Solving a problem requires expertise, knowledge and skills in a specific field. Although this sounds like a fair statement, there are new techniques for solving problem, that do not necessarily rely as much on the expertise, knowledge and skills of individuals, but use data as a means to solve complex problems.
With huge volumes of data being available across the world through internet, most of the complex problem can be solved just by analyzing relevant data. The process involves identifying the problem area, collecting relevant data, organizing it, visualizing it, inferring insights, and finally communicating them in an effective manner.
As organizations grow bigger, they embrace complexity. Complexity consumes time and reduces the productivity of the organization. It also creates conflict of interests and knowledge bottlenecks, thereby impairing an organizations ability to solve its problems. However, we have come to an age where lots of data is at our disposal, which can be leveraged to reduce inter disciplinary complexity and solve complex problems.
Data provides an insight on what has happened. If we learn from these insights, we can also build predictive models to forecast what we think may happen. Availability of data to the lowest grain makes it possible for us to diagnose a problem and find the root cause. It can also enable us to diagnose the success in a specific discipline, and to explore the possibility of replicating similar models in other disciplines. Data can also be used to diagnose future problems and take precautionary steps to avoid the problems.
Our ability to leverage data for solving complex business problems also provides us a platform for experimentation, to truly understand what works for our business. Also, what works today may not necessarily work tomorrow in this fast changing world. Data enables us to understand these changes quickly and helps us to respond quickly to ensure minimum damage. Analyzing data can help us expand our services in markets that we don’t understand, and enables us to experiment and identify the right business model for each market.
However, solving problems by leveraging data is easier said than done, as data comes with its own complexities. The processing of data involves careful considerations related to the volume of data, data formats and the speed at which data gets generated. It involves identifying the right data sets, and building complex analytical models to make sense of it. It also involves constructing various visuals to help in the interpretention and communication of insights.
This involves significant investments in appropriate platforms and technologies, including hiring of new skilled personnel like the data scientists and data engineers. The returns may not be immediate, but investing in these technologies is key for large global companies to become agile and swift.