Supply chains are riddled with growing complexity, global volatility, and relentless pressure to deliver faster, smarter, and more cost-effectively. Amid the challenges, data is the essential enabler – the fuel that powers supply chain planning to build agility and resilience.
In a recent blog, The Data Your Supply Chain Can’t Survive Without, we explored the critical role of external data; everything from economic shifts and weather disruptions to changing consumer behavior and global logistics challenges. Since external signals tend to have more of the spotlight, many organizations overlook one of their most valuable assets: internal data.
So, let’s shift the conversation inward, and explore the often-underutilized data that lives within your organization. Internal data holds tremendous potential to drive smarter, faster, and more aligned decision-making across the supply chain. Yet too often, companies focus solely on ERP data while overlooking the broader ecosystem of data available across their operations.
You Don’t Need Perfect Data to Get Started
Before we get started, let’s address the data elephant in the room. One of the most common blockers to tackling advanced data-driven planning is the myth that data must be flawless. But remember – perfection is often the enemy of progress – and you are currently planning with that bad data.
Jennifer Stark, Director of Planning at 1440 Foods, shared this valuable insight during the recent webinar Fueled for Growth: 1440 Foods Supply Chain Transformation Journey. This innovative brand shared its journey building an end-to-end, vertically integrated supply chain, while leveraging the right mix of people, process, advanced technology and data to navigate change and connect teams to streamline their manufacturing planning. As they set the stage for scalable growth, Jennifer said:
“We’ve really learned that you don’t need perfect data to start. We were able to revise and update data as we went. We started with some strong assumptions around shelf life or around lead times and MOQs (minimum order quantity) and used that to just plug into the system to start seeing how it works, knowing that we could go back and revise later.”
Jennifer Stark, Director of Planning at 1440 Foods
This crucial piece of advice is centered around an iterative approach that allows businesses to move forward without being paralyzed by data gaps. Initial assumptions can be replaced over time with more refined signals, including historical patterns, similar product attributes, and eventually, live data streams.
Where data is missing, artificial intelligence approaches and machine learning techniques can help fill the gaps. Advanced imputation techniques, such as K-Nearest Neighbors (KNN) clustering, Regression, and Deep Learning can infer likely values for missing data based on data characteristics of similar SKUs, Customers, Suppliers or correlated attributes. AI can take these efforts even further, by capturing complex relationships as well as detecting and adapting to different missing data patterns.
As you begin incorporating more internal data, it’s important to build a strong foundation around data management, usage and data governance – but that doesn’t have to happen all at once. Focus on monitoring and improving data quality over time, making steady progress rather than waiting for perfection. A flexible platform and iterative mindset go a long way in helping your data maturity evolve alongside your planning capabilities.
Moving Beyond ERP
For years, supply chain teams have leaned heavily on enterprise resource planning (ERP) systems as their only source of truth. Modern planning demands more. ERP data alone is no longer enough to fuel the kind of dynamic, forward-looking decisions today’s supply chains require.
To build a more complete picture, companies must unlock the broader ecosystem of internal data spread across the enterprise. This includes:
- CRM Data. Uncover customer trends, preferences, and additional demand signals like risks or upside opportunities to include in demand plan or in scenario-planning.
- Pricing and Promotion Data. Anticipate the impact of price shifts and marketing campaigns based on historical price-elasticity as well as calculate more robust financial forecasts in IBP and S&OP processes.
- Trade Promotion Systems (TPS). Align supply with upcoming market activities and retailer commitments to accurately supply and support promotions.
- Manufacturing Execution System (MES) Data. ERPs traditionally bring in a single point of machine run rates and usage then perform monthly ‘true ups’ which handcuff supply chain performance. Create more attainable Master Production Schedules by linking to real-time visibility into production capacity, material usage and operational assumptions.
- Visibility Data. Enhance planning with live shipment ETAs and movement insights.
- Transportation Management System (TMS) Data. Provide near-real time updates to shipment data and replan as needed across supply chain. Additionally, provide insights into rate variability, route efficiency, and service reliability across different scenarios and financial trade-off analysis for investments, responses, and risk management.
- Supplier and Supplier Shared data. Bring supplier Terms and Conditions, Blanket Orders, Site details plus shared data such as production plans and inventory levels.
- Customer Shared Data may include additional product features, point-of-sale (POS) data, inventory levels, order policies, as well as retail data like shelf space and more.
- Product Lifecycle Management (PLM) and E-commerce Systems contain many additional, valuable product features and insights into customers and behavior to leverage during planning efforts.
- And so much more!
The goal is to create a unified view across all relevant internal systems like CRMs, financial software, TMS, WMS, MES, PLM, and even data lakes or private clouds – to fuel more dynamic, accurate, and responsive planning models. At the same time, you want to eliminate the swivel chair approach – jumping from one system to another to view and act on your data. All of this should come into an integrated view of your supply chain planning environment.
Unlocking Internal and External Data with the Atlas Planning Platform
To harness internal data at scale, businesses need a platform that can seamlessly connect, cleanse, and contextualize data from across the enterprise. That’s where the Atlas Planning Platform from John Galt Solutions outshines.
Atlas supports effortless ingestion of both internal and external data, bringing together ERP, CRM, MES, WMS, financial systems, and more into one intelligent planning environment. Atlas empowers planning teams to enhance visibility and decision making throughout the supply chain through strategic integrations with partners like Optilogic for supply chain network optimization, GE Vernova’s Proficy Smart Factory MES for seamless integration of MES data into supply chain planning, and Shipwell, for unified transportation management and visibility.
The platform also includes built-in tools for data quality scoring, tracking, and hierarchical inference, giving teams the confidence to move forward, even when data isn’t perfect.
You can start now by leveraging what’s already available inside your organization. With the right approach and the right platform, internal data holds the potential to become a strategic advantage.
We help companies like yours turn that vision into reality. Let’s have a chat about how we can help you harness more diverse datasets and turn your internal data into an asset for differentiation, while empowering continuous improvement.
