If we see it from a financial perspective, we always want to make a profit with the assets we have in the company, in fact there are financial indicators, with which we can measure the performance of a company based on the use of these assets. For example: if you acquire an asset, what you expect is to obtain a return on the investment made. Recently there has been more talk about how much is the benefit your company is obtaining from the analysis you do on the data. For that we have the discipline of business analytics, with this, what we want is to manage the data, analyze it and obtain information that allows us to make more exact decisions, be more proactive and be prepared for different scenarios within an organization.
What do I do to implement business analytics in my company? First, you need to know the business and the company where you are working, second, you need tools, this, in addition to hardware, is the software that allows statistical analysis and identification of patterns in the data. And finally, you need a structural methodology that allows you to polish all these elements to put it into practice for your company.
First you need to define the problem, and focus on that problem with an objective. This objective may be focused on improving the relationship with the client, on improving the daily operations of a company, on improving the management of risks or looking for new investment opportunities. It is possible that in your company there is already a hypothesis about why the problem exists and then, with our data analysis, what we are going to do is discard or reaffirm that hypothesis or we are going to find a new solution to the problem. Four stages exist during this process: manage the data, carry out the analytics process as such, generate a visualization for the users or collaborators of the company when they need it and finally how we can integrate the things we discover into the daily operations of the company.
As an example:
Suppose there is a pharmaceutical company and it has historical data on the driving history of its carriers, average speed, sudden acceleration, turn on-off events of the units. On the other hand, it has the data of the fines generated by the operators of each unit. And on the other hand we have the data of theft of merchandise or transport units. So, let’s imagine that, in this case, the pharmaceutical company wants to predict its expenses on insurance policies for all its foreign units, they want to know, which units may have more risk of colliding or being stolen for the policies they are going to acquire, to really cover or protect their assets and inventories and to maximize their profits. What’s next? Consolidate all the data, collect it and make an initial analysis to discard the data that works for us and to extract the data that is relevant and then move on to the tools that we have available to do the analytics process. From there we are going to generate a model and what the model is going to tell us is which units are the most stolen, who handles them and how they handle them. Based on that model, we generate a visualization and we have an interface with which the operators can work. With this what we seek is to make our processes more efficient and in addition to that we are improving the performance of the company.
With the cleaning and analysis of data, the company can be more efficient and therefore more profitable.
The abundance of data brings many opportunities and we can reap many benefits from applying business analytics technology. This can be a guideline that comes from the top management or it can even be an initiative of an internal entrepreneur who wants to obtain competitive advantages in his/her department.