5 proven strategies stuck? How digital transformation projects get back on track
18.05.2021 author /
Editor:
Susanne Richter-Wills*
/ Ulrike Ostler
The global pandemic continues to force many companies to shift their investments, which were intended for digital transformation projects, to other areas: maintaining business continuity, setting up home offices and meeting immediate customer needs. And after that?
Companies on the topic
With the help of some basic rules, stuck digitalization processes can be set in motion again.
(Image: rihaij on Pixabay)
In fact, many CIOs reevaluate their IT goals and consider which projects they should resume, abandon or initiate. Prioritizing the right automation projects is important because it can ensure that the organization recovers and flourishes in 2021. The following are five best practices for selecting the right initiatives that are worth investing in digital transformation.
1. Prioritization of projects
There was a time when cost reduction was the primary driver of digital transformation. However, a survey by Forrester Research found that cost reduction is now lagging behind investments in technologies that “accelerate digital business transformation, improve customer experience, and increase employee productivity.”
The pandemic has actually led many companies to discover that they have been doing something wrong all along. Forrester’s Global Digital Process Automation Survey found that two-thirds of companies reported having encountered faulty processes after switching to home office due to COVID-19, and as a result, 60 percent are now rethinking their process strategy.
The use of process mining and process discovery tools is a growing trend in prioritizing projects. Process Mining enables companies to use the information contained in their systems to create a visual model of their processes.
These can be analyzed to identify opportunities for process improvement and to have real-time monitoring of operations. In addition, future results can be predicted and preventive measures taken to facilitate decision-making.
2. A data-driven approach
A data – based approach should be used to prioritise projects-whether it is customer onboarding, invoice processing, contract verification, claims processing or call centre inquiries. Otherwise, one risks making wrong decisions on the basis of wrong factors, be it in favour of opinions of different interest groups, internal policies or quick-to-do short-term business without long-term added value.
To find out which processes are best suited to automation opportunities and how employees interact with them, it is critical to get a bird’s eye view of the entire business process to ensure complete transparency. For example, if you have an unusually low customer retention rate in an insurance company in the last six months, you want to know exactly why.
So instead of suggesting that investing in a customer acquisition workflow is the solution, you may find that delays in claims processing are the reason and what you need to do to simply avoid them. The use of data to determine the processes on which digitization efforts should best focus and the knowledge of the expected return on investment are a clever way to set priorities.
3. The leverage of artificial intelligence in automation
According to KPMG International, the reaction of most companies after COVID-19 was to stop financing new technologies, such as automation and artificial intelligence (AI). Meanwhile, executives are more optimistic and plan to increase spending over the next twelve months to accelerate the digital transformation.
The most common automation projects that have come to a standstill are robot-assisted process automation (RPA). In another survey, 38 percent of executives said that their RPA projects missed the target because they did not really understand the intended process, which was to be automated, or because the RPA bots were unable to convert unstructured content such as invoices, bill of lading or application forms into usable content and initiate downstream processes.
The banks faced a major challenge at the beginning of 2020, when they had to ramp up their credit processing in order to take into account the volume increase in applications due to the promised state corona grants. Over a period of two months, the banks experienced a loan volume equivalent to that of ten years, and those who were just trying their hand at the first RPA projects got into trouble when bots could not properly read various loan applications and accompanying documents.
Banks also needed AI technologies such as machine learning, OCR and natural language processing (NLP) to provide RPA bots with cognitive skills for logical thinking and understanding. In this way, the bots were able to convert unstructured data from documents into usable information for further processing.
4. The adoption of easily applicable applications
The role of employees applying new automation technologies is growing within organizations. These employees are business analysts and knowledge workers who are not trained as developers or have in-depth expertise in coding or specific technologies such as analytics, capture, RPA or process mining, but who are able to use these technologies provided in low-code or no – code applications.
RPA has been a catalyst for these easy-to-consume solutions in the digital market. This market has enabled technology providers and partners to develop low-code/no-code applications that can be integrated directly into their platforms with user-friendly interfaces. Today, low-code solutions are available for most systems and intelligent automation and business process management platforms, whether locally or in the cloud.
Whether it’s replacing deadlocked projects or launching new initiatives, integrating low-code solutions is a cost-effective way to democratize AI across the enterprise and accelerate the transformation of digital business.
5. Successful in the new normal
Microsoft CEO Satya Nadella noted the following last year: “We have seen the digital transformation of two years in two months.“
Susanne Richter-Wills, author of this article: “The most common automation projects that have come to a standstill concern robot-assisted process automation.“
(Image: Abby)
Leaders can now be more confident after surviving the pandemic period and know that early investments in digital transformation have helped minimize significant losses. They now have a justification to invest in automation using the latest technologies in process mining, artificial intelligence and no-code/low-code applications to ensure the company’s resilience and success in the current situation.
*author: Susanne Richter-Wills is Head of Enterprise Sales DACH at Abbyy.
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