Before we move forward with the topic, I think it is important that you understand the difference between BI (Business Intelligence) and BIG DATA, and what the purpose of each is, because in the past I myself got confused and thought it was all the same thing.
BI deals with known questions and our preconceptions regarding data. Whereas Big Data involves a universe of new possibilities and questions we do not yet know.
Both are of great importance and must be well understood so that companies can make the most of them, adding value and achieving the desired business results.
The BI solution focuses on collecting, organizing, transforming, and making structured data available for decision-making, in addition to allowing predictive analysis in a fast and assertive way for organizations. They provide insights and trends to managers, so they can create efficient and effective guidelines to achieve the desired business results.
On the other hand, Big Data, in general, is less concerned with the accuracy provided in a BI system (except in specific cases or where the use of sensors is present).
Big Data focuses on processing data in search of correlations and discoveries. That is why in Big Data we will not always know the reasons for the existing correlations, as it could be something never conceived or studied before.
And therein lies the differentiator of Big Data: showing previously unknown paths and correlations in large volumes of data, in a timely manner, so that companies can gain competitive advantages.
Did you get it? So let's move forward.
In this article, I will highlight only BI, and the BIG DATA topic will be left for a future article.
I prepared a video produced by Pixar that I edited, so you can understand the resistance and objections that managers impose when implementing a BI system. Let's watch it.
Speaking of BI is no longer something so innovative when we talk about logistics; today there are already several software programs and platforms that extract these numbers from systems and provide the famous dashboards.
The central issue that I find interesting to address in this article is the limited view of this data, which prevents logistics companies from thinking a little beyond performance indicators, vehicle occupancy capacity, and damage volume.
The truth is that a BI system collects data from various sectors of a company, such as:
- Traditional corporate data from operational systems
- Traffic and weather data from sensors, monitors, and forecasting systems
- Vehicle diagnostics, driving patterns, and location information
- Financial business forecasts
- Advertising response data
- Website navigation pattern data
- Social media data
- Customer Service data
- Human Resources data (overtime costs, absent employees, employee satisfaction index, etc.).
- Commercial data such as number of proposals vs. closed deals
- Gatehouse data for access to the company.
Not cross-referencing them is like shooting yourself in the foot. We no longer lead a company following intuition, but rather with data that will help you in decision-making and process validation.
What is the use of having great delivery performance indicators if your customer service department keeps receiving complaints, if your employee is absent too much, if your logistics cost is too high, if you have high employee turnover, if your commercial area brings in many proposals and few closed deals? Did you know that market trends are brought in by the inbound channel and by your commercial agents?
Many managers still prefer to listen to what comes from the outside, the so-called "Siren song", opportunistic external agents focused on themselves and on what they can bring, extracting what is of interest and then leaving. Within logistics, this happens every single day.
Anyway, I repeat and say it again, the answers are not outside your company but inside, and it only depends on your interaction with your data and your employees to extract them.
The integration of all sectors is essential for the health of a company; it works the same way as a human body, it is no use for the heart to be healthy if other organs are compromised, as it will gradually cause damage to the heart.
The secret to the success of a BI project is the possibility of analyzing a large amount of variable, structured, or unstructured data with great precision and speed, providing managerial intelligence to the company.
It is very common that, when implementing BI, managers have some doubts regarding its effectiveness and how it should occur.
I state that, to be successful with BI, there are two key points that must be observed: planning and the adequate technological tool.
While well-structured planning helps to reduce implementation time and costs, choosing an adequate technological tool improves the effectiveness of the decisions made and generates better results.
HOW TO BE SUCCESSFUL WITH BI?
I believe there are 3 important points to be considered, which are:
ORGANIZATION
Just like in any project, the first step is the organization of all requirements to implement a strategy. This organization takes place during the planning phase.
