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How to overcome challenges in implementing Cognitive Automation

Understanding the possible challenges from implementing Cognitive Automation, and how to overcome them is important to make projects a success. We’d like to discuss a few areas of concern below:

1. Employee Resistance

Employees are the core of any organisation, and thus, employee resistance is a very real challenge in implementing cognitive automation projects. Employees at different level may fear job losses and the negative impact of automation. This is especially true for intelligent cognitive automation solutions such as Gleematic. You can overcome (or significantly) reduce employee resistance with education and regular engagement for employees. The employees should be kept up to date on the cases considered for automation, how it might affect their jobs, how they  might have to do work differently with automation, etc. Supervisors of affected employees should plan for job re-designing and job re-allocation and get the buy-in from employees. 

2. Tool Limitations

Office-work Automation is an emerging space, and the tools may still have some limitations. Artificial Intelligence may offer some hope, but is not a magic wand for solving all problems.  Thus, it is important to consider how to optimize the use of the tools, and yet be aware of limitations.

  • Tools such as Gleematic come with OCR (Optical Character Recognition) and intelligent document-extraction features to pick up data fields. However, OCR has limitation and may not be able to achieve high accuracy if the incoming document does not contain clearly printed text or if you have scanned it at low resolution. Thus, it is important to make sure you have the right equipment to scan if you want to automate processing of paper documents. 
  • There are algorithms for recognizing hand-writing, but the accuracy of current technology is not near humans’ yet. A lot of time and resources might be required to make machines read your hand-writing documents. Thus, it would probably be more efficient to digitize the process instead, or at least have type-written documents. 
  • Data sometimes may be presented in ways that may be confusing even for humans. Our team has seen documents with little consistency and complicated phrasing in one field (especially the “description” field of document). Thus, it might make more sense to re-design a form or document. 

3. Process selection and optimization 

Automation is not a magic wand, and it can only be successful if you select the right type of process(es) to automate. Or you might have to do a bit of process re-engineering to make the process(es) optimal for automation. For example, if your process does not have “standard operating procedure”, then you might want to start with documenting the process first. You can also choose low-hanging fruits, and start with simpler process to gain momentum. 

4. Licensing complexity

Many of automation tool vendors would like to lock you into their platform. So, they have complex licensing and pricing. Organizations may get into a difficult situation if these licensing complexities and specializations were not fully considered. It is essential to understand the long-term impact of the automation platform you are considering right from the POC/POV stage. On the other hand, Gleematic has a simpler pricing plan that we differentiate just by “Designer” or “Robot” licenses. Contact us to find out more. 

5. Bot Ownership

Cognitive automation tools such as Gleematic should be seen as a “business resource” and the bots should come under the care of the business unit, rather than just leaving it to I.T. department. If I.T. considers this as another software tool and undergoes traditional test periods, the benefits to the company may be delayed.

6. Right stakeholder involvement

All stakeholders need to be involved from the outset:

  • IT: The role of IT in implementing cognitive automation (A.I. powered RPA ) is to ensure adequate technical management ( e.g. hosting, security, etc.). You might have problems with IT design, infrastructure, and security if you do not involve IT at an early stage.
  • Procurement: In order to recognize the advantages of cognitive automation and be co-creators of business profit, procurement must be involved.
  • Audit / Compliance: Compliance teams from the POC / POV process will be involved so that they are on board and are helping to fix problems early.

Knowing and addressing the challenges ahead can help you improve the chances of making cognitive automation (A.I. powered Robotic Process Automation) a success.  

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