Fehlentscheidungen bei Saisonplanung durch unzureichende Datenbasis

Definition

Government sport funding schemes often cap the number or value of grants per event or year (e.g. Victoria’s Significant Sporting Events Program specifies that only one grant is available for the same event per year and has upper limits of AUD 20,000 for event assistance and AUD 150,000 for event development).[3][4] WA’s program may prioritise certain events and budgets in consultation with state and national sporting organisations when multiple applications compete within a single round.[2] Seasonal facility allocations by local councils are also constrained and often prioritised for established users, with allocation windows and criteria that can limit how many programs a club can realistically run.[1][7] In this constrained environment, sports instruction businesses must decide which seasonal academies, camps, tournaments or development programs to propose and budget for each year. When budgeting is done manually and aggregated at the club level, decision‑makers lack clear visibility into contribution margin per program, likelihood of receiving grants, and total resource requirements. As a result, they may prioritise traditional or prestige events with weak economics over smaller, higher‑margin instruction programs (e.g. holiday clinics), or they may spread resources thinly across many programs, reducing the chance of any single application meeting value‑for‑money criteria and being funded. Given that individual grants can be worth up to AUD 20,000 for operational costs and AUD 150,000 for development of key events,[3][4] steering limited resources towards programs with low funding probability or poor margins can easily represent AUD 5,000–25,000 of foregone net benefit per year when more viable alternatives exist.

Why This Matters

The Pitch: Sports and recreation instruction providers in Australia 🇦🇺 misallocate AUD 5,000–25,000 per year by prioritising low‑margin or unfundable seasonal programs. Data‑driven budgeting and scenario modelling helps redirect spend to higher‑return programs.

Affected Stakeholders

Club committee / board, Director of coaching, Program manager, Treasurer, State sporting organisation development officers advising clubs

Related Business Risks