Competing through data has been the secret sauce for a few organizations over the last decade and they have all built significant competitive advantage. “Competing on analytics – the new science of winning” by Davenport and Harris is a great read on these organizations.
Times are changing. Today, data is growing exponentially, thanks to better technology. Many more corporates are realizing that data and analytics can be powerful tools to make more informed decisions in their business. Newer applications of analytics are also continuously emerging in this digital business world.
A greater adoption of analytics is inevitable across all organizations over a period of time. Analytics would emerge as a need for survival. The differentiation between companies will depend on the extent to which analytics has been institutionalized in the decision making process of their organizations.
The purpose of analytics is to manage business operations more efficiently with data driven insights. It isn’t about data giants making complicated, difficult to understand reports and presentations. To ‘compete with data’ you need to be able to comprehend and decode your data as efficiently as possible. To enable businesses to do this, analytics as a discipline has changed. What was once the singular domain of statisticians has now included ‘data artists’ or visualizers who expose new patterns in data without compromising the complex nature of data.
The other new player in the field is the ‘data technician’ who uses technology to access, analyze and synergize data across the organization delivering easy applications which serves up ‘ready to use analysis’ across androids, laptops and traditional computing devices. The other emergent player is the ‘story teller’ or the Business Insights Manager, who understands the needs of the market / business and knows how to map back data driven insight to impact business operations, thus connecting the dots. Indeed the analytics company of today combines the skills of statisticians that build probability models, with consultants that can ask and answer business questions, and imaginative analysts with the vision of artists and the training of technologists.
At Hansa Cequity, our model is unique because it tries to integrate very contrasting dimensions into one entity where the sum is larger than the parts! Having a designer’s sense with data may contrast with a statistician’s dry look at numbers! We seek “intersection” skills- intersection of Creative, technology, data & business! Not easy to do with highly talented people & we are attempting it![divider top=”1″]
There is a lot of untapped potential in democratizing analytics. Almost everyone in an organization at some point or the other needs access to data to make decisions. The easier it is to access this data – the better the decision making. On the other hand – if it’s hard to access data, people will naturally tend to avoid it as they try to get their work done – or decision making will be slowed down. None of these is a good outcome.
In my limited experience – few companies truly democratize data access. It is hard to discover data in a self-service manner. One has to find key people with knowledge and access. New insights are hard to obtain as detailed data is often even harder to access.[divider top=”1″]
Try deep learning using MATLAB