We all know, to a greater or lesser extent, that we are experiencing a growing digital transformation that deepens the automation of tasks in the different business processes of a company, using information technology as a tool. With this we are not only looking for cost reduction but also for the improvement of the organization in general in order to make a good decision making.
Three technology drivers that directly influence the digital transformation of enterprise decision making:
- More available data (Big Data): Both the amount of data we produce internally in our companies (sensors, logs, databases, ERP, CRM, etc.) and those that exist on the Internet (social networks, IoT, data providers, etc.), we have within our reach the possibility of obtaining more information and knowledge than at any other time in our history.
- More processing and storage capacity (Cloud and IaaS): The emergence of the cloud allows us to have more IT infrastructure resources available in a more flexible way, reducing the initial cost of an investment in this type of technology.
- More sophisticated algorithms (Machine Learning and Artificial Intelligence): As a consequence of the greater amount of data available, the use of machine learning algorithms as tools for data mining and predictive analysis applied to the business world is becoming more popular.
Applying these three technological factors to the company’s decision-making process will allow us to make more objective decisions, maximize the chances that the decision will be the right one and, at the end of the day, automate management processes in order to save costs and time.
And how do we manage data?
It is worth noting that we now treat data as an asset, we have discovered a new world thanks to technologies that allow us to analyze data in two ways:
- In a massive way and this is the ability to use the information we obtain not only for decision making, it allows us to learn to sell new products, new designs, attract new customers, new strategies, … in short, build new business processes thanks to a good data analysis.
- To extract value (sell the data), increasingly common, there are companies that are dedicated to obtain direct economic gains.
How does Big Data affect logistics?
Below, we analyze the 5 V’s of big data applied to logistics:
Volume: It is important to have a good technical department at your disposal that allows you to store all the volume of data you need, a logistics operator has a lot of information to process and measure daily (output lines, inventories, times…).
Speed: It is important to know how to interpret data in a fast way so that effective decision making allows you to anticipate problems. In logistics, we make many operational decisions every day: increasing workloads, improving productivity or changing processes.
Variety: The origin of the data comes from a wide range of tools (GPS, cameras, WMS, etc.), for this reason it is important that the data collected is well structured, otherwise you will have to structure it and the success of this is to be able to put some data with others.
Veracity: The data that are collected must be valid, the data must be thoroughly cleaned and analyzed to verify that they have the desired quality.
Value: This is one of the most important points, companies need to know the value of the data they extract and what they are going to use the data for.
What is clear from this analysis is that Big Data helps us to improve the efficiency of processes throughout the supply chain and not only by looking at a past analysis to fix the future, but we can also rely on this analysis to predict the future. It is important to have all logistics processes analyzed, to know how to measure them and to be very clear about your level of quality with respect to these, added to the fact that they have become increasingly complex due, in part, to the increase in road traffic, the delocalization of stores, the increase in energy costs, the increase in E-Commerce demand, the complexity of a last mile with increased sustainability and pollution needs in cities and, finally, the different and changing normative regulations on the sector and this without taking into account the current economic-social situation.
In short, with data analytics you can achieve efficiency, making a better stock control, getting optimal routes, having controlled the fleet of vehicles, knowing where we have each product or even having segmented the demand of our customers.
Take advantage of the benefits we offer your business, for more information you can contact us at email@example.com.