• Top-Down vs. Ground-Up:  What's Better?

    As companies begin to implement Robotic Process Automation (RPA) into their operations and processes, they should find a systematic approach through which to define their RPA strategy in order to increase dividends and avoid the obstacles typically encountered by business expanding their AI department. There are two types of general approaches to an RPA strategy, as defined by the Everest Group: the top-down approach and the ground-up approach. 

    Within the top-down approach, RPA implementation is driven by top management. A team is set up in order to assist lower levels with the addition of RPA to their daily operations, and a detailed structure is followed in order to build familiarity and increase effectiveness over time. All processes are generally monitored and analyzed for optimality before being put into effect, and the focus generally lies within achieving greater efficiency in distinct, singular processes.

    On the other hand, the ground-up approach promotes the use of RPA technology beginning at the lower levels. Employees are educated about the effectiveness of RPA and the benefits of automating certain tasks, relegating them to the RPA robots and using their own time more judiciously. Each employee is given the technology and permitted to use it how he or she sees most fit, as well as given the assistance of a team of supervisors who are available for immediate consultation as well as to occasionally note progress and improvements being made. Employees can share tips, reward systems are created, and eventually the best RPA use cases filter throughout the company.

    Each method obviously comes with its advantages and disadvantages. Advantages of the top-down approach include its solid structure, which allows for better predictability of use and savings; a greater emphasis on higher-level process automation; and a greater level of support from IT, in part thanks again to the structured nature. But its disadvantages are also important to take into consideration, as there is a very high upfront cost associated with bringing in consulting, use-case identification, and process engineering. As well, because there is so much structure and the entire process is so heavily monitored, chances for RPA to be used in smaller cases or in situations which are not immediately evident are not usually taken, as corporate offices generally only associate RPA with major processes within the company..

    Advantages of the ground-up strategy include a much lower upfront cost, as there is a much more organic growth from within the company’s ranks, eliminating the need for expensive resources and teams. Change management is also noticeably easier, as employees are invited to work at their own pace, learning RPA for themselves and incorporating it as they choose. This in turn leads to greater innovation from within the company, allowing employees not only to use RPA to operate the large processes that would be covered using the top-down approach, but also smaller ones that grant the typical employee more flexibility within the day to create solutions for more difficult problems as opposed to be subjected to repetitive and mundane assignments. And while this approach can result in less optimized automation, results can eventually permeate up as the best solutions for specific processes are spread from the bottom, up the ladder.

    July 5th, 2019

    © 2019 RM Dayton Analytics, Ltd. Co.



    Cross-Enterprise AI vs. Intelligent Automation: 

    What's the Difference?


    As artificial intelligence (AI) has increased in efficiency and spread across the country and across the world, more and more managers have turned towards AI solutions to improve their processes and become more agile. The technology has drastically transformed the workplace, making it a much more intelligent, accurate, and productive space than it was even ten years ago.  

    Two of the most prominent systems used by companies today are Robotic Process Automation (RPA) and Cross-Enterprise AI. Organizations seeking to employ these systems often know that they can greatly improve their internal operations but not the extent, and in many cases they aren’t even sure how, without the help of extensive implementation consulting, to properly use these systems and install them in a value-maximizing way. RPA and Cross-Enterprise AI are extremely powerful, but their actual purpose must be understood, and proper expectations must be set in order to fully harness them.

    Strictly speaking, RPA is not a form of AI, as it represents more automation and performance of prescribed tasks than the use of data to create new information. RPA is designed to perform the same actions a human would through user interface and descriptor technologies. RPA operates in place of a human via a “bot” that uses various pathways and triggers. It does not create new data or enhance existing business models, but rather accelerates the timeline upon which those models operate.

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    Getting on the Right Path to Intelligent Automation:

    An Approach to Robotic Processing Automation (RPA) 


     The first phase in the journey is planning, in which you must determine the ways in which RPA can help you and whether your company is prepared to bring in this kind of software. You must develop your strategy, identify benefits that RPA could bring, and select a partner to help incorporate RPA. Key components of strategy should include building awareness of automation technology within the company, obtaining sources of funding, and creating your initial approach for implementation.  

    You then have to confirm that RPA programs are indeed applicable and begin your pilot programs, selecting your initial use cases, observing preliminary results, and measuring whatever benefits you can see. You must set up your basic infrastructure, begin acquiring skill in RPA technology and re-training your workers with new, more advanced skills that they will be able to use as a result of the freedom provided by robotic automation.

    The first major challenge can be a need of a roadmap or well-developed strategy. As mentioned earlier, a robust RPA strategy is necessary when it comes to determining potential outcomes, finding potential fits within the company for RPA tools, and executing the choices necessary to maximize the use of automation. Change management strategy is also needed when it comes to dividing roles, assuring company-wide buy-in, and resisting push back that may come from a skepticism of new technology.

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