4 Lessons Learned from the 2020 Automation Boom
Among the business continuity trends of 2020’s pandemic, business automation surged. This pursuit of survival has morphed into a land grab for a competitive edge — likely exceeding Forrester’s now-conservative estimate of $12B global spend on robotic process automation services by 2023.
Organizations of all sizes have embraced bot-driven digital transformation across departments to slim down operating costs and boost the quality of their results. But not all efforts have been successful — some have been quite the opposite.
As organizations move forward, many have discovered the hidden but preventable costs that separate failed programs from successful ones.
To avoid learning the hard way from common mistakes, here are some things your team can keep in mind if automating this year.
1. Never underestimate time-to-automate
From the start, many teams rely on estimated implementation timelines without accounting for processes that need additional prep work. Without taking the time to understand your processes, your automation may adopt inaccurate steps that are dated or simply not true to your real-world workflows.
Unfortunately, an “agile solution” that takes over four times the estimated setup timeline can easily lose momentum. Teams feel bamboozled about why their pilot automation efforts take up to half a year when they expected under 2 months at most. It’s only natural that some would abandon these slow and costly efforts before reaching completion.
To accelerate your efforts, knowing your processes is key. Employee interviews and other aspects of business process analysis (BPA) should be a consideration early into your plans.
2. Be sure processes are truly automation-ready
Knowing your processes can help you avoid another cardinal mistake in business automation: bots do not create better processes.
Teams who adopt bot-driven workflows may be convinced that issues with quality and efficiency are resolved by eliminating human error. However, some use existing processes with baked-in human error. Now they produce poor quality in higher quantities.
Naturally, organizations should be taking a deeper look at what their bots are being programmed to do. When picking the right processes for cost-effective automation, teams might see success with processes that:
- Will have a prominent impact to attract excitement from the wider organization.
- Are not complex in ways that lead to high-cost high-labor programming.
- Contain a clear start and end without tons of intensively-cognitive steps.
- Are standardized across departments and sites for better automation scaling.
- Are void of non-value added steps such as outdated activities.
Without automation-ready processes, redundancy and waste may still persist throughout your organization. Business process management (BPM) methods like the aforementioned BPA can help evaluate and prepare your processes.
3. Be wary of over-automating
On the other hand, some businesses have run too far with the momentum from early successes and applied it where it doesn’t belong. This will become especially true as more organizations pursue end-to-end automation. Overzealous efforts often come in the form of either:
- Automating past the point of diminishing returns.
- Spreading too thin with too many automation projects.
End-to-end business automation reaps big benefits for many workflows — but can actually cost far too much to program and maintain for others. Many businesses find as they offload processes onto bots and tether islands of automation together, there is often a final mile of complex processes that are best left to humans.
Other organizations have found that indiscriminately pushing for expanded automation leads to weak returns. With too few drops in too many buckets, teams realize they should focus most of their efforts on the smaller projects that make big changes. Eventually, growth comes naturally as internal teams gain experience and take the lead on their own specialized automation projects.
4. Embrace intelligent business automation solutions
Picking the right tools and platforms is just as important as choosing your processes. That said, a number of businesses discovered that some automation tools are more intelligent than others.
Many teams are learning that their choice in automation solutions are actually legacy systems.
For perspective, consider that your teams will have a difficult time building out their own automations if custom programming requires skills, time, or staffing that your internal teams can’t offer. Depending solely on your IT team or external consultants does little to build your internal talent pool and scale your business automation efforts at a strong pace. These are common challenges with legacy solutions.
In contrast, “intelligent” automation solutions are the next-generation designed with democratized development in mind. Integrating various DigitalOps Toolbox technologies such as RPA, AI, process mining, and business process management software (BPMS) gives organizations a smarter edge to their projects.
For example, teams are finding:
- They can leverage low-code interfaces to turn any frontline workers into part-time automation developers.
- Automating more complex processes within that “final mile” is more feasible with platforms that learn and adapt via machine learning.
- Process mining can further unpack data on their processes, train their AI, and narrow the time and skill needed to “bot-ify” elaborate workflows.
Ultimately, those businesses putting intelligent tools to work are finding competitive edge through better clarity into daily workflows. By combining techniques of BPM and BPA into intelligent automation, you can increase your chance to succeed where others have struggled.