Key Business Challenges for Retail Energy Providers: Part I
by Charlie Palmer
Effectively manage your core commodity business to understand and mitigate riskThe biggest challenges for most Retail Energy Providers are:
- Effectively managing commodity risk
- Accurately measuring and analyzing commodity gross margin
Managing commodity riskEffectively managing your commodity positions and mitigating as much risk as possible is the single biggest driver of a Retail Energy Provider’s bottom line. Done well and it can give your company a competitive advantage. Done poorly and it can take your company into bankruptcy! It is the single biggest business driver for a Retail Energy Provider – and must be managed as such.
The starting point for any Retail Energy Provider is to know its commodity positions (by wholesale hedging positions and risk/product type) accurately and with hourly granularity. What are the keys for being able to do this?
- Accurate data
- Customer counts and flow dates
- Load forecasts – hourly by risk type and wholesale zone
- Supply – hourly by product type and wholesale zone
- ISO settlement data
- Systems capable of handling this amount of data
- Hourly granularity
- Numerous positions
- Automated data handling to reduce risk
- Leverage BI tools to manage and visualize all of this data
Accurate measurement and analysis of commodity gross marginHow often have you heard a Retail Energy Provider complain that their financial forecasts are not accurate? Or that they can’t explain the variances? Or that they have large PPA’s flow through when they get their settlement statements? Or, the concerns by senior management that the forecasts they get from Finance, Supply and Marketing are all different?! A company with poor financial forecasts is not a good investment for either privately held or public companies.
Keys to success for accurate financial forecasting and analysis of variance drivers:
- First and foremost, the Retail Energy Provider must migrate to a ‘single system of record’ for all key data elements – load (forecast and settled), supply costs (commodity and non-commodity), and customer revenue
- Capability to disaggregate load forecast error into weather/customer count/model variances
- Having robust supply/ETRM/settlement systems to accurately track and forecast total COGS is critical
- Having the ability to match customer revenues to the supply ‘buckets’ is necessary to create accurate gross margin estimates
- Clearly understanding when COGS are being ‘allocated’ to customer groups to understand the accuracy and inaccuracy of gross margins
- Best practices is to have and integrated gross margin engine to accurately combine all three elements.