Category: AI in Supply Chain

Revenue at Risk

Ops leaders struggle to assess customer demand related risks in real time. This increases revenue risk. This is a bigger issue amid rising uncertainties like tariffs and inflation (circa 2025). Learn one of the many ways how Zyom helps customers such as Cambium Networks tackle Revenue risks.

Most Operations leaders can’t answer in real time, or even near real time: 

Which portion of my planned customer demand is at risk this quarter?

Which orders are at risk?

“At risk” here implies a significant likelihood that customer orders would not materialize, or even if it does, cannot be shipped on time.

Changing signals make it impossible to get demand and supply plans aligned, even using well-crafted spreadsheets and sophisticated, but siloed systems — planning cycles drag, errors creep in, critical Revenue and cross-functional meetings and forums (such as Sales & Ops Planning or S&OP) result in more unanswered questions, and by the time the risks are visible, revenue is already slipping away, or worse (orders lost to competitors).

In times of “garden variety” uncertainty these questions to uncover risk are hard to answer. In an environment of high uncertainty such as now (starting circa Q4 , 2024, to late Q3, 2025 in the US), identifying demand risk has become increasingly frustrating. Largely due to tariffs and pressured trade relations which directly impacts significant trade volumes from partners across the board (larger partners such as the EU, Japan, South Korea, and relatively smaller ones like Vietnam), these risks have increasingly grown for US based product companies. And this without taking into account the slowing employment picture and persistent inflationary trends which, in many industries, is already dampening if not damaging demand.

Branded product manufacturers like Cambium Networks cut planning cycles by 60%-80% and gave key executives and operating team members direct line-of-sight into supply risk with Zyom, starting in 2017. Their SVP of Ops called it “a system that brought our vision to fruition.”  Cambium continues to partner with Zyom as it navigates demand corrosive uncertainties.

If you can’t see revenue at risk until the quarter’s target is already slipping, and key operating team members are scrambling to get supply inbound, you’re too late.

Key Questions for COO and Operations team

  1. What is one key system capability from a supply Operations standpoint that companies such as Cambium need to ensure they spot revenue risk as early as possible? How should this capability evolve?
  2. What is one valuable decision prompt that the system can automatically provide to speed up decisions and actions from Supply Operations? This was not technically feasible prior to the advent of the newer generative AI technologies (late 2022 ChatGPT launch). i.e., traditional Machine Learning approaches till the public advent of GenAI (LLM) technologies.

To find out more, drop a comment here, or email us at: products@zyom.com

Sources & Acknowledgement: Zyom’s Cambium Networks Case Study.

John Duvenage provided key inputs to structure and composition.

Disclaimer: Generative AI was not used for composing any of the writeups on this site (including this one). GenAI was used to generate the pictures in this article and for content summarization. At this point of time, there is no plan to use GenAI to generate new content on this site. Readers will be informed in advance if this changes.