In part 1 of this post, I described how cognitive computing can be used to gain a competitive edge. By using the information and knowledge hidden in data sources, cognitive systems can extract knowledge. For instance, you can use cognitive computing to improve your customer engagement by leveraging your previous experiences with your customers. You can even automate your customer interaction by using automated self-service Question-and-Answer applications.
Utilizing your own knowledge through content curation
So how can you use cognitive computing to tap into the knowledge from inside your organization?
The answer is Content Curation: collecting and evaluating all documents and other data that contains knowledge, about the topics I want to use cognitive computing for.
Tools like IBM Content Curator have the ability to collect data from different sources, filter out the candidate documents and control the selection process. The latter is mostly laborious manual work, where domain experts assess the value of the knowledge contained in the data. But this all depends on the trustworthiness of the documents to be curated. Law books are trustworthy, medical handbooks too. Social media messages mostly less.
Based upon what you know about your customers and their interactions with you, a system like the Watson Engagement Advisor can be used which promises “to automate customer interaction by fielding questions in natural language with informed, evidence-based reasoning”. This system can take information residing within your organization and use it, may be together with public information, to create a knowledge base tuned to your line of business.
In order to do so, you will have to identify and harvest the sources of information within your IT environment. Look for the Document Management Systems, Wiki’s, social networks, etc. that are used to collect knowledge. Or to put it more precisely, look for systems that might contain knowledge.
I’ve been at lot of organizations where these tools for collecting and maintaining knowledge are underused, to say the least. Documents are only stored when used in operational processes and for legal record keeping purposes. Wiki’s are out-of-date because it takes too much time and effort to update them with information. Social media feeds contain too many bogus messages to be useful as an information source.
Information Management to the rescue?
When you store documents for legal purposes only, you will not be able to exploit the value contained in the documents. All the information that is simply stowed away will just cost you money.
If you want to supply your employees with better knowledge and insights, automate customer interaction, or gain a competitive edge through better quality information and decisions, you’ll have to have your information in good shape: managed and maintained.
Start by making your unstructured data accessible for use within cognitive computing. Use tools for content curation to access the information sources. And valuate the information for these sources, to make sure you’ll use that information that will help you to gain knowledge.
The next step is to prep your organization to be information savvy. Encourage people to collect and share information. And to store this information in an accessible and retrievable way. Creating and organization where collaboration and sharing are commonplace, is not easy. This requires a change in company culture and the way employees interact freely with each other. From an information management perspective you can start offering tools where collaboration can take place, within the secure boundaries of your IT infrastructure. Of course you should take care of information governance, no question about that. In my opinion, you should not prescribe the way people should interact, just offer the means. And look where it ends. Maybe “unstructured” ways of working just create that type of unstructured data you’re looking for: data that contains knowledge.
The third step is to become a learning organization. Combining the information at hand, analyzing the data and building hypothesis around it is the way to start learning. Aggregating information into new facts and insights and using these in company policies is a good step forward in building a new culture of learning and sharing. In this respect obtaining knowledge doesn’t differ that much from what we already do with Big Data: trying to find new insights from all the valuable data available, like we say at Capgemini:
“Harnessing the data generated by your customers, and your own operations and supply chain gives you the opportunity to provide new levels of performance. The right insight into this data can transform your supply processes, use of assets, and performance of services, strengthening your customer relationships and enabling you to out-perform the market. ”
At Capgemini, cognitive computing is central to our vision for the future. With our wide ranging experience and expertise in Enterprise Content Management and Information Management, we can help you gain valuable insights and create value by processing the information inside and outside your organization, thereby gaining a competitive advantage.
The future is here. Are you ready?
This article was written by Reinoud Kaasschieter from CapGemini: Insights & Data Blog and was legally licensed through the NewsCred publisher network.