# Setting Up Forecast Guidelines {% hint style="info" %} **Quick Answer:** Forecast guidelines are business rules you share with Mo to apply bulk adjustments across your catalog. Define rules for seasonality, regional demand, growth rates, and SKU-level behavior, then let Mo process them across hundreds or thousands of products at once. {% endhint %} ## What Are Forecast Guidelines? **Forecast guidelines** are structured business rules that tell Mo how to adjust your directional forecast based on your knowledge of the business. Instead of editing SKUs one by one, you describe patterns and rules that Mo applies across your entire catalog. Guidelines typically cover: * **Seasonality** β€” How demand shifts throughout the year for different product categories * **Regional weightings** β€” How demand varies across sales channels or geographies * **Growth assumptions** β€” Expected growth or decline rates by category or product line * **SKU-level logic** β€” Specific rules for individual products or product groups ### Forecast Guidelines Template Use the template below to document your guidelines before sharing them with Mo. Fill in the rows that apply to your business, delete the example rows, then upload the completed file via the **paperclip icon** in the Mo chat and ask Mo to update your forecast based on the guidelines. {% hint style="success" %} **How to use this template with Mo:** 1. Copy the table into a spreadsheet or text file and fill in your rules 2. Save the file (CSV, Excel, or plain text all work) 3. Open Mo in your Moselle chat 4. Click the **paperclip (πŸ“Ž)** icon to attach the file 5. Send a message like: *"Please update my forecast based on these guidelines"* {% endhint %} {% hint style="info" %} **Tips:** Fill in as many or as few rows as you need. Delete any example rows before uploading. The more specific you are with percentages, dates, and product names, the more precisely Mo can apply each rule. {% endhint %} | SECTION | GUIDELINE TYPE | PRODUCT CATEGORY / SKU | RULE DESCRIPTION | ADJUSTMENT TYPE | ADJUSTMENT VALUE | START MONTH / DATE | END MONTH / DATE | NOTES / CONTEXT | | ------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------- | ------------------------------------------------------------------------------- | ---------------------- | -------------------------------------------- | ---------------------------------- | --------------------------------- | ---------------------------------------------------------- | | **HOW TO USE** | Fill in each row that applies to your business. Delete example rows. Add as many rows as needed. Once complete, share this file with Mo in your Moselle chat and ask Mo to re-apply your forecast based on these guidelines. | | | | | | | | | **β€” SEASONALITY RULES β€”** | | | | | | | | | | EXAMPLE | Seasonality | \[e.g. Sunscreen SPF 50] | \[e.g. Demand peaks in summer months due to beach season] | % Increase / Decrease | \[e.g. +60%] | \[e.g. May] | \[e.g. August] | \[e.g. Return to baseline in September] | | EXAMPLE | Seasonality | \[e.g. Winter Candle Collection] | \[e.g. Strong seasonal demand tied to holiday gifting] | % Increase | \[e.g. +150% Nov / +180% Dec] | \[e.g. November] | \[e.g. December] | \[e.g. Minimal demand Jan–Sep] | | EXAMPLE | Seasonality | \[e.g. Daily Moisturizer] | \[e.g. Year-round staple β€” no seasonal swing expected] | Flat / No Adjustment | \[e.g. 0%] | \[e.g. January] | \[e.g. December] | | | **β€” CHANNEL & REGIONAL WEIGHTINGS β€”** | | | | | | | | | | EXAMPLE | Channel Weighting | \[e.g. Amazon] | \[e.g. Primary volume driver β€” largest single channel] | % of Total Demand | \[e.g. 55%] | \[e.g. Full Year] | \[e.g. Full Year] | \[e.g. Holiday spike stronger here than on DTC site] | | EXAMPLE | Channel Weighting | \[e.g. DTC Website] | \[e.g. Growing direct channel β€” moderate promotional lift] | % of Total Demand | \[e.g. 30%] | \[e.g. Full Year] | \[e.g. Full Year] | | | EXAMPLE | Channel Weighting | \[e.g. Wholesale / Retail] | \[e.g. Pre-season buy windows β€” orders placed well ahead of sell dates] | Ordering Pattern | \[e.g. Concentrated Q1] | \[e.g. January / July] | \[e.g. March / September] | \[e.g. Not a transactional channel β€” plan for buy windows] | | EXAMPLE | Channel Weighting | \[e.g. International DTC] | \[e.g. International demand follows domestic trends with a delay] | Timing Lag | \[e.g. 4–6 week lag