As businesses prepare themselves for a post COVID-19 world, we are seeing increasing focus on acceleration of automation in Corporate Services by business leaders. This isn’t surprising as leading companies look to make 25-40 percent savings in the manually intensive parts of their captive organisations and re-focus the human effort on driving business value.
But whilst the intention is strong, organisations are having to navigate through challenges such as unprecedented levels of disruption, resource constraints and change fatigue that increases the risk of ‘value leakage’ when investing in automation initiatives.
Here are 5 key considerations that business leaders should be thinking about to unlock future value from technology.
1. Don’t start with the technology…start with the (right) business problem
This may come as a shock to many but quite often automation initiatives get initiated because of heavy interest in a particular type of technology enablement such as RPA or Machine Learning rather than focusing on the business challenge that needs resolving. Our recent survey with HFS of 900 executives shows that fewer than 30 percent have seen tangible value from investments in digital technologies.
Digital technologies including automation, analytics and AI have matured and are easier to use than ever before. This introduces an opportunity to accelerate adoption and generate value but only when the ‘right problem’ is selected. For example, a client in the healthcare sector had to rapidly onboard in excess of 4000 staff as a result of shifting demands from COVID-19. In just two weeks, KPMG stood up an app to manage the onboarding and deployment of these 4,000+ members of staff, leveraging Microsoft Power Platform technology on Azure.
Keep in mind that the technology is just one part of the solution, not the whole solution, so spending more time on understanding the problem enables formulating a solution that also addresses equally important areas such as process/data standardisation, user experience, capability gaps, and new ways of working.
2. Establish a digital mindset across the enterprise
The organisations who drive significant incremental value, foster a mindset to re-imagine digital solutions that augment their workforce with analytics, AI and automation, leveraging the untapped potential of new data and new operating models. This requires adopting a test and learn approach from ideation through the launch of digital solutions. It also means thinking of the customer first, embracing uncertainty and innovating with agility through established agile methodologies.
The right mindset does not mean tactical upskilling initiatives at the operational level but a scaled and top-down shift in the way business problems are tackled across the organisation. Appointing a digital champion at the C-Suite level and establishing an Automation Centre of Excellence (CoE) are some examples of how leading organisations are scaling the transition.
3. Create and manage value streams
In a recent delivery of a finance strategy programme for a global healthcare manufacturer, the finance leaders reported that they had already implemented RPA on a number of their finance processes. However, they also provided feedback that these initiatives felt tactical and there was no clear way to track the qualitative and quantitative benefits that were being generated. Quite often, automation solutions only look at specific functional processes and do not consider wider enterprise implications. It is worth adding that value isn't only financial, measures such as Process Velocity and Efficiency, Employee Productivity, Customer Satisfaction etc. should also be considered. In fact, we find that the KPIs established by leading companies for automation projects also look at important aspects such as employee/customer engagement, behavioural shift and upskilled workforce.
Leading organisations are now establishing value streams, typically through a Centre of Excellence capability, which would consist of qualifying business problems against strategic objectives and developing hypotheses around sources of value through a cross functional and end to end process lens.
Once established, these value streams will need to be managed through enablers such as:
- Strong governance model
- Change control processes
- Agreed KPIs and subsequent MI reporting
4. Get the data right
Data is the fuel for any digital solution and making sure that you get the highest possible return on your data assets across the data value chain - from creation to commercialisation - is key to digital success. Return on investment can be maximised by having a value led approach to data initiatives, agile data delivery methods and a robust data governance model in place.