Stop arguing over forecasts.
Build an S&OP plan that holds up in 3 days.

A 3-day code-along on the analytics behind Sales & Operations Planning. Build the full chain (Demand Forecast → Production Plan → Materials Schedule) using retail data in Python.

Available until July 6.

75 mins each day · No prior coding experience required.

I'm ready to build the S&OP plan

Your First Name

Email

Biggest frustration with your S&OP?

What do you do in supply chain?

What happens each day

1

Forecast the Demand

Turn sales data into a 12-month forecast by identifying seasonality, comparing models, and measuring accuracy.

2

Adjust the Forecast and Plan Production

Use Generative AI to analyze earnings-call insights, adjust the statistical forecast, and translate it into production and inventory decisions.

3

Plan the Materials

Use the Bill of Materials (BOM) to translate the production plan into component requirements, order quantities, and purchase-order dates.

Your S&OP Meeting Shouldn’t Be a Battle of Opinions.

Sales arrives with an ambitious forecast nobody can fully explain.

Operations still doesn’t know how much to produce, when to produce it, or how much inventory to build.

Procurement finds out too late and has to expedite materials at triple the cost.

The problem isn’t your team.

The problem is that a forecast was never turned into an executable plan.

In this three-day challenge, you’ll connect demand, capacity, and materials from the data up into one clear S&OP plan for your business.

I'm ready, reserve my spot →

Hosted by

Stephania Kossman and

Luis Fernando Pérez

Researchers and educators driven by one principle:

Competence builds proof. Proof builds confidence. Confidence creates impact.

Together, they help supply chain professionals use analytics to replace uncertainty with clearer, stronger decisions.

Another reason to join this challenge.

The last challenge was cool. Like, really cool.

In the last live challenge, we worked through a supply chain analytics case from data cleaning to analysis, simulation, and designing inventory policies.

“It introduced the full workflow: understanding and cleaning the data, analyzing it, simulating the process, and generating predictions for inventory.”

— Alan

“The case reflected situations I’ve encountered repeatedly in purchasing, inventory, distribution, and demand planning.”

— Cristina

“The flow of materials made following along digestible. I can’t wait for the next data challenges.”

— Kendelle

Frequently Asked Questions

What will I get at the challenge?

The Python notebooks, the dataset, and a working method for connecting Demand Forecast → Forecast Adjustment + Production Plan → BOM + Materials Schedule

Will there be a replay?

Yes, for registered participants, for a limited time.

Who is this for?

Supply chain and operations practitioners who are curious about analytics but aren't specialists.

  • Demand Planners

  • S&OP Managers

  • Supply Chain Managers

  • Operations Professionals

  • Procurement and Materials Planners

  • ...

If you sit in S&OP meetings or feel the consequences of them, this challenge is for you.

Do I need to know Python already?

No. You'll follow the guided sessions even if you’ve never used Python before.

Be ready for the challenge.

How do I know if the challenge is for me?

  • You want a better answer than "last year plus ten percent." You're tired of being blindsided by shortages that, in hindsight, were predictable.

  • You want sharper data analytics skills that solve problems.

  • You want your work to influence decisions.

    Then this challenge is for you.

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