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AI for Insight: Three things we learned at the Forrester Data Strategy and Insights Forum

We live in an age of unequaled access to data.  By some estimates, the average company has between 150 and 400 terabytes of information stored. A large enterprise may have multiple petabytes, i.e. as much data as all the printed books in the world.

The problem, though, is that many companies haven’t figured out how to make use of all this information, up to 80 percent of which may be lurking in disconnected data sets or among millions of pages of documents. It’s as if they just had rooms full of phone books gathering dust.

That’s unfortunate. Amassing big pools of data but not making use of them isn’t just a waste of resources, it puts those companies at a competitive disadvantage. Forrester Research estimated that companies that effectively gain insights from the data they gather will be making over $1.8 trillion a year by 2021 and growing faster than others in their market segments – by understanding their customers more deeply and winning business away from their competitors.

The challenge is finding the right methods and applications to gain the necessary insight. Conventional data analysis tools struggle to digest these unprecedentedly large pools of data and unify many different types and formats – not just conventionally structured, static data in neat databases, but web content, free-form text (such as questionnaire replies or customer service chats), social media postings, Internet of Things data streams, medical records, and more.

To address that challenge, Forrester hosted an entire conference, its first-ever Data Strategy & Insights Forum, Dec. 4-5 in Orlando. It was headlined by some of its most respected experts on data strategies, analytics, and AI (artificial intelligence).

OpenText™ was one of the Gold sponsors of the Forum, and had the opportunity to share in our our own key to making effective use of your data – including the 80 percent you’re not fully using.

NOTE: Recently Forrester named OpenText a Strong Performer in both The Forrester Wave™: Notebook-Based Predictive Analytics and Machine Learning Solutions, Q3 2018 and The Forrester Wave™: AI-Based Text Analytics Platforms, Q2 2018.)

Zachary Jarvinen (left) and Virgil Dodson at Forrester DSI conference, Dec. 4-5
Director of Analytics Product Marketing Zachary Jarvinen (left) and Virgil Dodson, Analytics Developer Community Director, present insights into unstructured data analysis at the Forrester DSI Conference.

Spoiler alert: In our view, the key is using AI, especially language-aware functions such as text mining, to enhance and fill in the gaps of typical analytics or business intelligence applications. With a thoughtfully designed, AI-enhanced analytics platform (such as OpenText™ Magellan™), you can swiftly call up, organize, blend, search, and analyze data from dozens or even hundreds of sources, in enormous quantities, which lets you cross-reference previously separate data sets and gain all sorts of new insights.

That means you can make faster, better decisions; replicate expert judgments; speed up and automate repetitive processes; spot potential problems sooner; reduce waste and save money; serve your clientele more effectively; and identify new opportunities for profit.

We’ll delve more into that later.

But first, three of the best insights we ourselves heard at the Forrester DSI Forum:

Collectively, businesses have moved past the novice stage of asking “What use is AI? Why should we consider using it?” to asking “How can we realize solid, practical value from AI?”

We believe there are quite a few ways Magellan can deliver tangible value by automating your business processes, whether through asset performance optimization, helping you offer better-targeted product recommendations, listening to consumer/citizen sentiment, or processing paperwork.

Data is the lifeblood of AI.

That is, you can’t start deriving all these fascinating insights and automating business processes without feeding plenty of data into your AI algorithm to “train” it on what to look for, and how to handle different findings. With that said, outside a computer science lab no data set is perfectly clean and extensive enough to cover every possible situation you might encounter – so don’t let the perfect be the enemy of the good.  Get started today with the data you have, then improve it incrementally over time.

Don’t make the mistake of trying to rip out all your existing data strategies and assume that AI will solve all your problems.

Disrupting the status quo may be a Silicon Valley cliché, but it’s not nearly as fun in real life. Start with a well-defined problem, execute effectively on that, and build out from there. You need to find the right stakeholders to involve and the right processes to build your new AI project on top of. That way, it’s not a disruption but an enhancement to your existing operations. This gives it much better odds of succeeding, which builds trust for future AI initiatives.

Well, those were the insights we gained from the Forrester DSI Forum. And, as per the truism that the value you gain is equal to the value you make for your customers or constituents, we shared our insights on how text mining, one of Magellan’s major functions, can help you unlock the value hidden in the unstructured content that comprises up to 80 percent of your overall stored data.

This is hardly the first time we’ve talked about the challenges and benefits of analyzing unstructured data – especially human language, with all its richness, flexibility, and multiple meanings. At the Forrester conference, we showed some of the fun, interactive text mining demos we’ve built, such as mining the 30,000 Hillary Clinton emails popularized by the 2016 Presidential election, an iPhone vs. Android “battle of the smart phones” tech tracker, and even a content analysis of the very Forrester conference program attendees were experiencing. We talked about how Magellan analyzes both unstructured and structured data and integrates its findings into a convenient analytic interface that helps tackle challenges like improving the customer experience. And we touched on some of the use cases for analyzing natural language, everything from more efficient claims processing or new product development to cultivating brand loyalty by listening to the Voice of the Customer.

Did you miss the Forrester conference but want to have a conversation about these topics? Or you attended and now, inspired by what you heard, want to have a follow-up chat on the specific challenges you’re looking to solve? Contact us and we’ll be happy to dig in, share more insights, and talk through solutions.

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OpenText

OpenText is the leader in Enterprise Information Management (EIM). Our EIM products enable businesses to grow faster, lower operational costs, and reduce information governance and security risks by improving business insight, impact and process speed.

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