As artificial intelligence and machine learning offerings grow in popularity and move into production systems, enterprises are increasingly looking to utilize these technologies to automate critical business processes–from infrastructure maintenance to data management to customer services and beyond.
While there can be significant, tangible value in embracing automation technologies, realizing their full potential requires more than just flipping the “on” switch. Your automation journey should be well thought out ahead of time, attuned to the specific needs of your organization.
In this eWEEK Data Point article, Brian Sullivan , Managing Director of Oracle Technology Delivery at Accenture, provides six steps that he believes are important to developing and executing a successful automation strategy.
Data Point No. 1: Spot problem areas and create a vision for the future
We’ve virtually always found that those who look to incorporate new technology merely for the sake of it guarantee their own failure. Don’t dive headlong into automation. Instead, leverage the data at your disposal, and take the time to identify inefficiencies that could be improved upon the most by automation. Consider: Where are your teams spending the most amount of time? Which processes are most in need of improvements?
Once you’ve determined your problem areas, you’ll be well-positioned to map out the automation journey. You can clearly define desired outcomes, projected results, and KPIs (key performance indicators) for ongoing measurement. This is absolutely critical, as it’ll serve as your north star as you map out and then execute your adoption strategy.
Data Point No. 2: Socialize the project
Automation, despite its popularity, has also generated much fear of job change or loss. To avoid pushback as much as possible, make sure to socialize each initiative with stakeholders early on. Explain your vision: the project’s scope, the reasons behind the changes, and the expected results. This will enable them to help you on the automation journey, adjusting the project to their needs and avoid disrupting their work as much as possible. It is equally important to ensure that your organization’s executives are aligned with your vision. This helps ensure continued support from an investment standpoint.
Data Point No. 3: Assess your options
Before you broadly implement your automation strategy, examine your options. If possible, try out a few avenues in small pilot projects, and benchmark the results against each other. Make sure you have well-defined evaluation criteria and consider your organization’s current technology stack to ensure that the solutions you pick will integrate easily within your IT architecture.
Data Point No. 4: Embrace an agile mindset
Because automation brings such tremendous change to an organization, enterprises should proceed incrementally. Very much like the agile philosophy applied to software development, organizations should automate intelligently– one process at a time– to get valuable feedback and adjust the direction accordingly. This not only ensures a more rapid pace, but also provides opportunities to learn from each implementation, increasing the chances of success for following projects.
Data Point No. 5: Improve your organization’s tech, but don’t forget about the people
Enterprises spending a lot of time and effort on automation initiatives sometimes find themselves unhappy with the results, expecting either better productivity improvements or greater ROI. Often, it is not because the implementation wasn’t successful, but because no changes were made on the human side to best capitalize on the newly automated processes. Worse, sometimes changes enacted by automation have a negative impact on the teams by disrupting their workflow.
A good way to avoid this pitfall is to establish a longer term digital labor management process, with visibility across all implementations as well as a continuous feedback channel to ensure that normal operations–“business as usual”–are not being disrupted, and that productivity increases are consistent with the needs of each team. In this way, you’re well-situated to achieve expected ROI, and from there properly reinvest the time saved by implementing automation.
Data Point No. 6: Designate a Chief Automation Officer
Because automation is a continuous project, much like the journey to the cloud, I’d highly recommend designating a group and/or an executive responsible for automation initiatives moving forward. A Chief Automation Officer not only provides the oversight necessary to ensure initiatives are data-driven, consistent, and aligned with the business, it also creates accountability as well as a framework for future projects.