Organizations operating in asset-intensive industries must juggle complex and dynamic MRO (maintenance, repair and operations) supply chains to keep their assets up and running. From spare parts to maintenance supplies and other consumables, MRO materials generate vast amounts of data from various internal and external applications, equipment and systems. The data’s sheer volume and complexity can be difficult for companies to manage effectively, let alone leverage for insightful decision making.

With the rising use of analytics and internal business mandates encouraging data-driven decisions, the quality of MRO data has become more critical than ever. Without an accessible central database, housing clean, standardized and enriched MRO data, companies face operational risk – jeopardizing everything from parts procurement to asset reliability to cashflow. This is where MDM (master data management) comes in.

MDM ensures stakeholders have access to accurate and standardized parts data along the MRO lifecycle, to inform decision making and reduce supply chain uncertainty. And if the past few years have taught us anything, it’s that we must never take the supply chain for granted.

Bad data is bad for business

Inaccurate inputs lead to inaccurate outputs, meaning poor decisions, wasted money and reduced productivity. MRO data can often be fragmented, inaccurate or duplicate. Here’s a common example: a certain bearing is defined differently in the system by three different employees, each using a different stocking location. And the issue becomes exponential when such duplication occurs across your catalogue of 50,000+ spare parts.

In this scenario, gaining an accurate 360^◦ view of your MRO parts inventory and lifecycle would be impossible, making it harder to mitigate risk and make profitable decisions. Such mistakes slow down the supply chain, bloat inventory, tie up cash flow and require extra effort to fix. Sounds like a nightmare, right? That’s where MDM comes into play.

Many organizations lack a structured process for cleansing, aligning and enriching their data, all while ensuring appropriate governance policies, procedures and guidelines are in place to keep the data clean. Supply chain managers often have little experience with (or time/budget for) in-depth data analysis and governance, and it often becomes a question of which department even owns the data.

Assigning a data owner is often avoided due to the associated liability. On top of that, many executives are unsure about the data their companies collect. They may lack vision for how to use the data to make better decisions or be skeptical of the data’s accuracy due to errors or inconsistencies. While 90% of business leaders believe data literacy is crucial for success, only 25% of employees feel confident using their company’s data, according to Harvard Business Review.

So, what’s the best way for your organization to gather, manage and share accessible MRO data? And how can that data be better used to gain insights and create business value? Master data management. Particularly for industries that need to maintain robust and healthy spare parts supply chains, such as mining, forestry, automotive and pharmaceutical, proper MDM is crucial.

What is master data management?

The basic requirement for all MDM programs is to keep information up-to-date, accurate and consistent across the organization. MDM encompasses how data is collected, recorded, stored and analyzed from across internal and external data sources and then put in a single master record. It not only ensures trustworthy and accurate MRO data is on hand, but also that this critical data can be accessed quickly and easily by key stakeholders.

The best way to get started is by working on smaller data sets by plant, country or language, then expanding out from there. Companies are realizing that if they don’t have uniform data living in one place, it’s a big issue.

Good MDM also relies on governance and standards, to ensure that the data is of high quality when collected and remains accurate when updated. Without reinforcing these guidelines, master data will deteriorate, rendering insights less valuable and making the investment of time and money to implement MDM less effective.

MDM ensures all your item descriptions adhere to a defined taxonomy, aligning and enriching all to a common standard. It also offers other advantages:

• Keeps your data in line with rules to reduce the risk of data being stolen or lost
• Enables you to make data-driven business decisions
• Improves your ability to forecast demand
• Contributes to a more agile and resilient supply chain
• Automates tasks so you can save time and money
• Increases overall part availability, maintenance productivity and asset uptime

The list can go on and on. Ultimately, it comes down to your unique business requirements and goals. For example, do you want to streamline supply chain processes and improve inventory practices? Are you trying to eliminate data silos and unify data across multiple channels? MDM is designed to tackle specific challenges like these that align with your goals.

MDM and MRO Optimization

Overall, master data management requires you to prioritize the business outcomes most important to your organization and tailor your strategy to protect them. If your company is like most, MRO optimization is a goal that may not have the priority it deserves. Yet unreliable MRO data can be harmful to your business.

When it comes to assets, organizations expect lowest total cost of ownership, while ensuring high asset availability. This puts you under pressure to reduce costs, free up cash and improve operational efficiency. Striking a balance between working capital and operational effectiveness with part availability is critical. Taking a master data management approach can help you achieve this balance.

How an MDM approach works

MDM isn’t just installing a piece of technology and hoping it sorts everything out. So, what does a good MDM program look like?

