The ability to search for information and find what you need is a critical knowledge management capability for any enterprise search platform. But too often, search is limited to a quick keyword search and a set of links that leave you trying to figure out what you need.
What if you could take search to the next level? What if you could get search results that show you how things are connected (or aren’t), enabling you to get the insights you need to make good decisions quickly?
A Knowledge Graph transforms basic search into a set of relationships, connecting what may at first glance seem completely unrelated, or what would take you days or weeks to connect manually.
AI-powered search is delivering results for those using it, but we’re still just at the start of benefits the technology is truly capable of delivering. What’s more, companies that adopt early have a chance to run far out ahead by transforming themselves through innovation driven by artificial intelligence.
In earlier blogs about the value of cognitive search for life sciences companies, we’ve focused on the role it can play in accelerating drug discovery and finding new therapeutic uses for drugs that have received FDA approval. The search technologies that help achieve those goals can also make life sciences sales and marketing smarter and more effective.
Cognitive Search Powers Customer 360
A 360-degree view of the customer is something every company — life science or otherwise — aspires to yet few can achieve. The challenges to Customer 360 that life sciences companies face are similar in nature and scope to those of any large enterprise.
The corporate intranet remains the lifeblood of any major enterprise. Over the last decade it has emerged as a key location for ideas, documents and collaboration. But for many it can also be a frustrating morass of information that remains difficult to find, forcing people to rely on email or instant messages to trade ideas and documents.
The main problem is that many intranets were developed early in the online revolution and have been slow to evolve. Outside of work, employees are used to intuitive search experiences in their personal lives with tools like Google, Alexa, and Siri, and now they expect the same personalized, highly relevant experience for information access in the enterprise. They seek answers, not a list of results.
My last post on cognitive computing was a backgrounder, and it stated the importance of search to any cognitive computing initiative. So, how does cognitive computing powered by search lead to digital transformation? In fact, just what is digital transformation?
It is, no doubt, an overused phrase. But it captures something very real that’s occurring not only in business but across society at large. An article in i-SCOOP frames digital transformation as the ways in which a mix of digital technologies accelerate change in business and organizational activities, processes, competencies and models.
Today’s business users don’t search for documents that may have the information they seek buried within, instead they ask their systems for answers. This shift in attitude is a key driver behind the move to cognitive search.
Any large enterprise is packed with disparate sources of data coming from any of a variety of different systems. Cognitive search is about creating connections between this data so that employees can get answers quickly, so they spend more time on core activities, and they make better informed decisions.
From a business perspective, this means creating experiences that match how a user interacts with information.
When IBM Watson burst on the scene a few years ago by famously winning Jeopardy! people swooned. Here was a machine that seemed to live up to the promise of a science fiction future. IBM purported to show us all an artificial intelligence (AI) that could understand human language, sift through massive amounts of data, and provide answers to questions.
From a marketing standpoint this is a gold standard for enterprise software. Companies quickly signed on to the promise, looking to Watson for answers for everything from insights in their CRM data to finding a cure for disease.
When life sciences companies develop new drug therapies or biomedical interventions, what typically attracts the most attention is news about the success or failure of clinical trials. But a lot of work goes on behind the scenes before these efforts ever reach the clinical trial stage. In fact, as life sciences companies decide what promising therapies should receive development resources, it’s often rigorous fact finding and research that determines a go or no-go decision.
What exactly is cognitive computing? Well, if you ask 10 academics or scientists, you’re likely to get 10 different answers. Look it up on Wikipedia. You’ll see that in the academic and scientific community, there is no agreed upon definition. It’s just marketing jargon. Ouch.
On the commercial side though, we may not have a precise definition for cognitive computing, but we’re very aware of its potential to help our businesses.
Cognitive computing and AI have increased the tools in our toolbox. Machine learning, deep learning, neural nets, natural language processing. These technologies are the foundation on which companies are building new capabilities that affect top-line revenue and bottom-line profitability.
Hurricane Harvey hit Houston hard. Harder than many expected, including a number of the oil and gas companies located in the area. Some evacuated early and had no idea when they would reopen for business.
“How soon they reopen depends on the severity of flooding and the resumption of power to the areas. Experts say it's still too early to say, with the storm still moving through the region. But they believe gas prices will increase 5 cents, to 25 cents per gallon.” (CNBC.com)