Building a Stronger Intelligent Automation CoE

You have heard all the formulas of success to build an effective enterprise CoE, “Build a CoE in six simple steps”, “top 5 key considerations”, “CoE can be done in three phases”, etc. Let’s be honest, most of those were picked up at a leading software convention and bolstered by setting up an environment for just their software to end-of-life pattern. Shall I mention there was no other competition involved? What is better than having a little healthy competition, than to have an infrastructure to support any “affordable” technologies at your disposable. You can navigate those waterways and at the same time have multiple tools in your toolbelt, but at the end of the day, you may be left filling multiple roles in support of that elusive Enterprise CoE. What a client may gather in a roundabout way with conversations with vendors/software companies on how to build an effective CoE is not as simple as it seems. Why is that?

1. Companies are consolidated to meet outrageous RPA/ML timelines set forth by pre-existing implementations in other technologies. Whether those windows are 2 months to 6 months. The bottom line, it’s a completely different industry and needs to not be measured against others. Including those BPM implementation conducted many years ago.

2. Internal company political landscape. If I had a dollar every time a company downplayed the idea that intelligent automation or digital automation CoE should reside under another reorg structure to form a subset practice that naturally does not sound like it belongs to, I wouldn’t have to list political landscape at all. Now it’s just time to just come to terms that there are too many ownership games being played behind closed doors.

3. The industry is laden by stiff competition and overcommitments to win contracts. At the end of the day, “vendors” under-deliver and walk away 50k week revenue stream for the duration of the contract and leave the client with “outsourcing is the best approach to get your cost down”.

4. We can do this “on our own” to beat out marginalize the rate cards from internal recruiting or vendor RFP process. You’re playing the money game and if you’re not budgeting it now, you’re are wanting to make the commitments to building a CoE the right way.

5. Have we defined the role or roles successfully for this CoE endeavor? Time is the bargaining factor here and sometimes has to be determined with more errors due to budgetary constraints.

6. Our previous App Management structure is a bit clunky. Will the CoE adopt the necessary infrastructure and technology given we would like to include this in our digital automation landscape. Whether the present org is federated, decentralized or centralized

CoE is not as simple as all the bigger “guys” consultancy/software companies are making it out to be. How do you build an effective intelligent automation practice and incorporate an ever-diverse emerging technologies landscape?

According to Kai-Mation IntelliKM Report “Building an Automation Program”, top clients that have a sense of urgency to put a CoE in place are 4 times as likely to fail or give up efforts within the first year. Furthermore, not having the right individual in place makes it 3 times more likely to fail in the first year. Which has proven many reasonings, but there are four during CoE(s) that stand out the most:

1. “The company” or “competitor” has an 8-month automation maturity roadmap in place. Time crunch has put us behind the competitive competition hype cycle.

2. Scarce resources for each business unit create a complex level of competition in the organization. This leads to dramatic changes in the political landscape and longer drawn-out timelines for implementing a CoE.

3. My personal favorite, by the time we have this in place “we have invested too much time and money to take on the adoption of new emerging technology”.

4. We have a current challenge in RPA positioning. We have one technology that sits between the front office and BPM, but we are looking at another RPA tool that will tackle our productivity and access entitlements challenges.

RPA expertise is valuable to a growing and/or mature organization. The respected client of the stage should eventually move towards the creation of an IA or Digital Center of Excellence (RPA Group) that collects and distributes both the accumulate experience but shares the components (including process libraries) across future discovery and deployments within the organization.