Digitalization, robotization and artificial intelligence have become business buzzwords, frequently brought up during conferences and board meetings. How does the reality of a modern enterprise look? Are companies ready to embrace the potential presented by new intelligent technologies?
Two years after our first exclusive interview with Professor Willcocks of London School of Economics and Political Science, one of the most respected experts in the field of knowledge work automation, Digital Workforce had the opportunity to reunite with him, this time in London. Reflecting on what has changed over the past two years and looking ahead at the future of RPA (Robotic Process Automation) and other intelligent technologies, the discussion tackled some burning challenges companies face when implementing these solutions, how they currently stand with regards to knowledge work automation and how they should measure success.
How far have we gotten over the past two years in terms of technology and how managers see RPA?
RPA has gotten a much higher profile than it had two years ago, the technology has to some extent improved, in the sense of being more enterprise reliable than before. There are different, more sophisticated and highly customizable tools available now, solutions that are more scalable than others, but the underlying technology has not changed that much.
Business people have looked at RPA and realized they have to invest in it, due to its potential economic value. However, all managers have not come to this realization at once – we have observed three distinctive waves, implementing the technologies due to different motives. The first wave was a rather limited amount of relatively mature businesses who saw the value of RPA right up front. The second wave came in 2016, when a larger number of companies started investing heavily in process automation. Finally, the third wave started in early 2017, induced by heavily intensified marketing activities of RPA solution providers, and this enhanced visibility has been since than pushing companies to board the RPA train as well.
“RPA used to be sold as a “quick win”, easily adoptable and relatively cheap tool that would give you cost savings and a quick ROI – but people have now started to realize that it is rather a strategic weapon.” – Professor Leslie Willcocks of the LSE
Moreover, some risks have emerged that were not obvious two years ago. With regards to the main challenges RPA brings to businesses, only about 25% are directly related to technologies. The remaining 75% is about not managing it as a strategic project. Companies tend to neglect aspects such as good governance, quickly available resources, getting the C-suite on board, treating it as both a change management as well as a technical issue. There is a large number of steps the management should take and action principles that should be followed in order to reduce these risks.
What do you see as the major challenge for companies implementing knowledge work automation?
For sure, the biggest challenge is that companies are still not treating this strategically enough. They underestimate what they can achieve with it – something called a triple win, consisting of enhanced shareholder value, customer value and employee value. Their ambitions oftentimes do not aim high enough.
In the case of RPA – they are partially stuck with looking at it as a tactical tool rather than a strategic weapon, as a discrete tool rather than a potential uniting platform, as a software implementation and not as a change in the work processes. Ultimately, companies often miss on the real business value with RPA projects by this mistake. Looking for a quick ROI and hard business numbers to prove the added value while not factoring in that the main benefits might be unanticipated, such as improved customer experience and working morale of the employees, is the biggest mistake many modern enterprises make.
On top of that, cognitive automation has not yet taken off and is still at a promising, relatively immature stage. Some firms are implementing discrete uses of cognitive automation, which bring them real business value and progress. It seems so that the true synergies will arise from linking RPA with cognitive automation, eventually creating a platform that integrates seamlessly with other digital technologies in place.
Is this strategic approach towards RPA a necessary step on the way towards the implementation of cognitive automation and platform building?
Indeed, where RPA rests within the organization signals whether the company sees it as strategic or not. If you create a centralized center of excellence and you have senior executives involved in it, it is pretty clearly of a strategic interest. On the other hand, if you treat it as a lower level tool that you would apply increasingly across the organization, it seems to be more of a tactical approach without a sense of direction. The potential of RPA in relationship to cognitive automation is immense and the different automation technologies should be recognized as complementary pieces of a whole.
What is the most exciting development that you have seen in this field recently?
Lots of the cognitive automation technologies are truly exciting, carrying a massive promise. Once companies start combining them, they can get to an impressive level of automation, almost end-to-end in some cases, pushing the potential uses of the increasingly available technologies further.
Do you think that the organizational maturity is not necessarily there yet?
Mostly, the maturity of organizations with regards to their ability to absorb this level of change is not high enough yet. Companies are absorbed with way too many other IT problems and issues related to managing operations. This leaves them in a place where they are not ready to absorb even more technological change. As a result, learning to integrate the new advanced solutions is being postponed because people are still learning how to fit the previous ones into their businesses and to drive business value out of them.
How do you think the success of RPA and these first AI activities should be measured?
In some ways, measuring this presents the same problems as evaluating a success of an IT investment. There are some obvious costs and service improvement measures – you can reduce costs while offering a much superior service, the degree to which the automation does that is one of them. There is also a range of softer yet crucial benefits – such as customer experience that could be expressed by a plenty of measures. Especially in regulated industries, these solutions could help the companies to quickly and accurately comply with the imposed regulations, providing relatively cheap trial opportunities, compared to how would the companies do it without automation. Another set of metrics could revolve around employees – level of satisfaction, of morale, of productivity with machines as opposed to productivity without them and what the human beings bring to that combination. Last but not least, metrics around the level of innovation are also interesting – is the company innovating more in products and services?
What do you expect to happen in the upcoming two years?
I would expect to see a lot more RPA use-cases showing how they fit with cognitive automation, bringing lots of business value. Additionally, cognitive tools would improve on certain fronts – not the machine learning or the algorithms behind them, these are already advanced. Rather, image and data processing together with natural language processing is going to improve greatly, integrating the enhanced productivity and performance.
Leslie Willcocks, a professor of London School of Economics and Political Science, is considered one of the world’s most respected researchers, speakers and business publications writers in the field of knowledge work automation.
Professor Willcocks held the closing keynote at this year’s Blue Prism World event in London. You can check out the highlights of his speech titled “Robotic process automation 2018: Now, Soon, Later” here.