Editorial
“I’m sorry, Dave, I’m afraid I can’t do that.” — HAL 9000, “2001: A Space Odyssey”
What does the future hold for information management? This question is causing a lot of fuss, especially now that artificial intelligence and machine learning have moved from the realm of science fiction to become applied practices and disciplines in business.
Data is the foundation upon which these types of computer intelligence can be built. We want the machines to learn and do more, but in order for them to do that, we must provide them with good, quality data.
Bringing Consumer Search Expectations Into Work
Search is often misunderstood, if not downright under-appreciated. In a Google-driven world, we all take it for granted that search not only works, but that we'll find what we’re looking for within the first page of search results. The “consumerization of IT” has led to a situation where business users have grown frustrated with corporate IT systems whose search tools don’t perform as well as Google. The problem is complicated by the fact that the enterprise data being searched comes from multiple systems.
People have always collected, acquired and maintained content, whether it be books, music, photographs or something else. This human practice has played a significant role in our identity and relationship with our world. This has also become true for businesses, which create and collect content in order to interact with other businesses and, more importantly, consumers.
Companies now find themselves in a world where content is almost exclusively managed by digital systems and services, a busy, congested place to be. Having end users at the center has been standard practice for decades, but offering those users the same positive experience that consumer tools offer is an ongoing challenge.
Related Article: 6 Ways Enterprise Search Is Nothing Like Google Search
Business Needs Data
Search is how we navigate data to procure content and hopefully extract the meaning and value we seek. The problem with enterprise search is there are many different types of data in corporate systems, and not all of it is easy to search.
We have both “structured data” and “unstructured data.” Structured data is made up of discrete pieces of identifiable information, such as names, addresses, locations etc., that are found in database fields and are structured for use. Unstructured data is something quite different; it does not have the “structure” of a database or a system. Unstructured data may include images, videos, text files, social media posts and much more. All of that is good content, but it doesn’t have the structure that is needed for it to be easily found via traditional query methods.
Business systems are full of unstructured data. Users produce content without any metadata to search and categorize by, creating a library of files that cannot be properly utilized. An intelligent and robust “metadata model” and data dictionary can solve that problem by providing a reference for your work and a place for your users to search — a place where they can “enquire within upon everything.”
Learning Opportunities
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The Future of Social Media: Emerging Trends and How to Stay Ahead of the Curve
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The Building Blocks of Personalization
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Attracting—and Keeping—Your High-Net-Worth Investors
Join PwC to dissect their recent survey findings on a specific customer subset — high-net-worth investors.
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The Future of Contact Centers with AI at the Helm
Learn how to balance human intuition and interaction with the potential uses of AI to create delightful and lasting CX
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3 Steps to Unlock Your Customer Data and Drive Revenue
Discover how Twilio Segment’s #1 Customer Data Platform helps implement data-driven strategies.
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How organizations can design, build and run Generative AI into the Customer Experience
Discover how to drive enhanced CX through Generative AI
Webinar
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The Future of Social Media: Emerging Trends and How to Stay Ahead of the Curve
The impact of emerging technologies like AI on social media
Process: Know Your Content, Know Your Business
Data, information and content feed business. Customer data, financial data, human resources data, and also rich media like photos, videos, graphics, logos and marketing collateral — all of that can contribute to growth and innovation. Paying attention to how this content has been created, captured and leveraged, and an understanding of how it creates value, is the key value proposition of a business’s digital strategy.
This foundation is the secret that can inspire and provide the groundwork for the transformative digital strategy that expands markets and manages complex, consumer-centered supply chains. The strategy is never finished but is a continual process of leveraging the collective intelligence of a network of consumers and providers for rapidly cycling invention. As long as change exists, a strategy will change. Success starts by defining what your customers and business aim to achieve and then creating a strategy that is flexible and well governed.
Related Article: What Data Will You Feed Your Artificial Intelligence?
Technology, Trust and Authenticity
Technology is great when it is leveraged to transform data into information and then information into insight that can generate knowledge — something actionable and meaningful. Data provides the meaning upon which processes and the technology can be optimized. But if the data delivered does not match the user expectations, then the efficiencies of a personalized consumer experience are lost.
Technology is merely a tool, capable of being used to achieve a specific goal. The tool’s functionality has the capacity to produce satisfaction when used to perform a particular task. Understanding the needs of users and providing those touchpoints will increase the perception of personalization and improve the overall experience and allow machines to learn. The struggle in managing content within the digital world is as complex as the digital workflows underpinning the efforts. This provides the link allowing processes and technology to be optimized, and hopefully a point where learning and intelligence may begin.
Value Is Not Found, It Is Made
Data integrity is critical to AI and machine learning, and trust and certainty that the data is accurate and usable is critical. Be mindful of the people, processes and technologies that may influence data and learning within business. Content is critical to business operations — it needs to be managed at all points of a digital life cycle. Leveraging meaningful metadata in contextualizing, categorizing and accounting for data provides the best chance for it to deliver return on investment. The digital experience for users will be defined by their ability to identify, discover and experience an organization’s brand just as the organization has intended.
Remember: Value is not found, it is made. Make the data meaningful and manage it well. Start with a foundation in data, embrace the transformation and discover the value in content. There is no need for HAL to sing the “Daisy Bell” anytime soon, so let's not give him a reason to do so.
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