Process Doc Opportunity #3: Parallel vs. Sequential Processing
Reducing Cycle Time by Improving Teamwork and Coordination
The fastest relay team in the world can run 400 yards in less than 37 seconds. Four people running next to each other can run a collective 400 yards in less than 10 seconds.
Of course, the purpose of a relay race is for the team to run in sequence. In business, the goal is to deliver value to your customers as quickly and cost-effectively as possible. Sequential processing is bad for both business outcomes. Parallel processing, when possible, can save time and cost.
In 2020, the world got a giant example of sequential versus parallel processing: Operation Warp Speed. Traditional vaccine development takes a lot of time (5-10 years) and money ($500 million on average). Due to the low success rate of potential vaccines, pharmaceutical companies usually follow a linear sequence of steps, with long pauses for testing and data analysis.
During the early days of the COVID-19 crisis, it was clear the traditional process did not meet the needs of the global emergency. Here is an illustration of the Operation Warp Speed vaccine development process:
The work performed in each step was not reduced, though trial phases were combined. Certain steps were performed simultaneously with shorter breaks between steps. Pharmaceutical companies also prepped for manufacturing before vaccines were approved. This added to the financial risk for each potential vaccine project but given the number of “customers” to serve, it was a risk companies were willing to take.
Regardless of what you think of the post-emergency use of COVID-19 vaccines, Operation Warp Speed was a dramatic example of what is possible when you can move from sequential to parallel processing. In this case, the 5- to 10-year cycle was reduced to 1-2 years.
A more mundane example is the classic IBM Credit story. This is an extreme example of sequential processing driven by task specialization. Similar to a relay race, each “swim lane” performs a series of tasks before passing the baton to the next player in a different lane. This workflow is not necessarily bad but it is always an opportunity to reconsider process design.
In general, there are two ways to improve such a flow. IBM took the dramatic approach of reengineering. They leveraged information technology to enable the consolidation of several different job roles into a generalist position. (Figure 2.) In many cases, it is possible to enable some parallel processing by improving information sharing and streamlining inspection checkpoints. The results could look like Figure 3. In either case, cycle time and handoffs are reduced.
Excessive reliance on task specialization and sequential processing is an opportunity that “jumps off the process map” and is easy to explore during process documentation workshops. Optimizing workflow will help your team win the race!
Next: Process Doc Opportunity #4: Unbalanced Work.