CGT: How can CGs get value from better managing internal data within their organizations?
Internal intelligence is one of consumer goods companies’ biggest competitive assets. A tremendous amount of information lives in PowerPoints, PDFs, videos, Word Documents and more. This data is the most difficult to extract from, yet the most valuable, as time, money and insight was spent converting data into knowledge. It’s a constant challenge to find the information when needed, especially when information is spread across repositories and geographies.
Employees across CGs — including product marketers, IT, researchers, supply teams, sales, customer support and leadership — constantly run into the challenge of wasting hours every week trying to find information that lives within their company’s files and systems. We’ve seen situations where trying to find information is so challenging that customers commission projects for work that was already done because they had no idea it already existed.
CGs live in a highly competitive environment, taxed with a demand for quick, impactful results. Providing their teams the capability to quickly access internal knowledge delivers a huge advantage, from freeing up thousands of hours per year spent on searching for existing information to saving millions of dollars in redundant research.
CGT: In working with your CG clients, what pain points do they have using knowledge management systems?
The biggest challenge we hear is the time it takes to get the data into the system and make it usable. Many systems require users to identify, upload and tag enormous amounts of content. This is not just a one-time burden during implementation. The process creates an ongoing issue of adding or updating information on a continual basis. This old school way is a tremendous impediment to success and adoption. Quite frankly, promises of saved time and resources are often erased by this new time-consuming process.
Next generation, AI-powered knowledge management systems remove the manual processes of uploading, tagging and curation. The best advice is, don’t fall for the show of a friendly interface that makes uploading look simple. There’s no reason to move your content from already secure systems. Look for platforms that leverage existing assets where they live natively.
CGT: Where does the consumer goods industry rank in maturity-level for AI knowledge management implementation efforts, compared to other industries?
It depends on what pocket of the enterprise you are looking at. In research and insights, CGs seem to be certainly leading the charge. These teams are actively seeking out systems, know the benefits and are aware of challenges. They understand many of their competitors are already far along their journey. Take for example, PepsiCo who recently posted a “ performance assessment” of how their AI hire has done.
Outside of research and insights, it seems to be a more level playing field with sales enablement, HR and IT, implementing next generation AI-powered knowledge management.
CGT: Who should be involved in implementing AI knowledge management within the organization, and what are the best practices to make the process seamless?
This is dependent on the use case you are trying to solve. IT is always a part of the implementation and should be brought in early to help your vendor understand how content is accessed. Always include the subject matter experts for intel on the data they find most valuable and how it needs come to life.
A not so obvious answer is to include an executive. Technology doesn’t work in a vacuum. In fact, for technology to be successful, you need buy in across the company. Leaders need to understand the ROI, so they become your cheerleaders. If you have executive leadership buy-in, then you’re on the right path.
CGT: What advice do you have for CGs that are just starting to think about implementing AI knowledge management systems?
Solve problems one at a time. Start with small user groups with the biggest need. For example, before taking on a client we hold a user case persona session to clearly define specific needs, requirements, and ROI of each specific use case. If your vendor can solve it and prove the system is valuable, then continue scaling it by creating more positive use cases.
Big picture advice: Remember the Ferris Buhler quote, “Life moves pretty fast. If you don't stop and look around once in a while, you could miss it”. Tech moves even quicker. Don’t get comfortable. For CGs to stay competitive they need to continually test, learn and watch the marketplace, and never accept the status quo from AI vendors.