Four quick wins for AI in manufacturing

For manufacturers of every size, there’s growing pressure to adopt AI. The pressure emanates from enterprise-level factors and stakeholders.

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With an AI financial planning solution, updates don’t need to wait for quarterly or monthly intervals. “You can go all the way down to weekly or daily updates, depending on your business,” Chawda said.

“You can have multiple plans, with internal as well as external factors or ‘features’ as they’re called in AI-speak,” Chawda said. “You can blend in your internal and external data at a fairly granular level. You can get the view of the detail by geography or at a component level, and that precision drives a direct impact on your margin.”

“Then, see how it compares to your current process. Benchmark it for next few cycles against the insights you’re getting today,” Chawda said. “The business can get confidence by running it in parallel for a few iterations, and derive value from iteration one. So, it’s not a traditional pilot; You are doing the comparatives in the shortest time possible.”

AI has the power to analyze large volumes of data, which can improve both the speed and accuracy of financial planning. That power is also important when manufacturers manage their contracts.

“Contracts need to be reviewed for vendor overlaps, risks or limits, to ensure you’re aware of them,” said Grant Thornton Technology Modernization Services Managing Director Supreet Singh. “There can be a tight period for that, like during diligence for acquisitions.”

Past technology solutions used optical character recognition and forms processing to try to streamline contract management. However, these solutions didn’t adapt well to the various formats, phrasings and other differences across contracts from many suppliers and services. “That technology really wasn't fit for contracts,” Singh said.

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Now, AI natural language processing (NLP) can adaptively understand contracts like a human would. “It doesn’t just look for certain keywords,” Singh said. “Regardless of how it's written in English, NLP can extract clauses, compare them to your clause library and help you understand where there is a risk in the various limits, renewal terms, expiration dates, payment terms and other things you need to watch.”

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“Manufacturers often have many suppliers, and many contracts with the same supplier, so it can be many-to-many relationship,” Singh said. “Their sales organizations might not always know which contract to leverage, so they just go with the last one, or they find a match for certain clauses.” Sales teams simply don’t have time to analyze all the text in every possible contract.

If a manufacturer has financial planning, contracts and vendors optimized, the best use case for an AI solution might be an analysis of procedures. 

Singh described one project that helped a company ensure that their SOPs were up to date. “There are thousands of pages of PDFs that need to be converted, digitized or updated, and people just don’t get time to do that.”

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AI-driven document analysis for existing procedures can combine with NLP meeting transcript analysis. Whenever there’s a conversation about creating a new SOP or updating an existing SOP, AI technology can help build or update a workflow. “Solutions can scan a PDF or document of an existing SOP and then look for phrases or other indicators,” Singh said. “The technology can find connections and insert the updated procedure in the location of an existing SOP. When it creates or updates a procedure, it can send a link for that update to a reviewer. The typing has been done; the person just needs to review that it makes sense and approve the workflow.”

With software integration, an AI solution can both update the text and create swim lanes for entire processes, completing four steps:

1. Create new SOPs
2. Update existing SOPs
3. Create new swim lane diagrams
4. Update or add swim lanes for different roles

The key to quick wins is to identify a use case where your organization truly needs the power of AI capabilities — and then make sure you apply the best approach.

Whatever use case you choose, identify your goals upfront. “You’re evaluating use cases so that you can have truly measurable quick wins,” Singh said. Apart from looking in the four areas discussed, companies can generally look for projects aimed at cost reduction and automation for document creation, finance system access and standardizing interactions in the close process, ERPs and other systems.

The best approach is to align for early returns, then use them to drive investment in solutions that go on the offensive and build top-line growth.

“That’s really when you start talking about customer sentiment analysis, customer attrition and the question of where you allocate sales funding,” Singh said. More advanced AI solutions can help drive system consolidation or even integrate customer demand with supply chain management. 

“AI is an impact event in the business environment today,” Chawda said. “In order to stay relevant and profitable, manufacturers have to figure out how to use it.”