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Common Challenges AI-Powered Knowledge Management Solves

Posted by Equals 3 on May 16, 2019 8:13:31 PM

Businesses hold huge stores of unstructured data. Think of all of the  PowerPoints, PDFs, Word Docs, audio and video that are spread across different file systems. But how do you find what you need, when you need it? Knowledge workers—including marketers, researchers, business development teams, customer support and leadership—are faced with daily challenges to find information within those assets. Lost knowledge is a universal challenge. It also costs time and wastes money. 

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Common situations that elevate the problem include:

DARK DATA

80 percent of worldwide data will be unstructured by 2025 (IDC). After 90 days, those that are not actively in use are likely never to be opened or used again.

 

REDUNDANT RESEARCH

Millions of dollars are spent recommissioning research that has already been done. The more teams, the more geographies, the bigger the challenge.

 

EMPLOYEE TRANSITION

Someone starts, leaves or changes teams and previous knowledge is lost. Finding answers means deep exploration process or duplication of the predecessors work.

 

MERGERS & ACQUISITION

Times of rapid change when companies merge together or win a new account means teams are trying to get up to speed on the new influx of data.

 

CENTRALIZATION COMPLEXITIES

Information is moved off hard drives into data lakes, digital asset management systems or with an IT vendor, yet the tools prove to be inadequate in searching the data.

 

For years, businesses accepted challenges around unstructured data as the “cost of doing business.” Until now there was not tech solving this challenge. Past solutions required creating tags or file structure were wildly inefficient. One person thinks different so things get categorized according to individual preferences. Now there is finally technology to solve it. The answer to this problem lies in AI-powered Knowledge Management

 

 

 

Topics: Insider