vs. domestic] | \[e.g. Rolling] | \[e.g. Rolling] | | | **β€” GROWTH ASSUMPTIONS β€”** | | | | | | | | | | EXAMPLE | Category Growth | \[e.g. Body Care] | \[e.g. Strong momentum β€” new hero product and increased paid media] | YoY Growth Rate | \[e.g. +20%] | \[e.g. Full Year 2026] | \[e.g. Full Year 2026] | | | EXAMPLE | Channel Growth | \[e.g. DTC Website] | \[e.g. Investing heavily in email and retention β€” expect channel to grow] | YoY Growth Rate | \[e.g. +35%] | \[e.g. Full Year 2026] | \[e.g. Full Year 2026] | | | EXAMPLE | Decline Rate | \[e.g. Old Packaging SKUs] | \[e.g. Legacy packaging being phased out β€” still sell through remaining stock] | Monthly Decline Rate | \[e.g. -10% per month] | \[e.g. March 2026] | \[e.g. Until discontinued] | | | EXAMPLE | Flat / No Growth | \[e.g. Core Replenishment Basics] | \[e.g. Stable, mature SKUs β€” no growth planned] | Flat | \[e.g. 0%] | \[e.g. Full Year 2026] | \[e.g. Full Year 2026] | | | **β€” SKU-LEVEL RULES β€”** | | | | | | | | | | EXAMPLE | New Launch | \[e.g. SKU-1001 β€” New Serum] | \[e.g. New SKU launching April 1 β€” ramp to full velocity over 6 weeks] | Ramp Curve | \[e.g. Use SKU-0988 Vitamin C as comparable] | \[e.g. April 1, 2026] | \[e.g. May 15, 2026] | | | EXAMPLE | Promotional Hero | \[e.g. SKU-2045 β€” Hero Moisturizer] | \[e.g. Key hero product for BFCM β€” expect significant demand lift] | % Increase | \[e.g. 4x normal demand] | \[e.g. November 2026] | \[e.g. Mid-December 2026] | | | EXAMPLE | Discontinuation | \[e.g. SKU-3312 β€” Discontinued Colour] | \[e.g. Colour being retired β€” reduce forecast until fully phased out] | Monthly Decline | \[e.g. -25% per month] | \[e.g. May 2026] | \[e.g. September 2026 (zero out)] | | | EXAMPLE | Supply Constraint | \[e.g. SKU-4400 β€” Limited Edition] | \[e.g. Constrained by supplier capacity until new PO arrives] | Hard Cap | \[e.g. 300 units/month max] | \[e.g. Now] | \[e.g. Q3 2026] | \[e.g. Remove cap once new shipment clears] | | EXAMPLE | Bundle Logic | \[e.g. Holiday Gift Set] | \[e.g. Bundle demand will cannibalize individual SKU sales during promo period] | Cannibalization Offset | \[e.g. \~40% of individual SKU demand] | \[e.g. November 2026] | \[e.g. December 2026] | | | **β€” PROMOTIONAL CALENDAR β€”** | | | | | | | | | | EXAMPLE | Promotion | \[e.g. BFCM Sale] | \[e.g. Site-wide and Amazon sale β€” biggest demand event of the year] | % Demand Lift | \[e.g. 3x on Amazon / 2x on DTC] | \[e.g. November 28, 2026] | \[e.g. December 2, 2026] | \[e.g. Pre-campaign inventory by Nov 10] | | EXAMPLE | Promotion | \[e.g. New Year New You Campaign] | \[e.g. January wellness push β€” category-specific demand lift] | % Demand Lift | \[e.g. +45%] | \[e.g. January 1, 2026] | \[e.g. January 31, 2026] | \[e.g. New campaign β€” won't appear in historical data] | | EXAMPLE | Promotion | \[e.g. Influencer Collab Drop] | \[e.g. Limited edition drop with major creator β€” viral spike expected] | Demand Spike | \[e.g. 5x normal velocity] | \[e.g. TBD β€” confirm with creator] | \[e.g. TBD] | \[e.g. Update dates once confirmed] | *** **Time Required:** 15–30 minutes for initial setup **Difficulty:** Intermediate *** ## Prerequisites Before setting up forecast guidelines, make sure you have: * [ ] A directional forecast already generated (top-down or bottom-up) * [ ] Understanding of your product categories and their demand drivers * [ ] Knowledge of your upcoming promotional calendar * [ ] Access to Mo in your Moselle account {% content-ref url="/pages/XFbBg0MSQpAiqVkBJo75" %} [How to Create a Forecast](/planning-and-execution/forecasting/how-to-create-a-forecast.md) {% endcontent-ref %} *** ## Building Your Seasonality Rules Seasonality is often the most impactful set of guidelines you can provide. These rules tell Mo how demand for different product categories fluctuates throughout the year. ### How to Define Seasonality Rules {% stepper %} {% step %} ### Identify Your Seasonal Categories Group your products by how seasonality affects them: * **Highly seasonal** β€” Products with dramatic demand swings (e.g., swimwear, holiday gifts, outdoor equipment) * **Moderately seasonal** β€” Products with noticeable but less extreme shifts (e.g., fitness apparel, skincare) * **Non-seasonal** β€” Products with steady demand year-round (e.g., everyday basics, consumables) {% hint style="warning" %} Don't over-categorize. Start with 3–5 seasonal groupings. You can always add