Robotic Process Automation And You

Robotic process automation is a capability segment that is growing quickly in large part because of the speed in which it can be delivered with limited risk. This is a natural progression to the growing autonomous automation capabilities including robotics. This next logical step of business process improvements combines business process analysis and improvements with software robots identified and driven by artificial intelligence tools and workers. Combine the potential benefits with the limited risk and the robotic process automation provides a very alluring opportunity to quickly add benefits and efficiencies to processes in the operation.



The challenge in the operation is continuous pressure on improvements in efficiencies; to do more work with less human interaction. Unfortunately for the operation, and logistics in the supply chain, robotic implementation can be very disruptive because of the dramatic change to the operation. This is where robotic process automation can bring value to automate the existing process without dramatic disruption. This will provide the opportunity to improve efficiencies while the disruptive projects can be implemented. In fact, I would suggest that robotic process automation be viewed as the first step in a robotic strategy because it provides the first step to proving the automation.



Within the operation the greatest disruption is brought about by the dramatic and sudden change that is demonstrated by physical robotic implementation in the warehouse operations. Robotics not only disrupt the operation and the process and flow of people and operations, it also disrupts the physical layout of the warehouse resulting from the robotics implementation. While there have been dramatic increases in efficiencies, volume and accuracy this must be tempered, initially at least, with the disruption in the warehouse. Don’t get me wrong, I’m a strong advocate of automation to improve the operation, I am only saying you must go into this with eyes wide open to understand and plan for the holistic impact to the operations.



Robotic process automation allows for a trial at increased automation to improve the efficiencies of the operation without dramatic change. This is a benefit not only to the operation, it is also a benefits strategic planning by providing a point of validation for the automation. This is a critical benefit because of the investment required for increased automation with autonomous robotics. The resulting increased efficiencies delivered by robotic process automation allow for a refocus by the operation to more complicated processes that may be more difficult to automate or require autonomous robotic automation.



Automation is a multi-faceted opportunity for improvement and must be viewed as such in strategic planning and strategic initiatives. The organization and operation especially must evaluate options based on the process and automation opportunity, all processes will not achieve improvement from the same automation tool. This is why it is so important to implement a robust and forward thinking strategic planning process to help identify the improvements.



Automation is another flavor of process evaluation and improvement that brings a new set of tools to the toolbox. It must be remembered that these tools excel in different scenarios and situations and the strategic planning process must be a focus to incorporate these new tools as appropriate. This incorporation of new tools is critical to the long term success of an organization and especially now considering the velocity of disruption. There is no time to wait and see how others use the tools. The key to success is embracing a strategic process that experiments and looks toward incremental change to stay ahead of disruption. Disruption is the tipping point of incremental change, unfortunately it is tool late to react to disruption and best case scenario is creating your own disruption.

Generation AI Influence On The Market

Artificial Intelligence has greatly impacted the supply chain and ‘you ain’t seen nothin yet’ as they say. The market disruption is driven by the combination of consumer embrace of technology and the growing embrace from technology savvy, older generations in the market and the workforce. These converging influences are driving the supply chain now to incorporate these same new technologies in combination with artificial intelligence in order to sense and respond to the disruption. Disruption in the market will only increase because of technology capability improvements and the imagination of the consumer. This imagination and experimentation will increase the disruption as the new generations increase their involvement in the market.

We are seeing now a dramatic increase in market participation by millennials and gen-x and in turn the market must be prepared to incorporate their reactions and demands. As for sensing the demands, there is so much information available now in the market based on the online habits that there is really no way to sift through this vast amount of data to succeed in reacting and meeting the demands without Artificial Intelligence. We are seeing now the results of poor the poor sense and respond capabilities in the marketplace with legacy brick and mortar retailers struggling with the disruption and lurching from one attempt to react to another. The market itself and the consumers have moved on before these retailers can react. This is essentially a real time demonstration of the disruption in action and this will only increase in velocity.

The key disrupting factor now is mobile technology and how the younger generations are using this technology to support their lifestyle demands. This disruption has increased in velocity as the concepts are proven by early adopters and then spread through other consumer groups. Based on the embrace of mobile technology, what was once a strategic weapon is now almost a strategic albatross, I’m speaking of the number of brick and mortar stores. This embrace of mobile technology requires an equal embrace of the omni channel shopping experience by the large retailers. The current major disruption rolling through the retail market is related to the demands of consumers for a true omni channel experience. The retailers struggling are the larger retailers that have been slow to invest in technology to develop the experience.