Before your MDM program begins, you should build your strategy around these principles:

• Data governance: Establishing policies, principles and standards to ensure accurate and certified master data access. This is a cross-functional team process defining various MDM program aspects.
• Measurement: Measuring progress based on set goals is critical. Data quality and continuous improvement are key factors to consider when measuring progress.
• Organization: Ensuring that the MDM program has the right people in place is essential. This includes master data owners, data stewards and governance participants.
• Process: A defined process for managing master data throughout its lifecycle is critical. This means addressing the creation, maintenance and disposal of master data.
• Policy and standards: The MDM program should stick to specific requirements, policies and standards. This includes defining governance policies and establishing standards for data quality.
• Technology: A master data repository or hub is vital. This allows you to store, manage and access master data across the company.

Implementing an MDM program can be daunting, but the rewards are worth the effort. With careful planning, a commitment from all departments and stakeholders, and a focus on data quality, you can create a trusted, single source of truth for your asset data and take your operations to the next level.

Real-world success case, including increased cash flow in 60 days

A Canadian gold mining company, with an 85,000-line master catalogue, was transitioning from SAP ECC to S4/Hana. As part of this system renewal program, they were looking for ways to improve the efficiency and effectiveness of their core supply chain processes by increasing the quality of their master data.

The company worked with Xtivity to define a 4-phase program that not only satisfied their data goals, but also delivered free cashflow benefits in 60 days.

The Program:

1. MRO Health Check: Transactional data analysis, defining business case, establishing scope and level of effort

2. Inventory Optimization: Structured review and reset of the item level min/max and lead-times that drive replenishment planning

3. Direct Charge/Catalogue Enhancement: Translation of text-based “direct charge” POs to standardized catalogue item descriptions

4. MDM – Catalogue Cleanse & Enrichment: Migration of all item descriptions to a defined taxonomy, aligning and enriching all to a common standard

Key Results:

• $140M (70%): Potential reduction in free text direct charge spend (2022-2023)
• $5.1M (52%): Approved inventory decreases
• 27k items: Cleansed to standard taxonomy, including UNSPSC
• 5k items: Enriched with modifiers, attributes, categories

Overall, the company realized inventory reductions and service level improvements while freeing up cash flow by optimizing their inventory stocking parameters. A full 39% of their master catalogue items were identified as needing data cleansing and/or enrichment. With their catalogue loaded with good data, they were well positioned to make their MRO supply chain more efficient.

Get going at your own pace

Many businesses haven’t yet fully implemented data analytics to optimize their MRO. It requires significant effort, time and investment to get there. But you can start by using what you already have.

First, take inventory of your MRO data sources and evaluate their quality and reliability. Then, create clear policies and a governance framework, break down data silos and invest in MDM tools such as data integration, cleansing and profiling.

Finally, align your MDM strategy with your business goals and get buy-in from all teams across the organization before implementing changes. Assure them you have a solid plan to minimize the impact on their day-to-day business activities.

Technological advancements in MDM continue to evolve

Post-Covid, ongoing geopolitical issues are continuing to upset existing trade networks at a time when companies are hoping to stabilize their supply chains. The pandemic caused many organizations to begin or accelerate their digital transformation efforts to keep business moving forward. It has become very apparent that good data management is key to both successful digital transformation and supply chain health.

There’s a steady flow of organizations adopting MDM in order to manage and gain business insights from the masses of big data they’re collecting. The market is booming, thanks to technologies like artificial intelligence and machine learning. These technologies let you process and store a ton of information, including complex and diverse data. And you don’t have to worry about finding duplicate records or having poor data quality – these are common problems that MDM solves for you.

Mastering your master data with Xtivity

The key to making your MRO data work for you is to start with a well-designed master data management strategy, and Xtivity can help with that. Because pulling together all the pieces of a master data management strategy can be tricky, Xtivity offers a Managed Service, where our team assists you throughout planning and implementation.

The first step to processing your data is organizing and standardizing it. Xtivity starts by identifying your current data integrity status and pinpointing opportunities most beneficial to improving your master data quality. That means terminating data silos, identifying duplicates, setting up best practices, and more. With data governance in place and running the right master data management tools – data cleaning, descriptive taxonomies and visualizations – Xtivity makes data quality more straightforward and manageable.

When you have good data, you can make your MRO supply chain work better. It helps you focus on keeping your equipment productive, delivering better service, having the proper inventory and using your capital wisely. And you can achieve all of this with confidence because you know your data is accurate and reliable.

If you want to learn more about how Xtivity can help you streamline and ease the process of implementing MDM, book a meeting with one of our MRO specialists.