Daniel Fallmann is Founder and CEO of Mindbreeze, a leader in enterprise search, applied artificial intelligence and knowledge management.
CEOs and line-of-business leaders are smart people. But they don’t know what their enterprise knows. As a result, their organizations miss out on a multitude of valuable opportunities.
Organizations possess a wealth of data. However, the data is all over the place, held in siloed systems and various formats. There’s no way to make sense of it. This makes it extremely difficult for business professionals to find the information they need. Research on the state of enterprise search in Scandinavia last year revealed that more than a fourth of workers find it somewhat or very challenging to get the information they need to get the job done. That’s a drain on productivity, and it takes focus away from innovation.
But the problem that organizations face is far bigger than just a search and productivity issue. The lack of business understanding due to siloed data means business professionals don’t even know what’s possible. As a result, their businesses fall short of their huge potential for success.
In this highly competitive business environment, organizations need to change that by bringing meaning to their data so they can gain crucial insights. This requires using artificial intelligence (AI), cognitive search, an insight engine and knowledge management (KM) to connect the dots of enterprise data. When organizations can do that, they get a more complete understanding of their businesses, customers, processes and opportunities for improvement and growth.
Take A Business-First Approach To AI
Many businesses begin their AI efforts because somebody is screaming about the need for AI. Sometimes these voices come from the inside. Other times, they come from outsiders.
Martin White of IT consulting firm Intranet Focus Ltd. recently wrote that some vendors imply that “the AI/ML underpinnings of their technology render as superfluous any requirement to define user requirements.” He went on to add, “Nothing could be farther from reality.”
Taking an AI-first approach to business efforts is a mistake. Instead, think first about which of your functional areas can most benefit from AI and the corporate intelligence it can deliver.
A good supplier can help you with that. Together, you can work to understand where, for example, you can save money by using AI to do things in more clever ways. By defining enterprise success criteria when you’re getting started with AI, enterprise search and insights projects will enable you to get the maximum return from your efforts and investments.
Get Your Hands Dirty
Instead of simply writing down scenarios and specifying use cases as a theoretical exercise for how your business can gain value from AI and information insight, get your hands dirty.
Take your real-world data and see what a selected product can do with it hands-on. This will enable you to focus on concrete business pain points, understand the power of the product and where information insight can help you improve.
Remember, this is not a traditional IT project. Start with a certain functional area and involve the business stakeholders, use information insights to add value to that functional area, and then grow your corporate intelligence efforts organically. Strike the right balance between breadth and depth so you can begin adding value for your organization by applying an insight engine, enterprise search and AI to your business data and your business processes — without the need for an organizational change.
Connect The Dots
The concept of a digital twin is expanding beyond the industrial sector. You can now use insights intelligence to connect the dots of your enterprise data to get a 360-degree view (or digital twin) of your business, customers, processes, products and resources.
Our customer, a leading American audio products corporation, has created a digital twin to get a 360-view of its bill of material (BOM) information. In the past, employees at the audio equipment company had to jump between multiple applications to collect all the component-level information they needed about a specific BOM. Now, employees have a single interface through which they can get information about products, their use cases, interfaces, the components used in the various products, the dependencies and regulations related to those components.
In the past, it would take employees at least 20 minutes to find the BOM information they needed. But now that we’ve collected all of this data and connected the dots, employees have all the relevant information they need at their fingertips.
Understand Your Present — And Be Ready For the Future
By connecting the dots of enterprise data, you can be more efficient. More importantly, you can be more effective and more competitive today, and in the future, because you will better understand your business, your customers and important trends that will affect your organization.
Situations change quickly, so it’s important to keep your finger on the pulse of your business. Just consider what happened in light of the Covid-19 crises. Many employees started to work remotely. As you can imagine, this is changing the questions that your employees and the customers they are working to serve are asking their colleagues and you, their employer.
When you connect the dots of enterprise data, you help employees get the answers they need. But you can also do something even more interesting. You can analyze your internal queries and user behavior to uncover trends about what information and solutions people are looking for.
Now you can understand the current situation, sense demand and know where things are headed (demand curation). Knowing what you know will help you move in the right direction to address customer and employee needs, use your resources in the best way possible and ensure business success.
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