What it really means: Democratizing the data

Editor’s note: This article launches What It Really Means, a new recurring series on Supply Chain Management Review designed to clarify commonly used supply chain terms that often carry different meanings across organizations. The series aims to establish practical, shared definitions by grounding terminology in real-world planning and execution use cases. The series is authored by Andrew Byer, a former P&G supply chain leader, and Mike Dobslaw, who leads EY’s Supply Chain Planning Practice. New articles in the What It Really Means series will publish on the second and fourth Thursdays of each month.

A term often used in discussions on digitizing the supply chain is democratizing the data. But what does that mean in real-world, practical applications?

First, relax—democratizing the data has nothing to do with politics. In supply chain systems, there’s no such thing as blue data, red data or even purple data! What democratizing the data means is ensuring those who need the data (to plan, make decisions, track or adjust) have access to usable, quality data.  

The key point of democratizing the data is ensuring frontline planners/executors have access—on demand—to quality data in real-time. The key change is moving away from data being an IT or data-scientist-controlled asset and moving to data as a business asset available as needed, across the organization. This makes it democratized. Sounds simple, right?

 

Why is democratizing the data important? To optimize supply chain performance, a business needs planning and execution based upon the best available information. This information is translated into systems via coding that makes it data. This data can then be used in algorithmic calculations. Let’s use planning as an example of how this plays out. Planning is a set of decisions: what am I going to make, how much, when, using which resources, which materials, where will it ship, etc. Planning is typically a ‘frontline’ task, undertaken by employees using transactional systems. Planners are also accountable for monitoring executional performance vs. plan, including intervening if a gap exists between plan and actual performance. The data needed for monitoring execution are real-time tracking and control information (e.g. status of materials en route to the plants, production status, quality status, etc). Often, though, it does not exist in a form (or timeframe) available in transactional planning systems. Therefore, a planner needs access to operational data—wherever it exists in a company’s system architecture. This is where system design, access, and storage become factors in whether data is truly democratized. A simple test to know if your organization’s data is democratized: do the people who need specific data for their roles have a direct way to access that data as/when needed? 

The benefits to democratizing the data: In a high-performing organization, accountability for results is owned by the frontline employees—e.g. planners, manufacturing and warehouse technicians, etc. To empower and unleash these frontline employees, they need the tools to succeed. In this case, having the right data—accurate, current, readily available for planning, decision-making and monitoring status—is a key tool. The benefits show up in areas like:

• Plan quality
• Ability to execute the plan by operations
• Productivity: reduced time and touches in planning and operations
• Shift from reactive ‘fire-fighting’ to more proactive value-added planning activities
• Increased ownership for results and job satisfaction (“I have the tools to do my job”)

Watchouts: Unfortunately, there can be many intended or unintended barriers to democratizing the data, including:

• Systems design
• Organization security controls/limits
• Data accuracy and quality
• Timeliness of data availability
• Data storage for use on demand

How to get started democratizing the data?

You may be thinking to yourself “how can I even start to think about using data as an asset in this way—my planners don’t even have the time to clean their master data, let alone have the space to use data in a proactive way?”

A key to democratizing the data is to recognize the role of supply chain leadership. Leadership’s role is to eliminate the barriers facing the frontline employees imperiling their results. So for democratizing the data, the first step is to define data needed for a specific supply chain task (e.g. using a manufacturing production scheduling example, it’s important to know if materials will be received on time, and therefore what are supplier X’s typical shipping method and transit time ranges). The second step is to ensure this data exists, is accurate, and structured in a way that users can extract and use on demand for planning/execution systems. In this example, a leader should check that their planners have access to all the data they need to create valid material supply plans and monitor them. Importantly, it’s required that planners are trained (1) where to find and (2) how to access the data, and (3) how to use tools to extract/transform/load the data to be usable in analysis and decision-making in transactional systems, visualization dashboards, and other planning and control tools. 

About the authors

Andrew Byer is a former P&G Supply Chain Leader. Mike Dobslaw leads EY’s Supply Chain Planning Practice.  To learn more about how EY and P&G team to support supply chain transformations please write [email protected]

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