Steven Dock, SVP CMS Research, Content, Natural Language and Publishing, Moody’s Corporation
Enterprise Search, Cognitive Search and Semantic Search are terms I hear every day. And while many users of internal corporate systems may not be familiar with them, they are increasingly frustrated that trying to find information at work is so much harder than their everyday experience as a consumer.
A simple example, if I want to know who invented ladies shoes with red soles, it’s as easy as typing “who invented the red bottomed ladies’ shoes?” into my search engine of choice. The search immediately names the designer, and even when it was trademarked and who his competitors are.
There also are a number of links to related information, telling me the story of the designer’s life, his inspiration and even news coverage of attempts to copy his work. The information is collected from different sources and then explained in properly constructed sentences, in a concise and easily consumable form. It’s as if the explanation was written for my specific query. We all know it wasn’t but it’s pretty much on the mark.
Now, we all know that none of this requires any special input from the designer, requirements to use their taxonomy or fill in specific fields or wait for the next quarterly release. The search engine simply assesses the most meaningful information to my request across multiple sources, determines what is relevant and explains it me in a concise summary.
Now, try this at your office. Ask a question to your corporate intranet or one of the Information technologies applications. For example, searching “what is the next holiday where the office is closed for the day” will probably result in a message that states “document can’t be found”.
If you’re lucky, you’ll get a list of search results with the word holiday in the title and you might get a laundry list of calendar documents that doesn’t describe the relevant offices or countries and certainly doesn’t answer your question like above.
Search is the first step to the innovation we talk about in board rooms and industry conferences. It needs to be at the forefront of any real innovation strategy
So you do what we all do and spend the next twenty minutes reviewing every document until you eventually find the information you are looking for.
What we’re really asking is for our corporate systems to provide answers, not documents. We expect systems to be able to understand the semantics of our request and not the keywords, exactly as they would outside the office.
If I search the word “holiday”, the system should understand that I mean a non-weekend day when my office will be closed and return the information relevant to this request.
Before it can do that, it needs to know who I am and what calendar is most pertinent to me, read it and determine the answer to my question and then answer it in language that easy for me to consume. Of course, it should also provide me a link to this calendar and potentially a list of other calendars properly titled by office and country that it thinks is pertinent to my question. That way, I could look at the calendar if I choose but only if I choose.
Just imagine if work searches worked like consumer ones, providing information from multiple documents, and joining fragmented data points with coherent narrative. There is no question that this would create measurable time savings for any company. However, I still find myself convincing people that this is anything more than a convenience. The question is how would you monetize the following:
1. Searches that can find relevant information across the enterprise, databases and embedded in your unstructured documents. This requires cognitive capabilities capable of extracting the true meaning of the request and every document to identify the most relevant information.
2. And what if the search can also isolate elements of the answer and using Natural Language Generation, construct a response to questions in a way that users can understand.
3. And what if the search can be smart enough to know if users accepted the answer or modified the search to find a better answer learning from each interaction and a build a knowledgebase to better answer in the future.
Most of us would argue this would be a meaningful advancement. I argue that they will open the door to machine and human based conversations. The reality is that search and response is the core of everything that is artificial intelligence and more than that it is critical to our relationship with these next generation machines. We won’t be able to work together and they won’t be able to fundamentally change our competitive advantage, drive top line growth and cut costs if we can’t communicate with them the way we communicate with the people that work for us and with us. Search is the first step to the innovation we talk about in board rooms and industry conferences. It needs to be at the forefront of any real innovation strategy.