If you’re drowning in SKUs, wrestling with new releases, or tired of inventory surprises, product lifecycle tracking is the flashlight you need. This guide is for planners, ops folks, and anyone trying to keep their inventory—and sanity—under control. I’ll walk you through setting up product lifecycle tracking in Avercast, with zero fluff and no half-baked promises.
Let’s get your SKUs to behave.
Why bother with product lifecycle tracking?
Most companies treat every SKU the same, which is a fast track to overstocking, dead inventory, and missed signals about what’s actually selling. Lifecycle tracking lets you:
- Spot new products that need a different forecast.
- See when products are fading out, so you don’t reorder them.
- Catch slow movers before they become a warehouse horror story.
- Get smarter about promotions and markdowns.
And, yes, you can do this in a spreadsheet—but unless you enjoy pain, Avercast can actually make it manageable. Still, don’t expect miracles: It’s only as good as the data you feed it and the discipline you bring.
Step 1: Prep Your Data (Don’t Skip This)
Before you even touch Avercast, make sure you have your house in order. This is where most lifecycle setups fall apart.
What you need: - A clean list of SKUs (no old, dead, or duplicate codes). - For each SKU: intro date, discontinuation date (if known), and a clear category. - Sales history that’s not riddled with errors.
Tips: - If your system has SKUs that are really just packaging changes or color tweaks, decide if you want to track them separately. - You don’t need perfect data, but garbage in = garbage out.
Pro tip: Run a quick sales report. If you have SKUs with zero sales for 12+ months, flag them for review—they’re probably dead weight.
Step 2: Define Your Lifecycle Stages
You need to tell Avercast how you want to classify a product’s “life.” Don’t overcomplicate it.
Typical stages: - Introduction: Just launched, unpredictable demand. - Growth: Sales picking up, maybe some buzz. - Maturity: Stable, steady sales—this is the sweet spot. - Decline: Sales dropping off, time to plan an exit.
You can add more stages (e.g., “Obsolete” or “Clearance”), but more complexity rarely helps. Stick to 3-5 stages max.
What matters: - The triggers you’ll use. Is it time-based (e.g., after 6 months), sales-based (units per month), or a mix? - Being consistent. If you change your rules every quarter, you won’t trust your data.
Step 3: Set Up Lifecycle Parameters in Avercast
Now, finally, into Avercast. The screens and names might change a bit depending on your version, but the basics are the same.
In Avercast: 1. Go to the Product Setup or Lifecycle Module. (Depending on your config, this might be under forecasting or inventory settings.) 2. Input or import your SKU list. Use the cleaned-up file you prepped earlier. 3. Define lifecycle stages. There’s usually an admin or table setup for lifecycle categories—add the ones you picked. 4. Set rules for each stage. For example: - Introduction: Less than 3 months since launch OR <100 units sold. - Growth: 3-12 months since launch AND consistent month-over-month sales growth. - Maturity: 12+ months, stable sales, low returns. - Decline: Sales down 20%+ over last 6 months, flagged for review. 5. Map triggers to your data fields. Avercast needs to know which date fields or sales metrics to use. Double-check that the right columns are mapped (especially if you imported from Excel or your ERP).
Pro tip: Test on a small batch of SKUs first. Don’t throw your whole catalog at it until you’re sure the logic works.
Step 4: Assign SKUs to Lifecycle Stages
Avercast can auto-assign SKUs based on the rules you set, but it’s wise to check the assignments before you trust them blindly.
How to check: - Run a lifecycle status report. - Spot-check SKUs you know well—do the stages make sense? - Look for outliers: Products in “Maturity” that haven’t sold in a year, or “Introduction” SKUs that have been around forever.
If something’s off: - Review your triggers (maybe your sales data is off, or the date fields got mixed up). - Adjust stage definitions if needed.
Don’t get hung up on perfect assignments—aim for 90% right. The rest you can tweak over time.
Step 5: Integrate Lifecycle Tracking with Forecasting and Inventory
Here’s where the real value comes in: Using lifecycle stages to drive decisions, not just make pretty reports.
In Avercast, you can: - Apply different forecasting models by stage. New SKUs should never get a “straight-line” forecast. Mature products can. - Adjust safety stock and reorder points. Declining SKUs probably need less buffer. - Automate alerts. Get notified when a product enters decline, so you can plan markdowns or discontinue.
What works: - Using lifecycle as a filter when reviewing forecasts—focus on the problem children. - Having automatic “decline” triggers to flag products before they become dead stock.
What to ignore: - Fancy dashboards that don’t change your decisions. - Overly complex stage definitions that only confuse your team.
Step 6: Keep It Updated (or It’ll Rot)
The biggest mistake? Setting this up once and forgetting about it.
How to keep it alive: - Schedule a monthly or quarterly check-in. Update lifecycle assignments and review rules. - Make someone own it. If it’s everyone’s job, it’s no one’s job. - Use reports, not just dashboards. Make decisions—cut, promote, or adjust—based on what you see.
Pro tip: Set up a recurring calendar reminder. A 30-minute review beats months of cleaning up bad inventory.
Honest Takes: What Works, What Doesn’t
Works: - Keeping lifecycle stages simple and rules clear. - Using auto-assignment, but reviewing exceptions manually. - Integrating lifecycle with forecasting—don’t silo your teams.
Doesn’t work: - Setting and forgetting. Lifecycle tracking needs regular attention. - Over-customizing the process. More fields = more confusion. - Blindly trusting the tool. Avercast is powerful, but not magical.
Ignore: - Vendor hype about “AI-powered lifecycle optimization.” If you don’t have clean data, the AI is just guessing.
Keep It Simple, Iterate Often
Don’t get paralyzed trying to build the perfect lifecycle model. Set up something basic, test it, and improve as you go. SKU management is messy, but lifecycle tracking in Avercast gives you a fighting chance—if you keep it simple and actually use the insights.
Remember, the goal isn’t a fancy report—it’s fewer surprises, less dead stock, and a supply chain you can sleep at night about. Good luck, and don’t be afraid to adjust as you learn what actually works for your business.