No Match Found
It’s not easy to make automation simpler. Many early adopters of simple automation have found in retrospect that perhaps they went too fast. They would do well to slow down just long enough to ask a few key questions and put a governance framework in place. One company had more than five teams working on emerging automation in an uncoordinated fashion. They didn’t know what the other teams were working on. In fact, they didn’t even have a common definition of automation.
The need for a governance framework runs deep because a different governance model is needed when teams are empowered to use no-code tools. Think of the potential problems if only one person knows how a particular bot works. Poor controls that allow an error to become systemic to a process could put the whole company at risk. If a change to a source system like an ERP breaks a bot, and there are hundreds of bots tapping into that ERP, that change creates an operational nightmare. And when AI is part of a process, how will you explain its decisions to customers or other stakeholders? For reasons such as these, an enterprise-wide governance and controls framework is critical when automation is assigned to business units.
Poor controls that allow an error to become systemic to a process could put the whole company at risk.
Some companies, particularly those in financial services, already have frameworks that govern spreadsheet macros. An automation governance framework covers more ground. It spells out approved tools and security standards for system access. It also specifies controls, standards, mechanisms and requirements for regulatory compliance, as well as addressing configuration and testing, backup and recovery, ongoing maintenance and support, among other things. Depending on the level of autonomy granted to business units, a framework might include controls to validate code or check tool output, as well as documentation to define artifacts that should be retained for compliance and audit.
Governance also means ensuring that business users are aware of all their technology options and have a methodology to understand value and risk, so they can take advantage of the right tools for the right problems. By ensuring that even the simplest automation can be scaled and maintained over time, the risks can be adequately managed, and the benefits can be fully realized. Addressing risk is central to realizing business benefits because properly managed innovation risk fosters innovation.
Governance also includes building a roadmap to more intelligent automation. Automating end-to-end processes often means orchestrating work among humans and machines across multiple automation technologies. This orchestration requires IT to develop a framework that enables automation to bloom independently across the enterprise, while progressing toward a common vision. Data accessibility is an important consideration in tying together simple automation with intelligent automation.
In addition, cognitive frameworks with advanced machine learning often fall back squarely on IT to develop. Thus, the IT function’s role shifts toward governance in some areas, but control in others.
Orchestration requires IT to develop a framework enabling automation to bloom independently across the enterprise, while progressing toward a common vision.
Sustaining automation initiatives requires a clear governance framework as you empower more and more people with automation. Even if you are just getting started with targeted pilots, begin addressing company-wide governance that can grow with your ambitions.
When developing your governance approach, it’s worth asking yourself some key questions. How will you choose your automation projects? Which tools will you make available to business users? How are projects supported and monitored? What regulatory requirements affect data handling and processes?
How much autonomy do functions have over automation initiatives and which areas are the domain of your IT organization? Getting to the optimal mix requires business leaders like the CFO and CIO to model collaboration, demonstrate commitment and continually communicate expectations.