It is an adage in life that is also relevant to intelligent automation projects: before you start, understand where you want to end up. Beginning any journey without the end in mind is a sure way to waste time, lose money and frustrate everybody. Creating an Intelligent Automation (IA) Strategy that defines your end goals is the best way to ensure that you get the most value out of your efforts, and that these are aligned as much as possible with your overall business objectives.
Practically speaking, though, it’s not always possible to know exactly where you will end up but you should at least understand your Intelligent Automation ambitions. These ambitions can range from anywhere between ‘we just want to say we’re doing some RPA / AI / blockchain’ to creating a completely new business model. There are no right and wrong answers here, and your ambition may change along the way, but knowing your overall aspirations now will mean that you can certainly start on the right foot and be going in the right direction.
I would consider three degrees, or levels, of ambition, which I have called: ticking the Intelligent Automation box, improving processes, and transforming the business.
The first of these, ‘ticking the IA box‘, is for those who just want to be able to claim in their marketing material and to their customers that their business, service or product has some clever technology (usually AI) ‘built in’. This approach is surprisingly common, but I’m not going to focus too much on this approach because it can be covered by selecting the most appropriate elements from the other types of approaches. To be honest, you could justifiably say that your business uses AI now because you filter your emails for spam, or that you use Google Translate occasionally.
The first serious step to extracting real value from Intelligent Automation will be in improving the processes that you already have, without necessarily changing the way the function or the business works. Intelligent Automation, mainly through RPA in this case, will be used to make existing processes more efficient and/or faster and/or more accurate. These are the most common uses of IA in business right now, and inherently the least risky; process improvement is the approach that most executives will consider first when deciding on their initial steps into the world of IA.
Whilst making existing processes faster, better and cheaper can provide a great deal of value to a business, there is arguably even more value available through transforming the processes or the function. By transformation I mean using IA to do things in a materially different way, or in a way that wasn’t even possible before. One transformation example that IA is particularly suited for is the enablement of customer or employee self-service. The benefits of a self-service option are that it can be made available twenty-four hours a day, seven days a week, and that it is generally cheaper to run. It also gives the customers or employees a sense of empowerment and control. IA can be used for the direct engagement aspects of the process, employing chatbots and/or speech recognition capabilities to communicate with the person, and also for any decisions that need to be made based on that communication (e.g. should this request for credit be approved?) by using prediction or reasoning tools. Also useful when creating a self-service capability is Robotic Process Automation, which is able to handle all of the rules-based processing and connect all of the necessary systems and data sources together in a non-disruptive manner.
So, understanding your AI ambitions is an important early step in developing an IA strategy and subsequent IA capability. These ambitions will guide the first steps that you take and help steer you on the overall journey.
This blog article is written by Andrew Burgees and is an reworked excerpt from his latest book. Thank you for your contribution to this blog.