Let's make it real about Master Data Planning: Garbage in, Garbage out

May 24, 2024 by
Let's make it real about Master Data Planning: Garbage in, Garbage out
ABI-VNM - Abivin Vietnam, Phạm Nam Long
| No comments yet

Success with master data planning is essential. It is at the core of serious inventiveness in several businesses today. Whether your company is devoted to providing products focused on the customer or operational excellence, master data planning is vital for success, and the rate of success is heavily dependent on how you manage your data and its essential duties.

Garbage In, Garbage Out

Route planning software is a superb technique for enhancing your commercial business operations. But before planning to implement one of that software, you have to possess the key component: Data. The famous term "Garbage In, Garbage Out" implies that the information quality you put into the software is directly equivalent to the output.

the quality of input data decides the equivalent outputs
The quality of input data decides the equivalent outputs

Garbage in, garbage out means bad input data yield bad output/garbage. So the use of excellent master data planning techniques with practical forecasting and a strong overall method is important in ensuring you get the best output. In business-assisting software, poor data input quality leads to an ineffective result. Like any other automated device or software, the outcomes you can imagine are largely dependent on the value of the data the planning software you choose. Consequently, bad data leads to negative impacts: missed opportunities, lost revenue, etc. Having a plan to obtain, store, and make use of data ensures you make the most out of your available resources.

The importance of data quality

As technologies like artificial intelligence, automation, and the Internet of Things are changing many businesses, master data planning and data management are becoming more significant than ever. Inadequate data is among the major challenges encountered with logistics operations, and systematizing the planning process is not a bad idea going forward.

Master data planning and data management builds up data quality
Data quality is very important in logistics

Any planning and distribution forecast software is only as important as the value of the data provided to it. This is particularly true of routing software where the possibility of getting the wrong outcome is heavily dependent on how good the data is. The precision of your data could take your business far forward, so it is worth understanding the processes you can set up to accomplish that now.

Superior data leads to a healthier decision-making process and boost output. In the early stages of master data planning, it is significant to authenticate and confirm the data to be used. Shared aspects of an available driver, car size, and the precision of client location, form part of the important data that routing software will rely on. Extra factors like speed level, recognized congestion hotspots, and acceptable delivery times are also crucial. Like much other software, Abivin vRoute can only save your time and cost if the data you input is of high quality.

What should you do?

Companies should make sure to provide excellent master data for software usage. If you presently have a system in place to collect data, you should focus on improving this service. One alternative you can consider is having an Order Management System. Below are some steps to take in situations where master data planning is needed:

  • Make sure data is organized and easy to access

You should ensure your data is organized and easily accessible. You can also make use of ERP or software that focuses solely on organizing data. Route planning software like Abivin vRoute can connect and synchronize with most ERP in the market to make sure effective data flow between the two systems.

  • Ensure effective data planning: plan to reality

Ensure effective data planning to reality, not made-up. You have to make sure data can flow without difficulty between systems in your company. The failure to systematize data transfer between your company's vital applications not only slackens the process by taking input data through manual techniques but also can lead to human error.

  • Evaluate, Revision

The need to evaluate, revise, and plan which data is important to your business in real-life situations of operation is a must. A poor evaluation or revision will only serve to upset your employees, discourage delivery within certain routes, and lead to unsatisfactory clients with missed deliveries. With proper evaluation and revision, you can avoid any failure to see Return on Investment (ROI) from your master data planning project which really should be attainable within a fixed period of going live for most processes. Permitting genuine factors such as available car or driver, predictable traffic circumstances or delays at client locations remove the likelihood of a whole plan having to be ripped apart during implementation due to just one mistake.


Every master data planning undergoes a cyclical process of change, and numerous factors are affecting your business as it grows. How you approach or choose to deal with the situation matter a lot. Observing these changes and shifting your plan to accommodate them is an essential part of the planning cycle. Steady evaluation, revision, and reporting of real performance are significant to enable you to redefine further and alter your plans. The importance of evaluating master data planning plans, revisions, and operations to every business all boils down to growth, improved customer delivery, and services.


1. http://www.b-eye-network.com/view/4882

2. https://www.edq.com/glossary/data-quality-importance/

#bigdata #datamining #datamanagement #AbivinvRoute #AbivinVietnam #AbivinvRoute30 #fleetmanagementsoftware #routeplanningsoftware #routeoptimizationsoftware #Operateyourbusinessmoreefficiently #english

Sign in to leave a comment