granularity later. {% endhint %} {% endstep %} {% step %} ### Quantify the Seasonal Impact For each seasonal category, estimate the demand change by month or quarter: **Example seasonality rules:** * "Outdoor furniture: +50% April through September, -30% November through February" * "Holiday gift sets: +200% in November, +300% in December, return to baseline in January" * "Everyday basics: flat year-round, no seasonal adjustment" * "Fitness equipment: +40% January through March, -10% June through August" {% endstep %} {% step %} ### Share with Mo Open the Mo chat and provide your seasonality rules. Be specific about which categories are affected and the magnitude of the adjustment. **Example prompt:** "Apply these seasonality rules to my 2026 forecast: * Outdoor furniture increases 50% from April through September and decreases 30% from November through February * Holiday gift sets increase 200% in November and 300% in December * Everyday basics remain flat with no seasonal adjustment * Fitness equipment increases 40% January through March" {% endstep %} {% endstepper %} *** ## Defining Regional and Channel Weightings If you sell across multiple channels or regions, demand patterns may vary significantly. Channel weightings help Mo distribute your forecast appropriately. ### When to Use Channel Weightings * You sell through both **wholesale** and **direct-to-consumer** with different demand curves * Certain **marketplaces** (Amazon, Shopify) show different seasonality than your own website * **Geographic regions** have distinct demand patterns ### How to Set Up Channel Weightings Describe the relative demand differences across your channels: **Example guidelines:** * "Amazon typically represents 60% of our total demand, Shopify 25%, and wholesale 15%" * "Wholesale orders are concentrated in Q1 and Q3 for pre-season buys" * "Our Amazon channel has a stronger BFCM spikeβ€”2.5x vs. 1.5x on Shopify" * "International channels lag domestic trends by approximately 4–6 weeks" {% hint style="info" %} You don't need exact percentages. Directional guidance like "Amazon is our largest channel and spikes harder during promotions" gives Mo enough context to apply meaningful adjustments. {% endhint %} *** ## Setting Growth Assumptions Growth assumptions tell Mo how you expect demand to evolve beyond what historical patterns suggest. ### Types of Growth Assumptions | Type | Description | Example | | -------------------- | --------------------------------------------------- | --------------------------------------------------------- | | **Category growth** | Expected growth rate for an entire product category | "Our protein bar category is growing 25% year-over-year" | | **Channel growth** | Expected growth for a specific sales channel | "Amazon sales growing 30% YoY after our advertising push" | | **Decline rates** | Expected decrease for products being phased out | "Legacy packaging SKUs declining 15% monthly" | | **Flat assumptions** | Categories expected to maintain current levels | "Core basics should remain flat, no growth expected" | ### How to Apply Growth Assumptions {% stepper %} {% step %} ### Review Historical Growth Rates Before setting forward-looking assumptions, check your recent performance: 1. Navigate to **Reports** in the left sidebar 2. Review the **Demand Reports** for category-level trends 3. Note which categories are growing, stable, or declining {% endstep %} {% step %} ### Define Your Assumptions Create growth rules based on your business strategy and recent performance: **Example prompt:** "Apply these growth assumptions: * Protein bars: grow 25% YoY across all channels * Premium supplements: grow 15% YoY * Legacy packaging SKUs: decline 15% per month until discontinued * Core basics: flat, no growth adjustment" {% endstep %} {% step %} ### Verify the Output After Mo applies growth assumptions, spot-check key SKUs to confirm: * Growth rates compound correctly over the forecast horizon * Declining products reach expected levels by their discontinuation date * Flat categories haven't been inadvertently adjusted {% endstep %} {% endstepper %} *** ## Creating SKU-Level Logic Some products need rules that don't fit neatly into category-level guidelines. SKU-level logic lets you define behavior for specific items or small groups. ### Common SKU-Level Rules **New product launches:** * "New protein bar (SKU-2468) launches March 15 β€” ramp to