Looking for the next evolution of lean? Look back.
Many have achieved great success with lean – it’s all over the web. Companies have done 5S, standard work, value stream mapping, and flow-pull-perfection. Waste in value streams has reduced from 95% to 80%, which is magical; productivity gains have been excellent; and costs have dropped dramatically. But the question on everyone’s mind – what’s next? The blogs, articles, and papers are speculating on the question and proposing theories, all of which have merit. But I think we’re asking the wrong question.
Instead of looking forward for the next evolution of lean, we should look back. We must take a fundamental, base-level look at our factories, and ask what did we miss? We must de-evolve our thinking about our factories, and break down their DNA – like mapping the factory genome.
Though lean has achieved radical success, it has not achieved fundamental reduction in factory complexity. Heresy? Let me explain. Lean helped us migrate from batch building to single piece flow. With batch building, a group of parts are processed at machine A, then, when all are finished, the whole family moves to machine B. With single piece flow, a part is processed at machine A then she moves, without her sisters, directly to machine B, resulting in big savings. But in both cases, the fundamental part flow, a surrogate for factory complexity, remains unchanged – parts move from machine A to machine B. Lean did not change it. Lean has taken the bends out of our factory flow and squeezed machines together, but that’s continuous improvement. We’ve got good signals, we’ve got cell-based metrics, and 15 minute pitches. Again, continuous improvement. But what about discontinuous improvement? How can we fundamentally reduce factory complexity?
Factories are what they are because of the parts flowing through them.
Factory flow and complexity are governed by the genetics of the parts. In that way, parts are the building blocks of the factory genome. From the machines and tools to the people, handling equipment, and the incoming power – they’re all shaped by the parts’ genetics. Heavy parts, heavy duty cranes; complex parts, complex flows; big parts, big factories. When we want to make a fundamental change in bacteria to make a vaccine, we change the genetics. When we want to make a fruit immune to a natural enemy or resistant to cold of an unnatural habitat, we change the genetics. So, it follows, if fundamental change in factory complexity is the objective, the factory genome should change.
Don’t try to simplify the factory directly, change the parts to let the factory simplify itself.
Discontinuous reduction of factory complexity is the result of something – changing the products that flow through the factory. Only design engineers can do that. Only design engineers can eliminate features on the design so machine B is not required. Only design engineers can redesign the product to eliminate the part altogether – no more need for machine A or B. In both cases, the design engineer did what lean could not.
Lean is a powerful tool, and I’m an advocate. But we missed an important part of the lean family. We drove right by. We had the chance to engage the design community in lean, but we did not. Let’s get in the car, drive back to the design community, and pick them up. We’ll tell them anything they want to hear, just as long as they get in the car. Then, as fast as we can, we’ll drive them to the lean pool party. Because as Darwin knew, diversity is powerful, powerful enough to mutate lean into a strain that can help us survive in the future.
The next area of lean breakthrough is where it should have been all the time…
1st – Demand Management – Without fail the supply chain suffers from lack of clear, meaningful, and timely consumer and industrial demand information… shipping to releases is not demand… it simply pushes inventory forward. EOQ and similar thinking has caused the glut of inventory as it sits waiting for demand. Now that inventory has been depleted by the massive shutdown of plants across industry, now we are retooling with the same mindless thinking and I fear that lean tools haven’t been adequate to the task in demand management. When tiered-suppliers are ask about the nature of demand their customers experience that drives orders to them they are nearly all clueless. Optimizing supply without improved knowledge and transparency of demand information is folly. Yet we do it without question.
2nd – Product Performance Feedback – I recently attended a working session with a leading design technology provider and suggested that warranty information, failure information, maintenance information, customer satisfaction feedback, et al. needed to make its way back to the design engineer. The company informed me that I was 7 years ahead of industry thinking. What???? Ask Toyota engineering if they think this would have been useful in their accelerators and braking systems! Designing products that create value of the life of the product requires integrated market feedback… yet like demand information, constipation of essential product performance data remains the bane of industry. So now we have plants shut down as demand falls off the map for Toyota because products were designed that severely impacted forecasted demand. But that’s okay… demand wasn’t forecasted and communicated usefully (refer to first point).
We can’t 5S, Six Sigma, or Kaizen event our way out of these fundamental flaws in our supply chain practices… one-piece flow to supply (inventory) waiting for demand just doesn’t appear like progress to me.
This post was mentioned on Twitter by mwalsh: Overlapping philosophy w #leanstartup – nice. RT @MikeShipulski: The next evolution of lean http://ow.ly/18tL4…
A lot of the complexity we see in factories stems directly from designs which are not manufacturing friendly. One of the best things that an organization can do is ensure process engineers are on the team that defines the DFMEA. The process engineer’s feedback is critical in designing parts that are easy to manufacture with high quality and no complexity.