With industry 3.0, digitalization and information systems start to be an imperative to be in the market. Right now, industry 4.0 is progressively revolutionizing industries with access to real-time data, connectivity and computational power.
However, thinking that is necessary to gather an enormous volume of data before performing analytics is merely a myth.
From services to manufacturing, every company deals with resources and how to capture the best out of each one. Data analytics provides a set of tools that helps to build a tangible understanding of business processes and better utilization of each resource. Reports and dashboards are the simplest and the most used tool to keep track of each process.
Despite being a basic principle of management, by leveraging simple information into a set of KPIs enables companies to detect and keep on track their business.
From an operational perspective, monitorization is powerful to track historical decisions but it is not as powerful to foresee better resource allocations or act before more complicated issues arise generating inconvenient situations. Simulation and optimization models are perfect examples of how to overcome this difficulty.
By having the possibility to test different set-ups, simulations models specifically tailored to the business problem allow companies to forecast the performance of each KPI without an impact on operations or costly investments. With the possibility to anticipate and analyze each problem, archive better results and improve cost efficiency is much easier. Additionally, optimization models step-up the game by proposing optimal solutions for complex problems like production planning or delivery routes.
Simultaneously, from a marketing and sales perspective, data analytics is core to help companies target customer needs and focus their effort to connect the best products with the best communication.
Although, the other marketing principles like price or promotion will also benefit from better data analytics, being able to have clear control of what are the causes and actions of each resource is core to exploit the best out of each one.
More than numbers, advanced analytics must be ingrained within the company culture and should be fostered from the top. Currently, the challenge with this era is not how to gather the data or select the best tool to analyze it (there are a plethora on the market), but how is data backing up decisions within a company.
In a competitive environment not leveraging data is fatal, as is not having everyone on the same page regarding company metrics.
Data analytics is one more tool to get everyone in the company within the same page and following the same goal, whereas that goal is empowering growth, or improving overall company efficiency without misalignment or gut-feeling decisions.
Leveraging tailor-made data analytics such as statistical models or machine learning algorithms to increase client knowledge, optimize pricing strategy or improve resource utilization when doing production planning or inventory management is a sure way to increase a company bottom-line profitability.