Replace spreadsheets with intelligent planning.

IBP extends traditional supply-chain demand planning to include sales, finance, and operations in a unified process. CauSelf's IBP uses causal modelling rather than statistical averages — your forecast is driven by what actually moves demand: promotions, seasonality, pricing, and retailer behaviour.

CauSelf implementations complete in 2–4 months vs. 6–18 months for traditional enterprise platforms. Our proof of concept (2–4 weeks) lets you validate results with your actual data before committing to full deployment.

CauSelf is purpose-built for mid-market consumer goods companies — typically $5M to $150M in revenue — who have outgrown spreadsheets but can't justify enterprise platforms like SAP IBP or o9. If your team is managing Excel files instead of making planning decisions, you're likely a strong fit.

Every CauSelf subscription includes ongoing access to an experienced FMCG consultant — not a generic helpdesk. Think of it as AI handling the automation and pattern-recognition, while your consultant handles the judgement: optimising models for your specific market, managing new product launches, adapting to seasonal shifts, and running monthly performance reviews. Both are built into your subscription — no surprise hourly invoices.

Yes. CauSelf has been deployed across dairy manufacturing, beverage, grocery, specialty stationery, health & beauty, and fresh produce. The platform handles category-specific requirements including weather-dependent demand, perishability constraints, multi-brand portfolio management, and seasonal product lifecycle.

IBP manages demand forecasting. TPM manages trade promotion planning, execution, and ROI measurement. RGM provides strategic scenario planning for pricing, mix, and revenue growth. Together they create a closed-loop process: IBP assumptions feed TPM, TPM results feed RGM analysis, and RGM targets flow back into IBP.

Yes. Brett Podoll leads US operations including sales, implementation, and customer success. Tim Williamson, our Founder, leads APAC operations from Australia. Each region has its own contact team. APAC pricing is available on request and scoped in local currency.

Traditional demand planning relies on historical averages — CauSelf uses AI-powered causal models that identify up to 20 specific drivers influencing your demand: promotions, pricing, seasonality, weather, and retailer behaviour. The AI learns from your actual data and recalibrates automatically every planning cycle without manual tuning. This typically improves forecast accuracy by 10–30 percentage points vs spreadsheet-based baselines — while freeing your team from model maintenance entirely.^²

Traditional demand planning tools use dated and simple forecast methodologies that don't recognise the sales plan — promotions, price changes, distribution changes — and they don't capture the relationship between what the retailer sells (scan data) and what the retailer buys. The ability to forecast and overlay these two streams of demand is critical for improved accuracy and better supply chain visibility. CauSelf excels at exactly this: it delivers better visibility and more rigour, which reduces the guesswork — and as a result drives more effective sales planning and measurably better forecast accuracy.

Traditional Trade Promotion Management tools are very detail-heavy — getting deep into transactional weeds when creating a promotion. This reliance on manual data entry means that when things get complex, promotions are often partially completed and teams find workarounds. The result: TPM tools become so transactionally focused they stop driving the business, and Excel spreadsheets reappear to fill the void. CauSelf is different because we took the time to understand how sales teams actually manage their promotions and what finance genuinely needs to see. The result is a more comprehensive solution that captures the necessary level of accuracy and detail — but does so far more efficiently and effectively, keeping your team focused on decisions rather than data entry.