While motorists have undoubtedly been pleased with paying less at the pump, slumping fuel prices over the past year have had a wide economic impact, bringing many experts to the conclusion that the old ways of doing things should from now on be relegated to the past.
Oil and gas companies must become aware of how both revenue and cash flow deficits will change how effectively they can invest for the future, especially now with oil prices falling over 50 per cent. The pressure created by the current scenario is only exasperated by the high amount of debt accrued by oil producers, and the fact that many of those debts are set to be due this year.
For oil and gas producers, as well as their suppliers and big-bank creditors, this market turmoil has upset business models and greatly increased management’s need to ensure the profitability of ongoing and incremental investments in customers, products, services, channels and partners. As they seek the necessary profitability analytic insight to successfully meet the challenge, however, many companies find that the systems on which they have historically relied – traditional enterprise resource planning (ERP) platforms and profitability applications – fail to provide sufficient help.
These systems do a great job of processing transactions and creating a high-level, aggregated view of profitability, but they fall short of delivering the multi-dimensional profitability insights required to stay competitive in today’s economic landscape. A data-driven profitability approach, which gathers all relevant profitability data from a variety of internal and external sources and puts them into a shared analytic repository for modelling and user-friendly reporting, is a better choice.
Why? Because this approach:
1. Combines operational, financial and commercial data to provide a clearer picture of business performance.
When softening demand is shrinking top-line revenues, it helps to combine data in new ways, and by new dimensions, to identify where it’s falling fastest and where the impact should be mitigated with related expense and infrastructure cuts.
2. Captures more detailed business data, eliminating the need for complex, after-the-fact allocations within the profitability model.
By empowering business users to effectively link general ledger data to its operational activity-driver data (e.g. tying P&L data at the oil well level back to the operational KPIs behind it), profitability can be more accurately captured at the level of granularity required to recommend actions that protect or grow the bottom line.
3. Aligns the definitions used in standard and actual costing so that the profitability model can make accurate comparisons.
When business models are under assault and the old assumptions no longer hold, this ability is more crucial than ever.
4. Enables the selection of appropriate profitability objects.
This is a key element in building an effective profitability model, and it makes the data actionable and organised for decision making and immediate execution.
5. Overcomes the limitations of typical allocation and assessment schemes found in ERP or activity-based costing/management software.
Next-generation solutions accomplish this by working inside of an analytic database, where they can directly leverage the most granular financial and non-financial data available.
A well-built, multidimensional profitability solution becomes a solid finance foundation, especially when coupled with a single, integrated analytic data platform or similar cloud-based business intelligence platform. Technologies such as these not only help define and run your profitability model, but they also offer the ability to make changes quickly, run ad-hoc analyses, manage very large data sets and provide reporting and dashboarding beyond what’s available with ERP solutions. What’s more, this type of finance foundation can ultimately serve as the single source for all of the diverse types of analytics performed within the CFO department, because there is a direct link back to the General Ledger. A game-changing approach like this is well-suited to the tumultuous change impacting oil and gas, financial services, healthcare and numerous other industries today.