The mathematical corporation where machine intelligence + human ingenuity achieve the impossible [ Notes from the book]

Book by
Josh Sullivan and Angela Zutavern

---------------------------Summary of what I read on April 3rd, 2018-------------------------------------

In the industrial era, we used the switches and the term “flip the switch” to perform different tasks. In the current era, the largest switch is a machine intelligence. However, modern advancement is not only due to technology-machine learning- but also due to leadership. Leadership with the technology makes the elements of the successful organization to whom we refer as “Mathematical cooperation”.

Mathematical corporations are driven by the data and algorithms. Data and algorithms have made the corporation forward-looking and experimental oriented. The forward-looking is a guide to future power for the organizations. However, none of the organization is mature enough in forward-looking using data but their leaders understand the critical pieces to guide the direction of their organization.

Instead of using big data and artificial intelligence to answer the old known questions regarding the organization, the leaders of the mathematical corporations are using big data and artificial intelligence to answer the unknown question that no one is asking today. Therefore, smart machines along with intelligent imagination of the leaders make “Big minds” that are driving force in mathematical corporations.

Leaders in the industry are all convinced that big mind is disrupting the current business. The power of big minds is predicting the future that can be valuable to their customers. Having the power to predict unknown universe was never available to the leaders of the past.

Why were we restricted in the past? We were restricted with our lack of ability in prediction. The magic of prediction is in viewing the details. In past, we don’t have all the knowledgeable data to understand the wellbeing of the organizations. With data, we are looking the things in detail and are predicting that we don’t know. However, how should we use the data? The answer lies in letting the machine to learn the patterns.  In order to teach machines to find the unknown patterns, we also need the thinking skills to work with the machines and this book is a guide to get the required thinking skills.

Recently, many leaders are turning their traditional organizations to mathematical corporations. Mark Field, CEO of Ford, is among those leaders. He allowed his employees to drive the cars fitted with hundreds of sensors in one of the experiments in the organization to gather and analyze data to better serve the customer needs. Traditionally, the survey-based mechanism is used to gather data from the customers. However, that mechanism is not enough as compared to data generated from sensors to understand the needs of the customer that even they don’t know. According to Mark, organizations work in two parallel worlds: real and digital. The digital world helps in making the real world better by predicting the unknown requirements. Ford is not alone gathering data and serving customers based on the users’ data.

There are many other examples as well. Gathering data from unconventional tools, such as social media has also helped many organization to better serve their customers.  For example, gathering data from social media helped Glaxo Smith Kline (GSK) to recall one of its product and improve its reputation among customers. GSK succeed due to emerging new tools for data collection that were not available previously. Therefore, using ever growing new tools of data gathering, mathematical corporations will keep on disrupting business in new ways.