In part one of this series we discussed bridging the corporate generation gap with automation. This void is created as baby boomers retire in waves, leaving companies with skill gaps in critical areas. As these businesses struggle to gather and analyze the information needed to train new generations of employees, essential knowledge is often lost in translation, miscommunicated or left out altogether as the result of human bias.
Today, we will discuss another equally problematic issue related to accuracy in business process discovery – relying exclusively on the subject matter expert (SME). The SME’s understanding of context as it relates to business process execution is critical to defining the current state of any process. The SME is such a bedrock of process discovery that companies are hard pressed to find solution integrators, software OEMs or consulting firms that don’t base their planning on these experts. Looking at it from the provider’s point of view it’s an easy decision – SMEs are:
- Trusted as a highly-invested source of customer representation
- Accessible, engaged and experienced communicators
- Fast – Sourcing data and requirements from an SME is faster than outsourcing
- An economical solution
So why does this decades-old, readily accepted practice often fail to produce accurate process documentation? Why do solution providers build-in rework estimates to fix errors when requirements are so well defined? First, consider the problem of human bias covered in part one. The SME is no less vulnerable to this issue than anyone else, but the strengths of SMEs listed above should reduce the likelihood of human bias. This is especially true when combined with consistent communication and the use of standardized best practices. Yet the problem remains: projects reach user acceptance testing (or launch) with missing or incomplete functionality and unexpected behavior. So how can we break this cycle while maintaining the speed and cost efficiency of SME-based process discovery?
To ensure success, the scope of process discovery should be expanded beyond the SME. The SME’s knowledge remains crucial, but should be used as a starting point rather than the final word. This knowledge forms a baseline for establishing common execution paths – how business usually gets done. End-users can then be engaged as a source of validation for these paths. It sounds great – but who has the time or funding, much less the ability, to engage the entire workforce directly? That’s where crowdsourcing comes into play.
Crowdsourcing isn’t exactly a new strategy – companies have used this approach to brainstorm ideas and develop innovative new strategies for decades. Recently, the Enterpriser Project published an article about how one IT leader used crowdsourcing to achieve 100 wins in his first 100 days as CIO (Spoiler alert, he surpassed that goal). Crowdsourcing is popular across industries because it allows organizations to transparently leverage the wisdom of the crowd. It also helps establish good rapport with employees because it shows their expertise and ideas are valued. So how can companies implement this approach to eliminate human bias in business process discovery?
Using the latest automation technology, businesses now have the ability to capture the exact steps taken by all users to complete their daily tasks. These “captures” can then be compared against an SME baseline, providing accuracy in aggregate. By gathering captures at scale, human bias is reduced and a better picture of how and why business processes are working (or not working) emerges. This allows organizations to confirm common practices and identify previously unexplored process paths. Armed with this new information, analysts and consultants can ask targeted, informed questions to clarify the reasons for process variation. To learn more about how this type of automation works, take a look at this overview of Process Mining technology.
Do you have any thoughts on how crowdsourcing can benefit your organization? Drop us on a note on Twitter to let us know!