See the main points that should be included in your planning:
• Definition of functional requirements: consists of determining which KPIs (performance indicators of all departments) will be made available by the BI applications, at what time, and in what format;
• Definition of users: we can generally divide users into three groups, which are general report users; producers and analysts who evaluate the data; and managers who determine objectives and strategies;
• Data integration and quality: integrating data correctly and without losing quality is one of the key points for a successful BI project. Verifying the operating systems where the tool can run and how the data will be accessed is fundamental;
• Choosing the right software: using trial versions to check which software best fits your company's needs is fundamental, as it prevents the company from hiring a very robust and more expensive software when it will not use all the offered features;
• Limitation of execution time: by defining a deadline for the execution of a project, you demand a more intense concentration from the responsible sectors involved. This data limitation avoids postponing the actions necessary for the implementation of the project;
• Project maintenance: the market and the reality of companies change constantly — which also happens with BI applications. Constant updating and optimization of applications is a must.
APPLICATION DESIGN AND LAYOUT
In addition to the technical requirements for choosing an application, one must observe its design and layout issues.
The application must make data available in a simple and easy-to-understand way and enable the generation of reports with typography and color palette standards, in order to provide a complete and objective user experience (UX).
The charts generated in the reports must follow a color logic and present the information in chronological order or respect a sequence of events or processes, in order to facilitate the understanding of whoever is interpreting it.
In addition to these points, it is important that the application provides various types of specific charts for each type of analysis, such as a SWOT matrix, a BCG matrix for product or service analysis, and a benchmarking analysis board.
IMPLEMENTATION
After completing all the planning and defining the BI application to be used, the time comes for the implementation of the project itself. This process requires a few basic steps:
• Mobilization of those involved: the active participation of all directors and managers in the implementation of BI is essential, especially from high management, as only then will the project succeed;
• Information gathering: here, it must be determined which information should be made available to managers for performance and market analysis;
• Mapping of data sources: this mapping aims to identify where the information will be extracted from and analyze the feasibility of the information requested in the previous step. These data sources will feed the BI application.
• System construction: construction is, without a doubt, the longest part of the entire implementation process of a BI project. Data extraction, quality analysis, loading, and testing are performed in this stage.
• Availability to users: this is a very delicate stage, as it is when the resulting product is delivered. This stage must also include all training and qualification of users, so they can use the tool in their daily routine for decision-making.
WHICH ERRORS TO AVOID?
Even with a well-structured planning and a well-done execution, there may be some errors that must be avoided at all costs. See some of the most common errors that occur during the implementation process of a BI project:
LACK OF PLANNING IN IMPLEMENTATION
When implementing a BI tool, it is essential to define what the company's objectives are in making this investment and how this solution will contribute to achieving the expected results.
For everything to work, one must have a systemic view of the company, understanding how each resource contributes to and feeds the Business Intelligence.
UNDERUTILIZING THE SYSTEM
One of the most common errors is underutilizing the system. This occurs when the team has not been properly introduced to the tool and is unaware of its importance and operation.
This lack of preparation results in data scattered across various spreadsheets or other systems. It is very common for the most used feature of BI to be the "Export to Excel" button, and each user starts building their own analyses in Excel instead of incorporating them into the BI.
NOT PAYING ATTENTION TO DATA QUALITY AT THE SOURCE
One of the premises for a successful BI is the quality of the source data; however, systems often lack basic validation rules, making the loading process to the BI a major challenge. Blank fields, incorrect values, or differently spelled terms can distort the analyses.
The BI will show exactly what is in the database and, for the analysis to be used to its full potential, in most projects it is necessary to adjust data at its source.
LACK OF INTEGRATION WITH OTHER TOOLS
The BI must communicate with all platforms used to collect, process, and analyze data from a series of sources, such as TMS, ERP, CRM, Project Management, or other tools used by your company.
Special attention must be paid to the connectors available in each tool; some have few options, while others will charge an extra fee for each type of connection, forcing the user to export data manually to later load it into the BI.
By not integrating these tools with the BI, there is a loss of the ability to cross-reference data and analyze this information.
For your BI project to succeed, it is mandatory to have a properly qualified professional who understands how the tool works to assist in the information integration process.
