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A successful automation project must take into account technological and organisational aspects

Automating a process or, even better, a business area in your organisation therefore goes way beyond a mere IT project.

In particular, the implementation of an automation project requires consideration of two key aspects in tandem:

  • The technical and technological aspects, which involve firstly the definition of a set of processes capable of being tackled – in other words those in which the potential benefits can, for example, feasibly be maximised – and secondly the knowledge and identification of solutions that can best address the organisation’s needs;
  • The organisational aspects: here, data robotics (understood as a continuum between robotic process automation and intelligent process automation) implies a remodelling of working methods, which should be addressed right from the early stages of the plan.

Technical and technological aspects

What specific processes can be automated? With which processes can the company obtain the greatest benefits from automation? What strategic roadmap is needed to meet the business's automation needs? To address these issues, which are fundamental if an organisation is to avoid wasting resources and energy on initiatives with low added value, the company will need to take a structured approach to discovering its processes and identifying actual automation opportunities.

Using the Automation Opportunity Matrix è , it is possible to carry out a structured analysis of the automation opportunities available by evaluating over 30 qualitative and quantitative characteristics pertaining to the organisation’s internal processes. These are mathematically summarised across four key dimensions:

  • Structurability, understood as the effort required to create the conditions necessary for allowing a data robot to operate in an integrated manner and with the fewest possible exceptions. the more operational, linear and deterministic the process, the more it can be automated using robotic process automation solutions; similarly, the more crucial the human decision-making component, the more it will be necessary to integrate intelligent process automation components into the solution;
  • Business centricity, which expresses how critical the process is for the achievement of business results and, consequently, how important it is that the process is carried out with the fewest possible errors and/or repetitions;
  • Risk exposure, in other words, the possible risks to which the organisation is susceptible in the event of a process execution that does not meet its expectations;
  • The Value of automation, which measures the net benefits deriving from the implementation of an automation solution, i.e. the trade-off between costs (implementation, process re-engineering, etc.) and the resulting savings (lower process lead time, reduction in FTEs, etc.).

AI Landscape monitor

The Automation Opportunity Matrix is a tool designed to support managerial decisions relating to the automation roadmap, or in other words the selection of implementation priorities.

Nevertheless, the potential for automation must be supported by adequate technological capacity and, in particular, where Intelligent Process Automation, solutions are applied, specific algorithms must be available to systemise the focal points of decision-making, as must the input data needed to train those algorithms. The classic “make or buy” decision must take into account the associated impacts in terms of the time and costs needed for the solution to become operational:

  • The algorithms can therefore be developed in house, starting with appropriately integrated and modified generic “libraries” or, if available, found on the market;
  • As for the data, this can be gathered or as necessary created within the organisation or, alternatively, sourced from (more or less “open”) market sources.

A careful analysis is needed to identify which vendors, among the hundreds crowding the market, can provide the right algorithms, data or both needed to handle the various decision-making junctures.

The AI Landscape monitor, the market monitoring centre for artificial intelligence solutions developed in a partnership between Reply and the Bocconi DEVO Lab, utilises a high-level understanding of the artificial intelligence ecosystem to map out, on the basis of publicly available information, the complex ways in which AI is articulated in different application areas along with the features of the solutions involved.

The AI Landscape Monitor provides an exhaustive exploration of the artificial intelligence ecosystem. It analyses vendors and the solutions they offer in the market from a technological, commercial and financial point of view, using a framework and proprietary methodology that bring together Reply and SDA Bocconi’s extensive expertise.

The goal is to identify relevant solutions that might align with the process automation opportunities emerging from the application of the Automation Opportunity Matrix methodology, with regard to these opportunities, Reply assists customers with identifying the optimal solution based on their specific needs and with integrating the solution across their systems.


Organisational implications

At the same time, we should not overlook the importance of an organisational structure capable of supporting the roadmap both during implementation and once the automated solution has become fully operational.

In most cases, and especially when it comes to intelligent process automation solutions, the paradigm likely to succeed will be that of the Human-in-the-Loop. This is a scenario in which human and machine work side by side, with the former benefiting from the machine's data processing capacity, and the latter learning incrementally from insight generating by the human, who will retain ultimate responsibility for decision-making process for years to come. A risk of algorithm bias: therefore exists, in that there is a transfer of the human decision-making boundaries to the machines. Overcoming this requires a significant investment to develop the necessary analytical culture, a prerequisite for increasing the dissemination and effectiveness of the solutions involved.

Moreover, the establishment of internal centres of excellence for the operational and managerial management of automation solutions can represent a true roadmap accelerator. By bringing together process, technical, analytical and design-related skills, significant synergies can be created between the initiatives that make up the implementation plan.

Stand-alone automation initiatives, in most cases, do not bring the desired benefits and may be uneconomical and harmful to the business if the right organisational structure is not in place to support them. How is the automation roadmap structured within your own organisation?

Data Driven Machine Learning Robots

Intelligent Process Automation

Data Robotics, defined as the set of technologies, techniques and applications required to design and implement a new automation process based on self-learning and artificial intelligence technologies, facilitates the introduction and integration of automation into organisational processes. Thanks to the application of “smart” technologies Intelligent Process Automation guarantees an improvement of Robotic Process Automation, facilitating the evolution from solutions that handle straightforward and recurring tasks, to new paradigms based on machine learning techniques.

Intelligent Process Automation 0