Now we are seeing the results of this shopping disruption, especially in the large department store sector, where the early adapters are succeeding and the late adaptors are struggling! The struggling retailers are seeing the results of previous strategic practices to hold off on investment until the market settles and the winning technology has been selected by the market. As a result of the velocity of change in technology and use of the technology the winning technology is not selected by the market, instead the technology is embraced and usage of the technology modified and enhanced based on the users of the technology.

I see that the most significant disrupting factor in the market now is not related to technology use by the marketplace but related to the technology use by consumers within the market. Consumers have now turned the table on the market by developing methods that must be adopted by the market and retailers rather than the market pushing capabilities to the consumer. This is really where consumers are driving the market and this is also the most significant opportunity for a retailer such as Amazon or now Wal Mart to really reshape the relationship with the consumer and in doing this reshaping the market itself.

Data Analytics And Artificial Intelligence Driving Disruption

One of the most critical capabilities to responding to change and disruption in the marketplace is the ability to sense the change in a manner and, most importantly, timeframe that allows a response to be identified and executed. The frequency and discontinuous nature of change rocking the market requires a robust process that takes into account as many factors as possible to identify the change. This process then must describe factors and relationships to allow them to be analyzed to develop the response. The difficulty lies in the volume of data, both new and old, that must be taken into account to first identify the change and second to guide in determining a response. This is where data analytics practices utilizing artificial intelligence comes into the equation to support the business.

The two challenges; data for analytics and the actual analytics require a thoughtful strategy and approach that will allow you to sense the demands from the market in both a manner and a timeframe that will meet the velocity of change requirements. These challenges go hand-in-hand as two sides of the same coin; you cannot sense the change without a great deal of data to analyze and you cannot analyze the amount of data without the artificial intelligence to process large amounts of data.

From the data perspective it is very fortunate that the big data tools and storage technology has advanced to the stage were the collection and maintenance of the data is no longer an issue. This allows the collection of vast amounts of data available from all points of the supply chain and especially from the eCommerce channels. This data along the supply chain can now easily be captured for detailed analysis and because of the volume of data available the results of the analytics can be more accurate and more informative of trends. The important point here is the collection of data from the viewpoint that the more data the better because you never know where the analysis will take you and in order to come to a conclusion you must have the data to analyze and also prove the concept.

Ten years ago, in the early growth stages of big data, the challenge was the ability to collect and store the amounts of data for analysis and the analytic query tools to quickly perform the analysis. This required careful review of the data available to select the appropriate elements that you believed were necessary to produce the analytic results. Then the data collection required over night collection and the analytics were run to produce large reports in a daily schedule. Everything took time and you had to be careful to analyze the expected outcome. Now though because of the dramatic improvements in the technology the process and results are much more robust and immediate. Now there is no concern about the amount of data and the queries themselves are also much more interactive.

The analytics of the data presents the challenge in this equation and this is where the focus should be placed now. Artificial intelligence tools really come into play from this perspective to provide a value add to the equation. Artificial intelligence and machine learning will be a baseline requirement to allow the market to sense and then determine how to respond to the changing demands. These tools will are necessary to first sense and understand the demands of the market and then these same tools will provide the means to analyze the potential solutions and even forecast the impact to the market of change.

The key benefit of these tools is the speed of analytical results and then combine that with the delivery speed of a solution. Speed of sensing the demand and then speed of response are the objectives that must be front and center for the market and the participants in the market. All indicators based on technology lead to increased speed of demands and resulting disruption in the market and market participants will not have the time required for any manual analysis of these trends. In addition, only failure will come from participants that wait for the market to deliver a solution that they can adopt.

The participants that embrace artificial intelligence combined with machine learning will be the players that succeed and prosper in the market. The rate of failure that we have seen in the market will only increase as the velocity of changing demands increase. The good news is the building block tools to quickly and efficiently sense and respond to the increased velocity of changing demands are already available. The bad news is that the market participants must embrace the tools to develop their own practices to use the tools.