This professional will check if people are using the system correctly, if the team understands the importance of the data analysis process, and if more training is needed.
Where should I start to generate a BI in logistics?
In addition to all the benefits of BI within your logistics company allowing for more assertive decision-making, which were described above, there are also those benefits that are seen as a competitive differentiator that should feed your clients' BI.
Yes, feeding your clients with easy-to-access, fast, and reliable information will increasingly be the name of the game in this market.
Some operational staff still resist these changes because the lack of information hides their inefficiencies, but for how long?
Sending data that supports your clients' planning will allow the operational relationship to mature, and only then does Logistics 4.0 start to make sense for many companies that believe this reality is still far away in Brazil.
And how to do this?
Map and review your operational processes
Remember that the less human interference, the lower the possibility of errors.
Gradually migrate to a digital model; companies with obsolete processes, which insist on completely analog and manual management models, may find it difficult to adapt to this new moment.
For the manager who wishes to boost their company's results, it is very important that their work processes are known and reviewed, seeking to optimize and automate as much as possible.
Invest in communication with your shippers and clients
It is no longer acceptable to exchange order information, transport occurrences, and freight status by email, and manually enter information into systems. Therefore, the tip is to invest in technologies such as EDI (Electronic Data Interchange) and Webservices (a solution used in system integration and communication between different applications), which are capable of integrating shippers, carriers, and other partners (including suppliers and clients), avoiding rework, reducing costs, preventing errors, and accelerating work.
Integration is the key word for adopting the most modern logistics practices in your company. This connectivity facilitates management and allows complete control over processes.
Connect your fleet, drivers, and third-party contractors to the base in real time
If a vehicle is not following the planned route, the manager can intervene immediately in the fleet. In the same way, if a certain driver is showing poor average fuel consumption or inappropriate driving patterns, tracker technology integrated with fleet management systems allows evaluating them individually or as a group through analyses and statistics.
If any abnormality occurs in the transport operation, such as a mechanical failure or cargo theft, new technologies allow not only notification to the company and vehicle monitoring, but also remote shutdown of the truck.
Invest in Yard Management and occurrence logging
If you are a logistics operator with a fast-paced operation, where your clients demand agility in loading and unloading, and occurrence logging with a high level of information, there are already solutions on the market that, in addition to understanding how long a vehicle remains stationary inside your DC, also make it possible to formalize occurrences of damages and shortages in real time.
Structure smart and more efficient warehouses
I agree that talking about automated warehouses is still a bit distant from Brazilian logistics, but using BI to understand forklift movement and quantities of handlings is very real and within your reach. Better evaluating in which positions the fastest-moving products are and storing those with higher added value more securely seems obvious, but it is rarely evaluated in the chaos of Brazilian warehouses.
Using companies to perform inventories using drones is another reality that is very slowly starting to become part of the logistics market, but it allows not only agility but also labor savings and less interruption in operations.
Create a routine and culture of data-driven management
Given the large volume of data and information made available by new technologies and systems, the conditions arise for interested managers to analyze their companies from various aspects, and from there make the best decisions, reducing costs, improving delivery times, and serving their customers better and better. But for this, it is essential to create a culture within the company of following a routine of analyzing the reports and data generated by the systems frequently.
You can already see that Logistics 4.0 is an ally of efficient work and can even boost the safety of your employees, processes, and assets, right? This novelty is not a prediction for the future: it is an undeniable reality that needs to be leveraged as much as possible by the modern manager.
I believe I have demonstrated the importance that data has within logistics, and that specializing in analyzing it will be the great differentiator among companies.
Do not resist what can change the future of Brazilian logistics and, most importantly, that of your company.
Those who are at the forefront of these analyses will discover the best path and become increasingly competitive to compete with those who chose to adopt innovation as the main instrument to achieve results.
Until next time.
what if I want to create my BI with open source software?
"BI deals with known questions and our preconceptions regarding data. Whereas Big Data involves a universe of new possibilities and questions we do not yet know."