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Using Centres of Excellence Teams to Drive Intelligent Automation Strategies
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It’s an exciting time to be thinking about automation! According to Deloitte’s third annual RPA survey, 53% of respondents are beginning their RPA journey. Gartner’s 2019 CIO Survey found that 37% of firms out of 3,000 global CIOs surveyed are implementing artificial intelligence in some form.
If your organisation is new to the idea of automation; it doesn’t mean every person has to be a tech expert to pull off one of the most ambitious technology projects. And even seasoned veterans can still refresh their project approach behind the tech stack. A Centre of Excellence (CoE) can be built inside your organisation dedicated to delivering and upgrading automation.
Intelligent automation strategies are starting to become more and more common. But scaling up automation inside businesses is a challenge. In the same Deloitte RPA survey, only 3% of organisations have scaled to 50 or more RPA robots. Mickinsey’s global online survey has reported that while 47%of their 2,000 respondents are using AI, only 30% of those are using it across more than one business function.
To help increase these later figures, Kofax has created a six-competency model for scaling intelligent automation using a CoE. We advise bringing a set of teams together to focus on these. One team handles one competency, each:
- Program leadership and vision
- Vendor and IT relations
- Platform enablement
- Human capital and transition planning
- Programme reporting
- Knowledge, Management and Continual Improvement
Read on to see where your workers can fit and contribute!
Program Leadership and Vision Teams
The purpose of the project leadership team is to oversee the Centre of Excellence and act as a liaison between other internal departments. Don’t discount the value of company-wide communication when large change happens!
Each department’s senior staff probably has a lot of questions on what introducing automation means for their day-to-day work. When you look at each team as interconnected, it makes sense to include multiple parties in the execution of your intelligent automation strategy.
One example is having your program leadership and vision team plan with your internal audit team. The internal audit team should also work closely with operations. Internal auditors would need to make sure that internal audit standards are embedded in the operations-side of any automation programme and that it’s communicated clearly to ops.
In turn, the Operations Team lead would likely need to speak to your company’s IT department to make sure that IT stakeholders know what’s the operational reach of the automation strategy. This is also to ensure that there won’t be any duplicated efforts between automated tasks and problems that IT or in-house software developers are currently working on.
Program and leadership teams in an intelligent automation programme usually take the form of steering committees. Regular meetings are encouraged so that the committee can track and manage the project and activate any internal stakeholders.
Teams Centred on Automation Vendors and IT Relations
You would also need to manage your relationship with your Intelligent Automation vendor(s). A list of what this means is to QA your process:
- Tracking vendor software updates
- Troubleshooting problems by coordinating with vendor support personnel
- Negotiating discounts and licensing
- Looking for alternative vendors if your intelligent automation strategy starts to “outgrow” their offerings.
Internally, you should speak with your IT team about whether the automation software will run on a dedicated or shared server. You should also ask your IT team who will be monitoring the automation software so that it doesn’t become overloaded. Who in the IT team will notify if they see that there is any user-abuse.
Tread delicately on any IT discussion. IT is one of the most important departments that would need to be on-boarded with automation.
Automation Platform Enablement Teams
Platform enablement is admittedly a general sounding strategy. All-in-all it’s creating enablement assets to support the adoption and proliferation of an automation strategy. But what is an enablement asset? Some examples..
If you are designing the automation software internally, you need to think about how your robots designers will be trained to develop the software within a centralised standard. One of the difficulties is that while automation software (particularly RPA ) thinks in User Interfaces, most IT workers are more familiar solving problems via APIs (application programming interfaces).
Platform enablement also goes for the more technical details. What third-party applications does your organisations use? Can your automation platform integrate with them? This is an especially important question if you are planning on using the Artificial Intelligence or cognitive computing aspects of Intelligent Automation.
Human Capital and Transition Planning
Bring a worker-centric feel to intelligent automation. Your challenge is to make sure that your staff doesn’t buy into the “robots are going to take our jobs” narrative.
The first step is identification. Do a brainstorm, take notes, and record which areas of the business you feel will be most impacted by automation. Then have a think about how you can frame automation into an empowering opportunity for your current and future staff’s career development. For your end, it would mean:
- planning for role changes
- considering the impact for your organisation’s future hiring practices I.e. what new skills and job responsibilities needed for job ads
- Closing the skills gap that automation will bring to the workforce
The most successful intelligent automation adopters do not solely count their success on “highest as possible!” straight-through processing metrics. Nor do they only focus on how a new automation programme can reduce headcount and payroll. This doesn’t mean you *shouldn't* embrace the new areas of work capacity that digital transformation could bring you. It means when considering transition planning, you should minimise as much (alleged) collateral damage as you can in your human capital.
Taking quarterly or annual re-assessments? you need to take accurate quantifiable stock to see if your new automation tools are meeting expectations. Monitor the impact that automation is driving.
The metrics you choose will of course effect what your reports will look like. Key performance indicators and problem indicators (with baselines and benchmarks!) can build a cohesive story for your data. Knowing how and when a metric is considered “matured” with your business can also set expectations before analysis.
One framework that can be used is “Total Automation Yield”(TAY). There is no hard and fast equation for TAY. Instead, Total Automation Yield is a function of 4 impact assessments: finance, operations, workforce and strategic impact.
Each assessment would be a mixture of both qualitative and quantitative factors with their own metrics. The task for your data analysts is to create a methodology where each of these assessments can be woven into something that indicates automation success/failure.
Program reporting is not just used for justifying and expanding investment in automation. It is also a powerful tool of information for further human capital and enablement initiatives. When a metric shows growth, feel free to announce it to the rest of the business. This would encourage more positive thinking on the impact that intelligent automation has on the organisation.
Knowledge Management and Continual Improvements
Designing and implementing automation is not a one-time deal. Automation vendors routinely come out with new quarterly releases. You may adopt other new software/server packages along the way that would require some robot re-programming.
In the long-term, new business procedures can crop-up out of need. Keeping up with new software releases will require new testing, QA and deployment best practices. New manuals and codes will also need to be drawn up so that that newly implemented/updated software doesn’t conflict with pre-existing models being used in other departments. Never underestimate the havoc that a poorly managed overlap can cause!
Automation strategies have the potential to become a routine and permanent feature in your organisation. Creating a Centre of Excellence around these 6 specialties* will help breakdown important expert silos. At the end of the implementation process, you can expect that the CoE ‘s results create a more consistent experience for all that will be impacted by automation.
*Once again, the specialties are: Programme Leadership; Vendor & IT Relations; Platform Enablement; Human Capital and Transitions; Programme Reporting; and Knowledge Management).
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