17.09.18

Expert Opinion

Robotize your processes: Improve your performance management

  • #KeyrusManagement
  • #Management & transformation
  • #RPA

Izem FEKNOUS, Director | Keyrus Management Régions France
Jean-François GIGOT,
 Director | Keyrus Management Consulting

In the 1970s, the advent of the microprocessor transformed the way things were produced, and it was seen as the third industrial revolution. Building on the development of computerized production tools, the industrial sector continues to modernize its production lines, to such an extent that we now talk of "smart factories".

The shift to the computer age has profoundly affected both large and small organizations alike. It has led their support functions to industrialize their productive chains and automate certain tasks. Now they are starting to seek out solutions for automating their processes further.
Let us take the example of valuing stocks. The stock valuation is calculated by multiplying the volume of stocks held at storage sites (shops, warehouses, etc.) by the unit price for product type. The data are obtained through various channels: the inventory of one or more products, the recording of stock entries for merchandise received or sold, etc. To illustrate our exemple, let say that one piece of data equals one database that we need to access for 4 different databases to feed the calculation of stock valuation. Each database is owned by a different department  (Procurement, Supply Chain, Finance, Production) and their data are not fully harmonized accross leading to inconsistencies in calculation which are resolved through series a manual tasks. Time that could otherwise invested in conducting business analyses is taken up by the time-consuming task of sorting out discrepancies. Yet, such analyses are crucial if one is to gain an a posteriori understanding of the business, anticipate changes in it (examples being the seasonality of a product or its geographical nature), and also manage its performance effectively. 
For such a process to be automated, the databases must be made to "communicate" with each other. Such automation also involves redefining, in clear terms, the roles and responsibilities of each individual in the productive chain and the right sequence of activities to perform. 
To automate is, first of all, to remove sources of errors induced by manual tasks, improving there for significantly data quality. In the strict sense, it is about limiting manual actions to the initial stimulus that then enables the "thing" receiving it to perform the full processing. It is not a question of imitating manual tasks, but rather of accomplishing them in a different way, and thus  of reviewing and reengineering the process.

We are currently moving from a situation in which we have manual and automated tasks, to one where we are witnessing the emergence of automated or automatic processes, made possible by Robotic Process Automation (RPA) tools. As this shift occurs, the key fundamental factor behind the success of a project to automate a process is the project's capacity to integrate the new RPA tool into the existing setup.

Designing an effective process that builds on the existing one
What does Robotic Process Automation (RPA) mean?

It means the automation of processes using tools, called "robots", that are capable of performing a sequence of tasks automatically. The action by the user no longer consists in performing the task, but is, instead, limited to configuring the robot at the outset and then handling any unusual tasks (ones that cannot be accomplished automatically).

According to the principles of automation, the first thing to do is to take stock of the process that is to be automated. Adopting a Lean Management perspective, you need to identify duplicated
tasks, those with little added value, the individuals responsible for each task, the "upstream" and "downstream" tasks, etc. However, there are other points to be considered too:
• The quality of the data fed into the process at the front end, and coming out at the end of the chain, can affect the performance of tasks. For example, if data are incorrect and/or have come from two different databases and/or are in different links in the chain, they entail what can be a long process to analyze and reconcile the discrepancies in them, so as to ensure they are reliable.
• What is also required is a survey and assessment of the tools used: am I aware of all the tools involved in my process? Do they enable me to ensure the integrity and quality of the data? Do they help users perform their tasks? To what extent have users appropriated the tools available to them? Do such tools take account of the specificities of the business and/or organization
concerned? Once you have fully reviewed of the existing setup, (roles and responsibilities, organization, tools, and processes), you then need to design a target process, along with the roadmap for implementing it, whilst not forgetting to take into account the changing face of the structures with which we work. Thus, if consultants are assigned to work with a high-growth structure facing challenges linked to skyrocketing volumes, the new process will have to "support" such growth in both senses of the word: by both sustaining it, and withstanding it. This necessarily involves designing so-called "scalable" processes, and an RPA tool can ensure such "scalability" of the process.

Choosing your rpa tool so as to ensure that the automated process is efficient
This choice needs to be based on:
• An assessment of how well the tool meets users' needs
• The RPA tool's capacity to interface with the entire existing Information System (IS), without limiting the assessment of such interfacing capacity to only those tools now used in the relevant process
• The RPA tool's capacity to support the enterprise's growth and strategy 
• The integration of the tool's costs, including maintenance costs and licensing fees, into the Information Systems Department's budgetary strategy. 
In as much as the tool can be deployed transversely, it is best to avoid deforming the process to make it fit the tool. If the latter is used in a process that takes automation aspects into account, it then becomes possible to utilize the full range of the RPA tool's technical capabilities.
Today, the main benefit delivered by an RPA tool is the speed of result to achieve productivity gains by sequencing and automating tasks in an efficient way. Also since an RPA tool can be  applied transversely to business functions, it offers a better supervision of processes execution. It also brings with it a userfriendly dimension that acts to optimize the rate of appropriation of the tool by users. Lastly, from the perspective of steering the enterprise's activity, aside from the time that RPA tools free up – which can instead be used for conducting analyses - , such tools frequently offer a customizable reporting application that can be accessed on any type of device.

An automated process: what changes in an organization? 
An RPA tool implemented either transversely or on a single process (financial, HR, or IT) will provide gains on several fronts that will ultimately make time for undertaking analyses and steering performance:
• A reduction in the amount of time that the RPA tool's users spend accomplishing tasks. Their role is henceforth limited to managing one-off situations and establishing the rules of the business functions with regard to configuring the tool
• A change in users role from tasks execution to a steering/supervisory role, monitoring the status of the process in real time
• A higher level of collaboration thanks to tools allowing everyone to find out the current status of a process in real time, and to exchange comments on the documents included as attachments
• A common repository that improves communication, thanks to the possibility of formalizing and documenting the entire process in the tool, including everyone's roles and responsibilities
• A reference document shared by all the users of the process or processes to which the tool is applied, regardless of their individual roles, thus improving data quality by reducing both the adverse effects of having multiple databases, and the reconciliation actions required.

ABOUT THE AUTHORS
Izem FEKNOUS 

Izem's 13 years of experience have allowed him to lead projects involving IT consulting, IT-driven innovation, and digitalization, as well as organizational issues and transformations. Izem has developed recognized expertise in the analysis of Information-System-supported business processes and in the area of the governance of projects linked to business functions including Finance, OTC, and P2P.

Jean-François GIGOT
Jean-François Gigot has 20 years experience in Management Consulting in Financial Services & Life Sciences in the Benelux, advising clients on organization change and business  transformation through technology innovation, process reengineering and organization redesign. He has an in-depth expertise in Business Intelligence, Augmented Data Analytic, Data Governance and Performance Management.

Download