When Supply Chain Data Doesn’t Tell the Whole Story
Breaking Down Data Silos: How Better Visibility Drives Digital Transformation in Supply Chain
After working on digital solutions implementation with highly regulated industries focusing on manufacturing & supply chain teams, I've noticed one problem that keeps coming up:
- Teams have data.
- Systems have data.
- But the people who need it don't always have the right visibility at the right time.
Procurement looks at suppliers and lead times. Logistics tracks shipments. Inventory teams work with returns, stock levels and warehouse information. Sales looks at demand and customer requirements.
Each team has part of the picture.
Discovery and pre-discovery sessions have been one of the best ways I've seen to uncover where that picture breaks down.
Sometimes the requirement is a system enhancement. Sometimes it is a manual process that needs to be simplified. And sometimes, the real issue is that two teams are working with different information.
Where the technical side comes in
My work has often been at the intersection of business requirements and technology.
On the Salesforce side, I've worked with products, price books, product configurations, and business processes-understanding how what the business wants translates into an actual system setup.
On the SAP side, I've worked around supply-chain processes and digital solutions, including discussions with architects around how systems, data, and processes can work together.
That experience has changed how I look at requirements.
A request like "We need better inventory visibility" is not a complete requirement.
I want to understand: Where is the inventory data coming from? Who owns it? When does it change? What other system needs that information? What prevents the user from seeing it today?
Then comes AI
Once the underlying data and processes are connected, I think the hyper of AI becomes much more real and interesting.
Instead of another dashboard showing inventory levels, could AI help identify why inventory is unavailable?
Could it connect a shortage to a supplier delay, demand change, inventory in another location, or a compliance constraint?
That's where I see the opportunity-not replacing the systems already in place, but making the information coming from them more useful and actionable.
What I've learned
Good digital transformation starts before the solution is built.
It starts with listening to the people doing the work, understanding the process behind the requirement, and then figuring out where SAP, Salesforce, data, automation, analytics, or AI can genuinely make that process better.
For me, that is where business analysis becomes technical: understanding the business deeply enough to design better technology around it.
What do you see as the bigger challenge in your supply chain-access to data, connecting systems, or actually turning that data into decisions?
