Is the value of AI reduced by the inconsistency of multi-source data?

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Though there is much to be said about preparation, there seems to be little said about the preparation of data when it comes to businesses adopting AI or genAI technology.

It’s simple (or simpler) to have a Customer Relationship Management front-end system provide textual responses to predicted (or progressively predictable) questions from customers on-line, or to have a smart phone system responding to verbal questions (that become textual), etc..

It is another thing to just say “We have it as a priority to adopt AI or genAI in our business in the coming year …” to streamline our business processes, reduce costs, increase revenue and market share and not be prepared to implement it.

When AI or genAI is manifested in a company with a dozen or more systems (PLM, PIM, ERP, etc.), each system will have both common and its own degree of unique, contributive data when streamlining predictable business operations, etc. The only way this becomes reality is IF and ONLY IF those systems have formalized an intimated (intelligently integrated) profile of Digital Fluidity (flow of data).

What Digital Fluidity means is that if the data that exists in one system (i.e. Assortment/Product Line Planning) passes its information to a PLM system, it is critical that this information either remains protected from change OR that (if changed) it is passed back from PLM to the A/PLP system so that both systems are synchronized. Same with data that may pass from PLM to a PIM system used for ecommerce or big-box store publishing. Either it is protected or synchronized.

What has that got to do with AI?

Well, if the AI strategy is to combine/converge the data from all 3 systems to enable it to identify insights, then the data common between systems is either ignored (not likely) or it is ensured to have the same value. Otherwise, AI may identify misinformed insights or generate hallucination levels that are well above average.

When AI or genAI is expected to draw data from this myriad of system, such as the development time of a new Product (PLM) + the on-line linger time of customers in the on-line store of that same Product (ecom) + the sales of both on-line and in-store of that same Product (ERP or Financial SOR), then it is critical that all systems have a harmonization of common data that combines with each system’s unique data set.

Digital Solution Group is focused on assisting companies in forming that harmonization of data by intimating (intelligently integrating) the range of systems (silos) and forming digital fluidity throughout a company’s SolutionScape (set of systems used to design, develop, and deliver products from Mind to Market).

Check out how DSG can assist your company in “getting data ready” for AI and genAI – preparing for the future. Browse the myriad of other articles in the Potpourri section of our websiteor (if you need to reset and regroup) check out the article on The Need for a Systems Integration Strategy / Tactical Plan.

Click the Contact Us page to see how to connect with Brion Carroll (CEO/Principal Consultant) of Digital Solution Group

Is the value of AI reduced by the inconsistency of multi-source data?

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