So, you need a sales forecasting dashboard in Anaplan—but you don’t want another bloated mess nobody trusts or uses. You want something your sales team and execs can actually use to make decisions, not just another pretty chart that sits ignored in a folder. This guide walks you through every step, from setup to launch, so you get a dashboard that’s practical, reliable, and (mostly) hassle-free.
This is for you if: - You work with Anaplan and need a no-nonsense way to forecast sales. - You’re new to dashboards, or you keep hearing “can we get this in Anaplan?” - You value clarity over complexity.
Let’s get into it.
Step 1: Get Your Requirements Straight (Don’t Skip This)
Before you even touch Anaplan, gather your requirements. Yes, it’s tempting to click around and “see what happens,” but you’ll just waste time redoing things if you skip this.
What to ask: - Who is this dashboard for? (Sales managers, execs, finance, etc.) - What decisions should it help them make? - What data do they want to see? (Revenue, pipeline by stage, forecast vs. actual, etc.) - How often will the dashboard be used? (Daily, weekly, monthly?) - Are there existing reports people actually like? (Steal what works.)
Pro tip: If you can’t write down what the dashboard is supposed to answer in one sentence, you’re not ready to build.
Step 2: Prep Your Data (The Boring but Crucial Part)
Anaplan is only as good as the data you feed it. Garbage in, garbage out—no exceptions.
What you need: - Sales pipeline data (deals, stages, owners, values, close dates) - Actual sales results (bookings, revenue, etc.) - Time structure (months, quarters—you get the idea) - Maybe: product lines, regions, customer segments
Where it comes from: Usually Salesforce, Excel, or some other CRM. Get clean, consistent data. If you don’t trust your source, fix that first.
Watch out for: - Duplicate deals - Inconsistent stage names - Missing owners or dates
Don’t bother: Trying to automate data loads right away. Start with a simple import to make sure your structure works first.
Step 3: Build Your Lists and Modules
Lists are the backbone of Anaplan. Get these right, and everything else is easier.
3.1 Create Your Lists
At a minimum, you’ll need: - Time (use Anaplan’s built-in time) - Sales Reps or Owners - Deal Names/IDs - Products (if needed) - Regions (optional, but helpful)
Keep it simple: Don’t add a field just because you might need it “one day.”
3.2 Set Up Your Modules
Modules are where your data lives and calculations happen.
Typical modules: - Pipeline Module: Deals by stage, owner, amount, close date, etc. - Actuals Module: Closed/won deals, revenue booked. - Forecast Module: Calculated forecasts, weighted pipeline, etc.
Pro tip: Keep modules focused. If a module is trying to do everything, it’ll be a mess to maintain.
Step 4: Import Your Data
Now, actually get your data into Anaplan.
How to: - Use CSVs or direct connectors for your first load. - Map columns carefully. Anaplan will throw errors at the smallest mismatch. - Test with a small sample before importing everything.
Common mistakes: - Forgetting to update lists first (you’ll get errors). - Loading data with future dates that don’t match your model’s time periods. - Expecting Anaplan to clean your data for you (it won’t).
Ignore for now: Fancy integrations or automation. Manual loads are fine until you’re sure your structure works.
Step 5: Build Key Calculations
This is where you turn raw data into something useful.
5.1 Basic Calculations
- Total Pipeline: Sum up deal values by stage, owner, month.
- Weighted Pipeline: Multiply deal values by probability for each stage.
- Forecast: Pick a method (rep forecast, historical average, weighted pipeline—just be clear which one you use).
- Actuals vs. Forecast: Show where you’re ahead or behind.
Stick to what matters: Don’t try to build fancy machine learning models unless your data is bulletproof (it rarely is).
5.2 Time Intelligence
- Add logic to roll up by month, quarter, year.
- Highlight deals closing this quarter vs. next.
5.3 Variance Calculations
- Show changes vs. last month’s forecast.
- Show win rates by rep or product.
Avoid: 100+ KPIs. Most people only care about a handful.
Step 6: Design the Dashboard
Now, make it look good—but more importantly, make it useful.
6.1 Create Dashboard Pages
- Use Anaplan’s New UX (the old dashboards are clunky).
- Drag in grids, charts, and KPIs—but don’t go overboard.
- Group related info together (pipeline, forecast, actuals).
- Add filters for time period, sales rep, region.
Must-haves: - Clean summary at the top (big numbers, trends) - Pipeline by stage - Forecast vs. actuals chart - Drill-downs for details
Skip: Eye candy and complex color-coding. If it’s not actionable, leave it out.
6.2 Test with Real Users
- Show a draft to a few sales managers.
- Ask: “What would you actually use this for?” and “What’s missing?”
- Adjust. Repeat. Don’t fall in love with your first version.
Step 7: Set Up Security and Access
Don’t let everyone see everything by default—especially if there’s sensitive data.
- Use Anaplan’s role-based access controls.
- Give sales reps access to their own data.
- Managers and execs get broader views.
Mistake to avoid: Waiting until go-live to set this up. You’ll regret it.
Step 8: Automate Data Loads (Only When Ready)
If your dashboard works and people use it, then automate data loads.
- Use Anaplan Connect, CloudWorks, or an iPaaS tool if you have lots of data.
- Schedule regular imports from your CRM or data warehouse.
- Always QA the first few automated runs—automation just makes bad data problems happen faster.
Don’t bother: Building a complex integration before you know your basic model works.
Step 9: Launch, Listen, and Iterate
- Share the dashboard with your users.
- Train people, but keep it short—if you need a manual, it’s too complicated.
- Gather feedback: What do people actually use? What’s ignored?
- Tweak. Cut out unused features. Add what’s genuinely needed.
Pro tip: Most dashboards are cluttered because people keep adding things nobody uses. Be ruthless—less is more.
A Few Honest Takes
- Anaplan is powerful, but not magic. It won’t fix bad data, broken processes, or unclear goals.
- You’ll never get it perfect on the first try. That’s normal. Just make it better each cycle.
- Ignore buzzwords. Predictive analytics and AI sound cool, but most orgs can’t even get a reliable weighted pipeline.
Final Thoughts: Keep it Simple, Keep Improving
A good sales forecasting dashboard doesn’t have to be fancy—it just has to work, be trusted, and answer real questions. Start with the basics, roll it out, and improve as you go. Don’t get sucked into endless “phase two” wishlists or gold-plating. The most useful dashboards are usually the simplest.
Now go build something people will actually use. And if all else fails, ask your users what they’d delete from the dashboard—then do it.