For most companies, it’s easy enough to automate simple, single-operation processes, especially when they’re limited to one business unit, such as customer service, HR or sales.
These tasks typically involve copying and pasting information, documenting compliance, triggering alarms or sending files to the right person for approval. By their nature, they are clearly defined and constrained. But all bets are off when it comes to cross-enterprise processes that involve multiple data sets and human actors, not to mention a series of decisions and actions across business units.
The biggest reason it’s so hard for CXOs and their operations teams to understand more complex business processes? They often don’t know how they work. That’s not a criticism. In a lot of companies, complex processes are created by the line-of-business managers, not the executive team.
Even when COOs can identify the steps in a given business process, the executives are usually far removed from the actions their employees take every day — and often, those don’t align with the intended plan. Sometimes, that’s the fault of the processes themselves — they’re too cumbersome, they don’t make sense or they don’t allow for the nuances of the real world.
The hidden value of process roadblocks and exceptions
The only way to improve enterprise-wide processes is to know what they are. Investigate, benchmark and move forward with a plan to improve upon the ways things get done.
Take the loan-approval process at a bank; you can trace the steps from initiation (customer fills out a form) to approval (manager signs off) and completion (customer is onboarded). The process crosses various departments and relies on a collection of information from multiple databases, from start to finish. At each step, certain actions are taken by certain people based on certain criteria or data.
The problems arise when roadblocks and exceptions pop up. Maybe the customer makes a mistake when entering information into the form — an error that a savvy loan manager might be attuned to spot, especially if it’s a mistake that happens again and again due to poor form design. Or maybe the manager who normally approves loans suddenly goes home sick — his colleagues know this, but the system may not, and so it will continue to route approvals to him.
In a human-driven system, the people involved in the process will change the way things get done in reaction and response — usually for the good of the company, as these new (unsanctioned) behaviors lead to better outcomes (say, quickly fixing the misinformation on an application or manually picking up the slack for a sick colleague).
And while there are lots of good reasons to know where these roadblocks lie, the most important one is simple — they’re where you’re most likely to see value from intelligent automation.
Why enterprise intelligent automation should be one of your big bets
Many organizations are moving from basic, foundational automation (in which they automate simple, routine business processes) to wider enterprise intelligent automation (in which they automate more complex, enterprise-wide processes). Why? Because enterprise intelligent automation (IA) applies a combination of technologies — including artificial intelligence (AI), natural language processing and machine learning — to bring humans and machines together to transform the way work gets done in every relevant corner of the business, boosting the power of the technology in the process.
Intelligent automation can handle structured and unstructured data, and it relies on reasoning and learning capabilities to analyze operational information and then make decisions based on pattern recognition and other advanced analytics. The end goal: to drive better outcomes in all areas of the business.
Foundational automation is intended to cut costs, improve data quality and reduce employee boredom and churn. But enterprise intelligent automation is intended to do something much better — free up your human employees to focus on the work that only living, breathing people can really do.
That means giving your workers room to make decisions and take action outside of explicit parameters.
Some processes will benefit from programming an algorithm to make business decisions based on available data. But most cross-enterprise, complex procedures won’t; algorithms just aren’t as good as people at making those kinds of decisions. However, people will always benefit from having the right data to help inform their actions, and that’s where IA can really shine.
An intelligent system will help experts deliver personalized advice (with the help of assistive automation) by delivering data that lies across the organization and tapping into algorithms designed to offer up actions based on perceived outcomes. But based on a combination of the information presented by the system and her own knowledge of the customer or his industry, the expert should be left to decide what approach to take. You want to enable that — even if it doesn’t square with the automated process your system serves up.
As companies transition to this new way of working, COOs (especially) will spend plenty of time and resources evaluating and deploying the technology involved to make it work. In order to enable a successful transition to intelligent, end-to-end business automation, these executives must also embrace the change management required to make sure that the company and its employees are ready to leverage the new capabilities.
Frankly, that can be more difficult and time consuming than implementing the technology itself.
It’s a three-step process:
Start by taking a clear-eyed look at the processes you want to improve — not just how they’re supposed to work, but how they actually work.
Involve the end users who actually live those processes every day to learn where the roadblocks lie (because that’s where the improvement comes in).
Give your employees the freedom to tap into their expertise once IA is in place so that you are getting the full benefit of the technology. IA is supposed to make it easier for people to do the things only people can do — not to replace them or to constrain them further.
Frost & Sullivan research shows that by automating complex business processes, you’ll not only understand those processes better, you’ll also be able to optimize them for maximum effect. That will help empower your people, speed decision-making and have a measurable impact on the bottom line. Acting now will also give you a significant competitive advantage.