Over the past year we’ve seen a significant shift in market as organizations deal with two conflicting realities:
- The underlying technology of intelligent automation (IA) is a proven commodity precluding the need for pilots and proofs-of-concept (POC)
- The vast majority of IA programs have been predicated on pilots and POCs that have failed to deliver any meaningful value.
This has led to the next logical question – If small projects deliver limited value, can scaled deployments deliver scaled value?
Scaling an intelligent automation program continues to be a topic of intense focus in the market. The analyst community frequently cites problems with scaling as being one of the biggest concerns for enterprises wishing to increase the impact of their program. But as with many things involved in setting up an automation program, the absence of a strategy can make scale hard to come by.
The most common approach we see (and it’s only an approach not a strategy) is to look to define scale in terms of the number of bots deployed and the number of technologies employed. This addresses only one aspect of scale.
A less common, but far more impactful approach is to define scale in terms of the value delivered to the organization from automation. While the metric is more complex (“value” vs number of bots), this approach forces a rigor around truly transforming processes, addresses the impact on jobs and workforce, and brings a discipline to the deployment of technology.
If your strategy includes the goal of “transforming” the work being done, you must decide whether you plan to do the same work with a different mix of labor, (the basis of most outsourcing arrangements) or if you are open to finding new ways to perform the work to effectuate the desired outcomes. The implications of what kind of “transformation” you are seeking are clearly different.
In the same way, your strategy should be clear on what you mean by achieving success through scale. One mode, typically driven by focusing on the number of bots, might lead to an approach that scales by rapidly spreading across the entirety of the organization. This ‘wide’ approach to scale has some benefits – but can be quite limited and will not help realize the more profound benefits that can be derived from reimagining processes and functions to take full advantage of automated capabilities, and ignores that scale can be both horizontal (wide) and vertical (deep).
During early planning phases, you must consider whether you would rather have automation at a basic level across the entire set of workstreams, (wide) or if you would prefer to capture all of the available opportunity in a given business area (deep)? You would likely expect that the answer is both, but that ignores that the approach to achieving each type of scale can differ, and is driven by your definition of transformation.
“Transformation” means more than just changing the mix of labor. Following the 3 D’s of Intelligent Automation as a guide, we can see where the approach to each type of scale can be different.
The 3 D’s...
- Decompose - breaking down the processes to be automated and building them back up with an eye toward efficiency and an “automation-first” design ethic.
- Digitize - identifying the right tool to move the work in question from delivery by a human-based workforce to a virtual-based (or blended) workforce that requires digital input.
- Deliver - working with all the stakeholders to design and deliver an orchestration of service between the virtual and digital workforces to improve performance across the targeted measures.
Here’s a quick look at wide vs. deep scaling:
- Moves rapidly across the business
- Evaluates current processes against defined automation criteria
- Releases fractional capacity back to the business
- Supports an agile model and incremental functionality
- Focuses on specific processes within designated areas of the business
- Takes a deep dive into data requirements
- Consolidates how automation can be deployed to achieve the desired outcome while further enhancing process performance
- Requires significant investment in design to enable automation development
Further, as design of future state processes will require corresponding changes to associated jobs and organizational constructs, a deep approach will more closely resemble a BPO or Shared Service transition where careful attention needs to be paid to the organizational transformation and how work transitions from the current state to the future state. As a result, the benefits associated with the new automated process often go well beyond capacity released to realized savings through tangible cost reduction and measurable impacts in process performance (compliance, service levels, etc.). The implication of affecting change at this level is that success cannot be measured at “go-live” and significant effort should be invested in the workforce transformation and the measurement and realization of benefits.
Overall there is value to be derived from both approaches and trade-offs associated with each. The wide approach allows you to move quickly, deliver quick wins, and in many cases minimize initial investment, but the overall value may not be at the level anticipated. Further, there is a risk that the automation impairs future process transformations.
The deep approach will take longer and require capabilities beyond automation implementation, but the value delivered can be orders of magnitude greater.
As you consider your own automation programs it’s crucial to understand your overall objectives and the business challenges you are looking to solve, so you can develop a strategy that is appropriately aligned. In our next blog, we’ll discuss how a focus on “quick wins” can lead to an approach that runs counter to a larger organizational objective to deliver fundamental change.
This is the first blog in a 4-part blog and video series entitled: Automation at Scale: Diagnose, Decompose, Digitize, Deliver... Discuss. Ready for more? You can read the second post, Beware the Quick Win Syndrome here.