Data is the new gold. Especially when it comes to supply chain optimization, companies need to be able to leverage the true power of their data if they want to stay competitive. One helpful tool for supply chain managers is a unified data model: let’s understand what it is and how to implement it.
Does your company need to rethink its data strategy?
Data is probably one of the most valuable resources today. It is so helpful that companies can’t afford to waste its potential, leaving it in siloed departments. But many researchers say it is precisely what’s happening in most organizations.
Harvard Business Review reports that data silos are the leading problem companies face when it comes to data: 87% of companies worldwide reported it as a top challenge in the implementation of their data strategy.
Executives know that data management is a must (96%), but despite this, 70% say their data strategy is falling behind. This is often due to a lack of visibility, threatening companies’ ability to leverage their data powerfully.
One of the areas in which data proves more valuable is the supply chain. Supply chain management turns data into action, but if data is siloed and fragmented, it can’t drive informed cross-functional decision-making.
Supply chain data is generally stored in different systems, owned by other functions, and used for various purposes; this makes it difficult for supply chain managers to have complete visibility of all data to maximize decision-making.
But what can executives do to solve this issue?
To achieve maximum value from data, companies need to rethink their data strategy and shift from being departmentally focused – with data stored in silos restricted to just some teams, users, or business units – to being enterprise focused. This means data is treated as a resource for the whole company, and all stakeholders can have access to it at all times, breaking down data silos, eliminating duplicate datasets, and ensuring data harmonization.
Easier said than done, but technology, particularly Supply Chain AI, comes to our aid for supply chain optimization and a more efficient data strategy.
What is a unified data model?
Unified data models are one of the best supply chain analytics solutions technology that has been unlocked for us. To use Princeton University’s definition:
“A data model organizes data elements and standardizes how the elements relate to one another.”
We can think of data models as an information hub that combines data from all sources and platforms into one place to give a complete, clear, and fully representative picture of the supply chain. Such a supply chain visibility enables effective decision-making and business intelligence.
Unlocking the benefits: why unified data models are so valuable
A modern, unified data model delivers tangible and measurable business benefits. Remember that a unified data model acts like a foundation upon which data can be correlated, combined, and analyzed consistently, facilitating the application of ML tools across different datasets.
Data scattered through the company locked in silos and stored in different formats is practically inaccessible from a strategic point of view. Without centralized storage and a uniform data management strategy, businesses can’t use their data to make informed decisions. This is why data harmonization and unification are crucial for today’s companies.
Google has listed the following as the primal benefits of unified data models:
• They allow uniform data storage from different sources. Typically, data from various sources has different formats; unified data models will enable data normalization to be read and stored by any platform and software across the company, making it easier to read and understand.
• They make supporting log types from new devices easier as long as they are compatible with the existing structure.
• They make it easier to operate on the data using standard access methods.
• They increase supply chain visibility across all stages, removing the top obstacles to effective supply chain management.
Three questions to ask yourself before implementing a new data model
Before diving head-first into implementing a unified data model, you need to ask yourself three questions.
•When it comes to data, what are your business-specific goals?
Each business has unique and specific goals, and your data strategy should align with them. Unified data is most valuable and efficient when it addresses specific needs to achieve said goals, and therefore, before implementing a new strategy, you need to begin by defining these goals and the process to get there.
•How will you handle data security and access?
According to Gartner, the supply chain is particularly at risk of cyberattacks: the forecast is that by 2025, 45% of companies worldwide will have experienced at least one cyberattack on their supply chain.
And the bad news doesn’t end here: 82% of data breaches 2023 included cloud-based data (source: IBM). This is why executives need to find solutions that provide visibility across hybrid environments and protect their data as it moves across clouds, databases, and other environments.
Before implementing a unified data model, it is crucial to identify all stakeholders needing secure access to the data and what platforms they will use. This will make finding a safe solution for data access and handling easier.
•Are you sure your current data sources are compatible?
Before choosing one data platform, ensure it is compatible with your current use. List all sources, platforms, and software currently in use and identify which ones are compatible, which are not, and which sources need to be converted. This will allow you to understand which platform is the best fit for what you currently have.
How Tredence helped a global retailer to increase visibility and reduce costs with a unified data platform
The client, one of the world’s largest retailers serving more than 100M households, struggled with low visibility (less than 50%), resulting in complex decision-making, incomplete insights, and reduced productivity.
The main goal was to move from data silos to a 360° view by creating a unified, comprehensive view of customers’ data across all touchpoints.
The approach.
To achieve the goal, Tredence harmonized and integrated more than 70 data sources with real-time updates and automatizations to process over 250 TB of data weekly.
The results?
A 14% increase in visibility across all touchpoints and $4.8M saved in costs from optimized processes and decision-making.
It’s time to make the most of your data
We live in the data era, but despite this, most companies are still struggling with siloed, ununified, and unharmonized data. This prevents them from tapping into the real potential of their data, wasting ample opportunities.
Data can be empowering, but valuable insights are lost when it’s siloed and fractured. Especially for supply chain executives, extensive opportunities for digitalization and efficiency enhancements are opened up when data from multiple sources is combined, harmonized, and processed, but to achieve this, companies need to implement a unified data model first. A unified data model can make data storage more manageable and comprehensive and supercharge data analysis and business intelligence, leading to business growth.