Technology Overdose: Is AI/RPA/IOT/others being sold a bit too much?

Category
Digital
Author
Praveen Kumar

While we know the advantages and values of technologies like AI, RPA, IOT (or likes) to the business, are these being sold a bit too much? Are business users really getting the advantage or value-add which eases their life or are they stuck in this technology race? Are these innovative technologies being used as an R&D item, solving a technical problem and not addressing a business issue?

While conducting Digital Transformation workshops with some of my clients recently, these were the questions which were floating in my mind after the first few sessions. During the workshop, we were also discussing the possible improvement areas in business for factors like efficiency, quality, customer satisfaction etc.

Some of the technology folks from the team were too excited to extract some use cases which can be used for a quick POC, without thinking about the road-map post POC.

To share an example:

One problem statement came up that vendor data is being loaded into the ERP system manually by data team. They receive the excel sheet in an email from vendor management team. After receiving that, they manually verify the completeness and correctness of those sheets before uploading that in the ERP system.

Client wanted to explore possibilities of automation here. And guess what, technology team had RPA/AI written all over their faces even before the Data Team lead completed his process description.

RPA POC was immediately proposed by technical lead. Data team lead asked about how will the correctness of data be taken care as the team is doing that manually and there are no rule-based or pattern-based corrections. And that’s where the discussion went into a different direction.

What came out was, considering current process and limitations, implementing RPA may not really decrease the effort or drive more accuracy. On top, only for automation in this business process, RPA tool cost was way too high as compared to the salaries of data team, unless there is a holistic view about this tool.

I am not trying to say that, we should be fearful about RPA or any other technology. The point I am trying to make is, fitting a technical solution into a business problem vs finding a technical solution for a business problem. Technology teams can work hard to get a cutting-edge solution like RPA, AI etc. implemented, but unless it really cures the pain area of the business fully and has the applicability in wider areas than that POC, planning for failure won’t be an exaggeration.

Keep delivering value!!

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