As more manufacturers dive into business-process analysis and modernization efforts, many are quickly realizing they have accumulated a great deal of process debt—inefficiencies, waste and redundancies that have collected in their workflows over time.
Not to be confused with the better known term “technical debt,” which refers to legacy code, outdated design elements, and lingering bugs, process debt is primarily the product of patchwork fixes. Typically accrued when inefficient (yet seemingly convenient) workarounds have been applied to processes, process debt results from a lack of commitment to continuous-process improvement. It does, however, have one thing in common with technical debt: both lead to inefficiencies, inflated costs, and a marked decrease in quality.
While many experts contend that automation represents the best way to eliminate process debt, automation is, in fact, a major contributor to process debt. This is due, in part, to the fact that many manufacturers treat automation as a “set it and forget it” technology. In the rush to automate and realize the lofty returns automation promised, they failed to optimize their processes before automating them or, even worse, we see cases in which automated processes that should have never been automated, due to their high complexity or low utilization. Managers then left the automation to do its work without ever revisiting it to determine efficiency or where strategic fixes might be needed.
Process debt also can result from employee turnover. When process owners or employees who built the automations leave the company, the process knowledge they possess often walks out the door with them. This can result in new employees building the same automations that already exist (or at least portions of those automations), since no one has a full understanding of the company’s complete automation estate.
Regardless of the cause, the consequences of such actions can be staggering, and can include:
· Automating processes that don’t need to be automated
· Not optimizing a process before automating it
· Not factoring maintenance costs into successful criteria
· Not properly evaluating the cost of the automation upfront
· Not aligning processes to the company’s strategic goals
By most estimates, 20-30% of the average organization’s automated-process landscape is redundant. And bottom line, redundancies, waste and workarounds cost manufacturers money. One company I recently encountered was spending $1 million to maintain, support, and operate one of their automated processes. That same process, however, was generating only about $300,000 in business value. With that kind of money on the line, it’s easy to understand why manufacturers want to rid themselves of process debt. The question is how?
Logically, the first step for manufacturers to take in eliminating process debt is capturing and documenting what their arsenal of processes currently contains. Clearly, it is impossible to analyze the effectiveness of existing business processes and identify where redundancies and inefficiencies exist (as well as how best to remove them) if there is not a complete accounting of the processes being used.
With that information in hand, manufacturers will be able to better understand what is happening in each process before determining whether it makes sense to automate it. So if cost-reduction and increased efficiency via higher quality and fewer errors is the objective, processes can often be improved without automation, saving both cost and resources.
Anecdotally speaking, three-quarters of all process improvement does not involve automation. Given that, it is essential for manufacturers to quantify the value of their processes before determining the best process-improvement strategy to pursue. For example, automation might decrease execution time on a specific process by 80%. If there are only 10 inputs to that process per day, though, the ROI realized by automating the process would likely be negligible because the output remains the same whether it is executed manually or by a bot.
To analyze the value of their automation portfolio, manufacturers increasingly are turning to a value-mapping assessment to see precisely what automations they have, how complex those automations are, and where redundancies exist. Whether performed using internal or outsourced resources to audit all automations currently in production, value-mapping enables manufacturers to understand:
· What automated processes are in the company’s estate
· Where hidden and structural deficiencies exist in the automation design
· What opportunities exist to optimize existing automated processes, reuse process components, re-platform automations to another RPA tool to lower operational costs and enable scale, or retire redundant processes that create maintenance problems and deliver marginal value
At a more granular level, a value-map assessment performed on individual processes can reveal where there are:
· Redundancies in a process as a result of indiscriminately copying automation components (a common practice for companies that use automation anywhere for RPA design, deployment, and orchestration)
· Reuse opportunities by analyzing Metabot usage and efficiency across an entire automation estate
· Orphaned processes or process components across the automation estate
By taking these steps, manufacturers can vastly reduce (if not completely eliminate) process debt, enabling them to increase efficiencies, reduce costs, and increase quality.
Tony Higgins is chief product officer with Blueprint Software Systems