Digital Transformation » Technology » Digital transformation: moving beyond the expectation gap to the cutting edge

Robotic Process Automation (RPA). Artificial Intelligence (AI). Cognitive Processing. Advanced Analytics. These and other next-generation digital technologies are highly touted these days, with the promise of lower costs, fewer staff, improved effectiveness, smarter and more strategic business decision-making, and enhanced customer experience.

Despite the hype, the potential is definitely real. Smart automation and broader digital transformation offer a radical shift in how companies operate, and the benefits they can generate. The latest research from The Hackett Group finds that companies can cut finance costs by over 40% through comprehensive digital transformation, including full technology optimisation. With less time spent focusing on transaction-oriented activities, staff can shift to work that creates greater value – such as driving innovation, improving agility, identifying and avoiding risks, finding new opportunities, and improving the customer experience.

And the findings are similar in procurement, HR, IT, and other back office, or business services, areas.  Digital transformation can bring operational cost levels down to below those of top-performing “world-class” organisations in these areas, based on The Hackett Group’s extensive benchmarking work.

Corporate aspirations and actual adoption rates

The reality is that most finance teams have significant smart automation and digital transformation aspirations, and almost every company is doing something. But most have barely dipped their toes in the water. There’s a tremendous “expectation gap” between corporate aspirations in digital transformation and actual adoption rates. Perhaps they’ve run RPA pilot programs to try and automate more labour intensive transactional activities. But many have plateaued there, creating “islands of excellence” that have not yet been standardised or rolled out more broadly, generating only limited benefits. Few are using these technologies to significantly impact end-to-end processes.

The potential and the benefits are there, and business units across organisations are jumping in with both feet, as the winners and finalists in The Hackett Group’s Digital Awards demonstrate. Vodafone has revolutionised its procurement operation with automation and AI, training hundreds of users across the company to use data visualisation tools to spot trends, and using RPA to simplify tasks. They’ve cut procurement costs by about 20 percent, and virtually all their purchase orders are perfect (less than 75 percent were before). Shell has created an analytics network of 1,600 people who can now optimise the ordering of spare parts, delivering millions of pounds in savings. They are also using machine learning to predict failures in compressors, valves, and other equipment. IBM is relying on its new Cognitive Support Platform to manage support for more than 7,000 products across 170 countries, prioritising cases, managing workload, and in some cases using chatbots to resolve issues via self-service.

What’s holding finance teams back, when comprehensive digital transformation can deliver such impressive gains? One issue is certainly confusion. Finance teams simply don’t know where to start. Also, this is a new technology area, and momentum is still building. Finding staff with the appropriate skill set can be challenging, and companies must manage competing priorities. Careful planning is required, as well as discipline, expertise, and insight. Opportunity assessment is also key, as some processes and issues are much easier to address with digital transformation than others. In addition, since digital transformation often involves the integration of technology from multiple vendors, it’s more challenging to create a “shopping list.” It’s not as straightforward as picking a single large technology vendor and moving forward.

Scaling up is hard for many finance organisations. In part it’s because discipline, expertise, and insight are required to navigate the three major trends here, which require new and very different skill sets. Automation is built on process reengineering and transformation practices. Analytics is based on data and statistics disciplines. And AI requires skills at the cutting edge of computer science. To put together an innovative digital project, technology and disciplines from across AI, analytics and automation may be required. It is this combination that we see as driving disruption, innovation and impact.

Value from digital

Progress is being made, but it’s slow in coming. Digital is a process, and companies are slowly discovering how to extract value from these new technologies. The initial focus has been on operational environments with high-volume transactions, and also on customer-facing applications. But RPA, data capture, and other technologies are now maturing, and companies are starting to explore their use in other areas, like risk management, fraud identification, and more accurate forecasting of things like commodity pricing. This is a powerful shift, because it moves beyond eliminating transactional work, and enables companies to make smarter decisions, improve cash flow, manage risk, and streamline their supply chain.

What are the greatest lessons learned from companies leading the charge towards digital transformation? From the outset, companies should treat digital transformation as a comprehensive change initiative, with a business case and a detailed plan for implementing at scale. There must be real partnership between IT and the business, and integration with existing IT systems. In many cases business units try to “go rogue” and do this on their own, then end up encountering organisational IT issues that prevent broader rollouts. Vendor selection must be done cautiously, as many of the leading smart automation vendors, like Blue Prism, UiPath, and Automation Anywhere, were recently small companies, and are now being challenged by massive growth. Finally, it’s critical to make sure that smart automation applications truly ‘move the dial’. If you’re using IBM Watson to just identify double-counting of expenses, for example, you’re not thinking big enough. Your competition are looking at transforming themselves across the board.

By Paul Morrison, RPA and Smart Automation Lead, The Hackett Group

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