full velocity over 8 weeks using our chocolate bar launch as a comparable" **Promotional items:** * "SKU-1357 is our BFCM hero product β€” 3x normal demand in November, with a 2-week tail into December" **Discontinuation:** * "SKU-9876 is being phased out β€” reduce forecast by 20% per month starting April, zero by August" **Constrained supply:** * "SKU-5555 is supply-limited to 500 units per month until our new supplier comes online in Q3" **Bundled products:** * "When we run the holiday bundle, the individual SKUs in the bundle should decrease by the percentage of sales expected from the bundle" {% hint style="warning" %} Keep SKU-level rules for items that genuinely need individual attention. If a rule applies to an entire category, define it as a category-level guideline instead. {% endhint %} *** ## Organizing Your Guidelines Document As your guidelines grow, it helps to organize them in a structured way. Consider this format when sharing with Mo: **Category Rules:** * List broad rules that apply to product groups **Channel/Regional Rules:** * List rules specific to sales channels or geographies **Growth Assumptions:** * List forward-looking growth or decline rates **SKU-Specific Rules:** * List rules for individual products that need unique treatment **Promotional Calendar:** * List upcoming promotions with expected demand impact and timing {% hint style="success" %} Save your guidelines document externally so you can reuse and refine it each planning cycle. Over time, your guidelines become a valuable playbook for demand planning. {% endhint %} *** ## Recommended Workflow {% stepper %} {% step %} ### Start Broad Begin with 3–5 category-level seasonality rules and your most important growth assumptions. Apply these first and review the results. {% endstep %} {% step %} ### Add Channel Detail Layer in channel-specific weightings if your demand varies meaningfully across sales channels. {% endstep %} {% step %} ### Apply SKU-Level Rules Address individual products that need specific treatmentβ€”new launches, discontinuations, promotional heroes. {% endstep %} {% step %} ### Review and Iterate Spot-check representative SKUs from each category. If the adjustments don't match your expectations, refine the guidelines and reapply. {% endstep %} {% step %} ### Finalize Once your forecast reflects your business knowledge, lock the forecast and move into replenishment planning. {% endstep %} {% endstepper %} *** ## Frequently Asked Questions ### How many guidelines should I start with? Start with 5–10 rules covering your most impactful categories and seasonal patterns. You can always add more granularity in subsequent cycles. ### Can I update guidelines after applying them? Yes. You can share updated guidelines with Mo at any time. Mo will adjust the forecast based on your latest rules, preserving any surgical edits you've already made unless the guideline directly conflicts. ### Do guidelines carry over between forecast cycles? Guidelines are applied per conversation with Mo. Save your guidelines externally so you can reuse and refine them each planning cycle. ### What if my guidelines conflict with each other? If Mo detects conflicting rules (e.g., a category growth rule and a SKU decline rule for the same product), it will ask for clarification. Be as specific as possible to avoid ambiguity. ### How do I know if my guidelines improved the forecast? Track your **MAPE scores** in the Forecast Performance Report before and after applying guidelines. Over multiple cycles, you should see accuracy improve as your guidelines capture business dynamics the model alone cannot detect. *** ## Related Guides {% content-ref url="/pages/0j4ySH8ZiAtDK6eRiQ77" %} [Refine Your Forecast](/planning-and-execution/forecasting/refine-your-forecast.md) {% endcontent-ref %} {% content-ref url="/pages/ja1XQcZPneh77RB6KNv3" %} [Build your forecast with Mo](/planning-and-execution/forecasting/build-your-forecast-with-mo.md) {% endcontent-ref %} {% content-ref url="/pages/KXh7MTxw84WmaJhhHp6g" %} [How Mo's Forecasting Works](/planning-and-execution/forecasting/how-mos-forecasting-works.md) {% endcontent-ref %} {% content-ref url="/pages/D2BTtZoIEwFaGlVVWPXZ" %} [Forecast Best Practices](/planning-and-execution/forecasting/forecast-best-practices.md) {% endcontent-ref %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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