The race is on to automate rote, repetitive tasks because organizational efficiency is a competitive weapon. Organizations successfully automating processes lower operational costs and increase the value of their human capital. Conversely, when the need for speed trumps a sound strategy, companies can lose valuable talent, waste money, annoy customers and assume other unnecessary risks.
“Artificial intelligence (AI) combined with robotic process automation (RPA) are being touted as the magic elixir that will solve virtually any business process problem. But companies must first review their business processes to determine if they’re worthwhile candidates for automation, ” said Ted Rohm, senior ERP analyst at Technology Evaluation Centers (TEC). “Many business processes will see no benefit from AI and RPA tools because there isn’t significant data to drive the AI tools or the current process is simply too old to fix. Any company looking to automate through AI or RPA technology needs to take stock of the current condition of its business processes before investing.”
Automation is not just a technology problem
Several technologies can help automate tasks including AI, machine learning, RPA and low-code tools that facilitate RPA. However, successful automation isn’t just a matter of acquiring tools.
“There are so many technologies that can help to automate and optimize business processes, it can be hard to know which is the most suitable,” said Craig Sweeney, SVP, global strategic solutions at global recruitment process outsourcing, executive search, talent consulting and talent acquisition solutions firm WilsonHCG. “Before committing to a new intelligent tech platform, organizations need to understand what they are aiming to achieve with their investments. It seems obvious, but there are still many companies out there that just go for the latest tech without clear and well thought out objectives, including how it will integrate with their existing their technology stack.”
In the haste to automate, various departments can end up procuring their own solutions to solve point problems. That approach can increase costs by adding to tech stack complexity while duplicating automation efforts. For example, HR, legal, and IT departments each get the same basic questions repeatedly, which is why those functions have replaced internal portal FAQs and hotlines with chatbots. Increasingly, organizations are standardizing on solutions that can solve several similar problems in the organization simultaneously.
“While RPA has been shown to lead to strong ROI, it is still important to have a plan. Rushing an implementation increases the odds of failure,” said Tom Taulli, author of The Robotic Process Automation Handbook: A Guide to Implementing RPA. “A good way to start is with a workshop, where there is a look at the basics of RPA. There should also be brainstorming sessions to see what processes are repetitive and routine, where are the bottlenecks and so on.”
One obvious automation risk is employees’ fear of being replaced. As Taulli points out, the impact of the pandemic has caused companies to look for ways to cut costs. Automation is one means of achieving that. However, before jumping in and executing, it’s wise to have a strategy designed to benefit all stakeholders.
Have a strategy
Tactical implementations of point solutions are not as valuable as a cohesive strategy executed well.
“Companies investing in automation can assure greater success by taking a step back and considering the full landscape of their business processes and stakeholders,” said Michael Sena, founder and CEO of Excel VBA consultancy Senacea. “Automation is inevitable for the majority of businesses, but its scope and implementation may vary.”
To determine which way a client should go, Sena focuses on four areas that are pinpointing the opportunities for automation, deciding the level of complexity that is actually necessary, understanding how automation will integrate with the broader business infrastructure, and human capital and upskilling users.
“We should always attempt to quantify automation benefits to see if the opportunity is there,”
said Sena. “Whether we use it to minimize manual work, assure better accuracy or quicker turnaround cycles, it is possible to estimate the monetary value. It lets us settle on the most efficient combination of automation and expert work.”
Since automation changes the scope of what a human does, it’s important to work with the affected parties to understand exactly how a process or task works and whether it works effectively before automating it or part of it. However, even when employees have been involved in the reimagining of processes and tasks to determine what should and shouldn’t be automated, they still need to learn how to use the system effectively.
“Smart systems have to be paired with the appropriate know-how and the skill level of the users,” said Sena. “If possible, automation should empower people by changing their work profile from manual execution to high-level management and control of tasks. When technology is not met with the appropriate skills, we risk [adopting] black-box systems and losing control over some processes.”
Justin Honaman, president and chief commercial officer of consumer products development company Contender Brands, recommends first establishing an RPA center of excellence (COE) that provides the required structure, governance, and discipline to achieve business goals. He also recommends:
- Establishing a process definition framework which identifies automation candidates;
- Defining the value proposition in qualitative and quantitative terms;
- Prioritizing opportunities; and
- Deciding whether the company has the resources it needs or whether it should outsource the problem.
Don’t overlook potential automation risks
It’s easy to get mesmerized by automation opportunities, but don’t overlook potential risks. For example, WilsonHCG’s Sweeney said in theory, one can hire a candidate without human interaction but his firm wouldn’t recommend it because too much automation can have a negative impact on the candidate experience.
Robert Mather, CEO of employment background check company Pre-Employ, said one of the most potentially dangerous implementations is the use of AI in the pre-employment screening industry to complete background checks on job applicants. If not thought out correctly, the use of AI can cause irreparable harm to individuals by employing processes that cause a disparate impact on minority applicants during the hiring process.
“Automating decisions about criminal behavior may discriminate unless each background check report is compared to the job applied for,” said Mather. “A company that uses an artificial intelligence system that rejects all applicants who were convicted of a felony may be discriminating against minorities. AI can frequently cause background check companies to be sued (not just the employer).”
One of the best ways to prepare for automation is to involve the stakeholders who will be affected. For example, employees tend to feel less threatened when they’re involved in the design of automated processes and tasks. Moreover, it’s the people doing the processes and tasks day after day who can explain how it works (or doesn’t work) best.
Some organizations make a point of asking employees what they don’t like about their jobs because the parts of jobs employees don’t like are usually boring, repetitive or both and therefore ripe for automation.
In addition, organizational leaders should be careful about the message(s) they’re conveying, consciously and subconsciously. While it may be more difficult to automate C-suite tasks than front-line tasks, one can stoke the flames of dissention and fear by underscoring the need for automation while claiming to be immune from it personally. The reality is even C-suite roles aren’t immune to process and task automation.
Fundamentally, automation requires effective change management both culturally and technologically. Getting the cultural piece right tends to be the most challenging.
For more on automation strategies check out these recent InformationWeek articles.
Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include … View Full Bio