor). The objective of lean is to eliminate as many of the non-value-added processes as possible (some are necessary) and to optimize the efficiency of the value-added activities, while maintaining the established value to the customer.

The value being produced should never be adversely affected by process optimization, the elimination of activities, or other improvements. Destroying real value is more wasteful than eliminating inefficient time, money, or raw resources utilization. An organization may or may not be better off becoming more efficient through elimination of waste independent of its effect on value creation. The latter may be the goal in some organizations, but it isn’t lean.

In the context of a lean startup, in which the production and delivery of value hasn’t been proven, you don’t truly know either the value being created or for whom it’s being created. You may think you know. You may believe what’s between your ears; you may have faith in your idea and your abilities, but until you’ve successfully conducted transactions whereby customers have paid some currency for the value you’ve produced, you don’t actually know.

This is why we say that, no matter what your startup endeavor is, your job is to discover the value, for whom it’s being created, and whether there’s a large enough market to support the business you envision.

This is true in large organizations as well as startups. If you are working on known problems with known solutions, you are likely making incremental improvements to your products, some based on true innovation. This is fine and good and is necessary to compete against your known competition. It won’t protect you against disruption, however. For that, you must foray into the unknown, into disruptive innovation.

If history teaches us anything, it’s that for your startup to succeed, or your existing business to flourish, you must be willing to experiment and fail in search of the right combination of problem, product, and market that results in big success.

Fundamental changes will occur in your thinking between concept and delivery. Your early assumptions will likely be proven wrong. This is true of all types of businesses that face uncertainty. There’s nothing wrong with that—embrace it. Go ahead; we’ll wait.

Case Study: Seeing from Customer’s View

When Sight Machine founder Nathan Oostendorp set out to disrupt the $2 billion machine-vision industry, he assumed his solution would require a massive amount of hardware: cameras, mounts, brackets, and black-box appliances. Machine vision is a quality-control process whereby camera sensor equipment is deployed across a factory floor and image analysis is used to ensure that automated manufacturing lines are producing high-quality parts or product.

The existing practice typically required custom solutions for each customer and required massive amounts of professional services. Nathan’s vision was to create a platform that customers could “order like they were purchasing a Dell computer. We provide you all the pieces and then we put them together to do very specific things.” The value proposition was to dramatically lower the total cost of ownership of deploying and maintaining a machine-vision system, through lowering the costs of hardware, integration, and customization. The system could be installed “by anyone with an Allen wrench.”

The trade-off would be flexibility. Once installed, the setup is difficult to modify. Sight Machine’s choice to pursue this model was driven by the pain of the current high-price model and the assumption that customers didn’t really want to have anything to do with the system itself. In Nathan’s words, “We thought people didn’t want to have to deal with the technology and so we were developing appliances that would process images into data, compare the data to given parameters, and then do something with the data, like trigger a light or send an alert.”

As they were developing the platform, Sight Machine conducted pilot programs with early customers. But because the product was not ready for primetime, it required a lot of manual installation. It was this customer interaction that changed their perspective on what customers really needed.

“So when we actually started interacting customers with the technology we found that they were actually curious about the technology. We had to bring the operation of it even closer to them.” In other words, flexibility was as much the driving factor as lowering the total cost of ownership. Customers wanted to be able to move the cameras and mount them in challenging environments, as well as create their own tests in the software. In other words, they wanted the flexibility of the high-cost, services-based model—but they wanted to be able to implement, manage, and customize the system themselves.

“Today, our goal is to show up in a van—like the Geek Squad—with a bunch of hardware in the back and mount a camera and have vision systems set up on the first visit. Unlike the way it works right now where you maybe have a four- to six-week lead time for all of your equipment; we really make it so that anyone can get something up and running very fast.”