Companies that were caught off guard by the spikes in inflation and tariffs a few years ago, lost market share and profit. Those who were prepared, were able to position themselves advantageously.

Uncertainty and rapid change are back. Companies need to be able to quickly respond and adjust.

For leaders managing complex product portfolios and pricing agreements, relying on manual analysis cobbled together from multiple sources will lead to slow and poor decision-making. The company will be at risk of margin erosion and competitive disadvantage.

What-If Analysis

To navigate this volatility successfully, organizations need processes and technology that enable swift, data-driven decision-making. The goal is to move beyond reactive adjustments towards proactive scenario planning, understanding potential impacts before they fully materialize. One highly effective approach is What-If Analysis.

What-if analysis is a data simulation technique used to understand how changes in a set of input variables will impact key business outcomes.

For example, a firm may need to understand the overall impact of different scenarios where country-specific tariffs, input costs, inflation, are all moving at once and unequally impact each of their SKUs. As they weigh the probability of different scenarios, they will need to know the potential impacts to things like product line margin, business unit profitability, inventory holding cost, competitor price positioning, etc.

What-if Analysis allows leaders to explore various potential future states based on different assumptions and external factors.

Real-World Example

Imagine a new 10% tariff, effective in 30 days, is unexpectedly announced on goods from Vietnam. A robust What-If model could be leveraged in the following way:

• Identify Scope of Impact:
  • Exactly which products are sourced from Vietnam?
  • Which products have raw components sourced from Vietnam?
• Timing and Inventory
  • How does this tariff apply differently to our current on-hand inventory (often valued at pre-tariff cost)?
  • How are in-transit shipments (which might clear customs after the effective date), and future orders impacted?
  • What alternative sourcing options outside of Vietnam can be leveraged?
• Margin Risk:
  • If we don't adjust prices, what's the precise dollar impact on gross margin next quarter, considering the mix of pre-tariff and post-tariff costed goods to be sold based on forecasts?
• Pricing Levers and Constraints:
  • Can we simply increase list prices?
  • How are customers on special pricing agreements impacted?
  • Do specific contracts preclude price increases for a fixed term, forcing us to absorb the cost for that volume?
• Competitive and Demand Impact:
  • Will passing the full cost make us uncompetitive, potentially leading to a drop in sales volume?
  • Might we see a surge in pre-buying before the tariff hits, impacting inventory faster?

By modeling scenarios, you can quickly evaluate options and choose the strategy that best balances profitability, customer relationships, and market realities.

Building out Your What-If Dashboard

Several key steps are needed to build out a What-If Dashboard:

1. Define the Needed Answers: Clearly identify the business questions related to tariffs, inflation, pricing, costs, and inventory that you expect to address.
2. Identify Critical Data Inputs: Determine the essential data points which often include:
   • Product Master Data: SKU, Hierarchy, Finished Good and Component Countries of Origin
   • Costing Data: Raw Component Costs
   • Inventory & Procurement Data: On-hand/In-transit/Open POs; Tier 1 and Tier 2 Supplier Locations
   • Pricing & Sales Data: List Price, Average Sell Price, Special Pricing Agreements
   • Market & External Factors: Competitor pricing intelligence, inflation indices, FX rates, demand elasticity estimates.
3. Consolidate & Prepare Data: Define the best approach to consolidate the data. More advanced companies will have already integrated their BI tools with sources of this critical data. Maturing companies may need to find scrappier, manual work arounds to quickly gain access to insights.
4. Build & Validate the Model: Develop the analytical model incorporating the data and business logic. Validate outputs rigorously against historical data or known scenarios to build confidence in its accuracy.
5. Select the Right Tool/Platform: Choose technology that offers the necessary flexibility. While sophisticated spreadsheets can work for simpler cases, BI platforms are better equipped to handle complex calculations.
6. Integrate & Iterate: Embed the tool and its outputs into key business processes (e.g., Pricing SWAT/Committee reviews). Ensure cross-functional teams (Sales, Finance, Supply Chain, Procurement) understand how to use the insights. Continuously refine the model as business needs and data sources evolve.

Kenway Can Help

We've supported many of our clients build out What-If Analysis to support data-driven decision-making. Don’t lose margin or market share because you didn’t act fast enough to prepare for these volatile times. If you want to know how it would work in your organization, read more here or reach out to us today.