Process Mining | Intelligent RPA | Cognitive AI
Simple rules for RPA project success

Simple rules for RPA project success

#Robotic Process Automation or #RPA hasn’t been a serious solution up until very recently. But in this short time, it is alarming to note that the statistics on RPA project success rate are quite low. Perhaps, it is borne out of the hype surrounding RPA and what it can or cannot do especially when the boundaries between workflow automation tools, RPA and AI are not well understood. Clearly, something is not being done right. Here are some simple rules to consider to increase your chances of success:

Rule #1: Don’t be a “know all”. In my opinion, this is the most important rule to remember. Perhaps it is the single most important cause for RPA project failure. RPA may look very easy to implement on the outside and you may be tempted to do it alone. Don’t. There are many steps involved in the successful RPA journey. So seeking professional help e.g. an RPA vendor certified consulting partner or a vendor tool certified RPA consultant will go a long way in ensuring project success. If you do it alone you may either create short cuts or take on more than you can chew. Either way, it won’t be helpful. Also, it is not always possible to allocate your limited human resources from their normal work to new strategic initiatives and they may not have the needed bandwidth in terms of time and motivation for project success. So my advice would be to involve professional help and leave planning and execution to the experts as they have the methodology and best practices to successfully implement RPA  projects. But do provide your full support to the RPA implementation consultant or consulting partner. 

Rule # 2: Avoid Big Bang approach: Too often organizations rush into solution mode with both feet in and start implementing RPA across the whole organization, sort of a big bang approach. These are generally the organizations that have ignored rule#1. So don’t be that. Instead, do it in stages or what I call “automation waves” especially when there is no prior experience of implementing new technology and the required know-how is lacking. First, begin with simple processes in a contained environment and focussed on a specific business area business and then go onto more complex ones as your experience and skillset improve with each stage and lesson learned can be applied to each successive implementation wave.

Rule #3: Avoid Hammer and Nail approach: Too often, if the only solution you have is a hammer then every problem looks like a nail. So is the case with RPA. Even processes that are not the right candidates for RPA will find their way into an RPA project. So it becomes imperative to have a framework/criteria in place for process identification and selection. For example, this is part of “Analysis and Diagnostic phase” in our methodology when helping clients implement RPA technology in their organization.

Rule #4: Metrics are important: Metrics provide you with a way to know how well you are doing against a set objective. It is said you cannot improve what you can not measure. So it is very important that you define the key criteria for automated project success. It is equally important to define the baseline against which you will measure RPA project performance. For example, if one of the criteria for an RPA project is “Time to completion” then the time to complete a process by a human would be your baseline time and you will measure the time it takes to complete the process using a bot against that baseline. In your criteria, you would define a factor by which you expect the work to be completed by a bot versus the human. If you fall short then you probably will need to improve the performance of the bot to attain the set objective or to lower your expectation if that is what is required. Metrics also help you to moderate over expectations.

Rule #5: Do your due diligence for product fit: During sales process solution vendors sales executives will make many claims about their RPA product features and functionality in order to sell their solution. Once the sale is made and licenses sold they are off to newer pastures. It’s only during implementation time that you will know the true capability or functionality of a feature in terms of what you are trying to do.  So it is important to do your due diligence upfront and not after the fact. Here is where an RPA consultant/ partner can help. They can help bring their prior experience and expertise to know what are the pitfalls and how to avoid them. So it is important to have your consulting partner engaged earlier on. They would generally create a process inventory or repository of your key processes and understand what is involved in terms of technical and implementation feasibility.

Rule #6: Set the right expectations: It is important that your business area have the right expectations. Generally, it is the IT or PMO that will do technology/product fit assessment and business case. It is important that the business area where the solution is implemented is involved upfront so that the solution is as per their expectation. Many times IT will over promise and under deliver and that may be a cause for project failure. 

Hopefully, these simple rules and guidelines will help improve your success rate for RPA automation. 

Until my next article – Happy RPAing!!.

About the Author: Jaideep Kala is a principal at Toronto based Onbotix Services where he provides process excellence, automation and cognitive AI consulting services to medium and large enterprises.

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