“In the connected world, customers are no longer just a number or account; they are unique human beings with a distinct set of needs.”
- Robert Scoble, Age of Context: Mobile, Sensors, Data and the Future of Privacy
Well, work or no work, life is contextual. What seems perfect for you might be imperfect for someone else. This is a basic fact of life and yet how to ingrain this idea into technology remains a persistent challenge.
Have you noticed why a particular company has specific management rules in a particular location and why these change in another geographical location? We have to understand that societies, culture and practices are different in different places. Countries across the globe have different economic scenarios and values.
For global corporations, implementing organization-wide enterprise solutions is extremely challenging because the management teams do not realize and recognize the ‘context’ of each different place. Enterprise technologies need to learn this contextual difference and bend accordingly.
Imagine you have a twin sibling. Both of you wish to pursue science as a major subject. While Astrophysics fascinates you, your twin is inclined to Biochemistry. What if your twin was forced to follow your dreams? Would you pursue Biochemistry? Now imagine the failure out of disinterest and forced choices. Disappointing, meaningless and a wastage of resources – time, money and effort.
A reigning restaurant chain owner in the U.S. food industry plans to enter the South Asian market. To grab the target audience, the owner will have to find out how price conscious people are in this part of the world. When do they like to eat their meals and what does each meal constitute? Yet, unless the owner offers newer options with local spices and condiments that the South Asian population is habituated with, the chances of success are lesser.
When buying a car, the European customer is likely to take a decision based on the safety factor, while an Indian will definitely zero in on the price point. Hierarchies, gestures, values, body language all differ from place to place. What about unspoken rules and assumptions which might be playing havoc in the inter-personal relationship between you and your colleague across the border?
Expecting employees across the globe to respond uniformly to say an enterprise technology implementation is asking too much. Successful decision-making is possible with contextual data analytics of each place; and the accommodation of options which show how best success could be achieved by adapting contextually at each place; thereby also planning in advance the necessary steps, possible risks and mitigation involved.
Contextual Intelligence is the capability to explore and apply extracted knowledge (contextual analytics) from any or all of relative data.
Quantification of data is a prerequisite process of contextual technology.
The challenge here is that not all of available data can be quantified since not all of it exists in forms that machines are used to comprehend i.e., in numeric form, typically referred to as Structured Data. Data also exists in non-numeric forms like random textual data; including data from social media and digital footprints; audio and videos. This is referred to as Unstructured Data. Making meaning from this type of data requires advanced algorithmic technology which comprehends human language – words and their relationships - intelligently.
Contextual technology reaches even the darkest corners of data and gives analytics of great value.
Imagine being able to quantify the contents of a book or a research report and generate meaning out of it? Imagine applying this intelligence to real life situations for better outcomes? As can be seen, organizations are missing out on valuable insights from their Unstructured Data.
Another example. You have a huge collection of books that are of importance for your research work submission. Your supervisor has asked you to pen down a paper for an upcoming conference. How do you find data from the books, notes and journals that is relevant to the paper? Of course you could do it manually on the one hand. On the other hand, contextual technology could that for you! Filter out only that data which is relevant to the topic. Only those notes, words, sentences and paragraphs from all of the available data (books, notes, journals) ‘relevant’ to the topic you wish to write. You will also get insightful analytics from the extracted intelligence. This is the significance of context.
In a nutshell –
• Contextual Intelligence analytics show why one particular environment is successful while another is not. Context is Requirement specific.
• Contextual Intelligence saves time, costs and operational effort.
• Contextual analytics influences decision making with hard evidences in real-time
• A complicated conclusion is made easy with contextual insights and data.
Everything that we do in our daily lives, the way we think, the way we react is contextual. Without ‘context’ we tend to drift away from any relevant idea. Using intelligent tools to unearth the contextual meaning out of any content is the call of the day. It is the new frontier in Artificial Intelligence.