Good data hygiene is a foundational piece of a scalable and actionable business strategy. Understanding your master data helps create your strategy by documenting what information you have, defining goals, and improving business processes to use the data, which results in a more structured and resilient supply chain.
But to get the most from your data, there are initial questions that need to be answered: Where do you start when there is an exponentially increasing amount of data coming from new sources, both internal and external? How do you decide which data set is prioritized in your supply chain? How do you cleanse the data in a way that allows you to analyze your current performance, and prepares you for unexpected events in the future? What are the best practices to follow when implementing a master data management strategy?
In this blog post, we will identify potential roadblocks to consider and provide a definition of how to leverage master data to improve your business performance.
Roadblocks. We’ve all faced them
In an article about data utilization “Robust and continuously updated Master Data: A key ingredient for successful supply chain digital transformation,” Stephan de Barse, EVP at o9 Solutions, states that the biggest supply chain challenge to date has been the lack of visibility. The key to solving this problem is connecting to real-time data using smart analytics that will continuously update the master data. This provides an instantaneous and accurate picture of current inventory levels, operational performance, and holistic visibility of both demand and supply.
In April, we asked our Innovators Network members to share their insights on what activity takes the most amount of time when working with large datasets. 10 Innovators weighed in and 70% of them stated that cleaning the data or data quality is the most time-consuming activity when it comes to managing data overall.
Successful master data management actually starts with people
Across the business, and even within departments, employees may have different requirements to access and analyze data to arrive at their goal. These differences, and their skill level to understand the implications of master data, shouldn’t be a limitation when growing the organization. In fact, with a well-structured MDM strategy, teams can facilitate improvements in all areas of an organization and build adoption momentum by being actively included in the design and execution of your plan.
Filippo Catalano, former CIO at Nestlé, supports this concept on the F.A.I.R. data management framework which he personally applied during his tenure in the Consumer Packaged Goods (CPG) industry. He goes into detail in a recent Masters of Digital Transformation podcast to share his thoughts on building a solid data strategy, with particular attention being paid to making the data findable, accessible, interoperable, and reusable. This approach enables companies to create value from the exploding amounts of data, both structured and unstructured, in an organization to help drive better business decisions and results. By collecting, cleaning, and organizing the data and empowering people across the organization to act on the insights companies will drive greater success across all of their pursuits and projects both internal and external.
Supply chain data management platforms are tools that help us make better decisions and add more value
Most of us remember using an atlas or foldable map when driving someplace new. The map provided the dots, but it was up to the driver to determine the best route, and often there was no ability to add new information that would suggest a better route. Many supply chain operations are still working on an equivalent system and trying to compete with organizations that have invested in the equivalent of GPS technology. But there is no competition.
This new technology, or a well-executed MDM strategy, will automate the steps required to read the map. In the case of an MDM strategy, the process will be to first mine the data. Second, turn the data into insights. Third, understand the implications to the organization and identify which is the best route out of all the possible routes you could take. Then, let’s hit the gas and go knowing that you’re on the right road.
The outcomes of this strategy will be better supply chain data management and the use of planning technology platforms to manage data and all the wisdom locked within. Unfortunately, this will lead companies to achieve their strategic goals, reducing costs, managing inventory, responding to customer demand in real-time, and helping make more sustainable decisions.
Understandably, embarking on a master data management project can be daunting but with this guidance, the hope is more leaders will take the leap. By identifying challenges, investing in tools, and providing access to the right information, leaders should be confident that the results will far outweigh the risks.