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How to Best Utilize Forecast Accuracy in the Office of Finance

Insurance finance practitioners know the drivers of an efficient planning and forecasting model. Unfortunately, they’re often difficult to build: Often, finance leaders face long cycle times, with thousands of hours spent in planning cycle. Sometimes, data integrity issues prevent them from trusting the data. In many cases, their systems are too difficult to use, either because they’re overly complicated or because they’re unstable. And on top of that, many companies have too much dependency on tribal knowledge. Whatever the reason, you need your planning and forecasting to work so you can stay profitable.

Let’s look at what takes a typical forecast process so long to complete. One major prerequisite for a forecast is a legal entity plan. To complete that plan, an insurer must first derive the operational plan. Doing this in either an enterprise planning system or in conjunction with offline excel models, you can expect it to take roughly 9 to 12 weeks. Next, the company must go through an exercise to account for its products through product-based allocations. Add on another three to five weeks. And depending on the type of insurer, they may need to undergo more downstream multi-step allocations, account for intercompany adjustments, make reinsurance adjustments (if applicable), and finish up other miscellaneous adjustments for another three to five weeks.

Bottom line: The annual operating plan can take as much as 22 weeks to create—close to half a year. In the time it takes to make your plan, both your strategy and economic conditions can drastically change, making your original plan less valuable. On top of that, this estimate doesn’t include time for collaborative planning, driver-based assumptions, analysis, or review with necessary management and leadership.

There are better ways to build your model.

This is where the introduction of modern enterprise planning systems can make a big difference for your company—and it’s especially important for insurers. Your primary KPIs are controllable expenses, revenues, losses, and cash flow transparency. If you can get to these numbers quickly, you’ll have a strong start for a faster planning process.

We recommend a consolidation model like the one below with a driver-based profit and loss (P&L) outline which pulls from various ‘spoke’ models. These models are where key data sets are housed, such as underwriting (GWP projections, earnings), allocations (divisional/corporate expenses, actual), controllables (associate-level workforce planning, RSUs, office space), and likely other associated inputs. With these consolidated, you’ll have a summary starting point.

Taking a transparent design and driver-based approach to your insurance schema, you can potentially not only streamline siloed operational/entity planning processes, but also scale business-owned outcomes with elasticity around changing needs of the business. Global insurers can become nimbler and more proactive on the mechanics of the forecast across various operational and legal entities.

None of this is new science. It’s simply about achieving quality and consistent execution across the enterprise, beginning top-down in the SLT and management rooms driving strategy, funneled into the divisional practitioners who are typically the unsung heroes during budget season. If your organization is able to achieve good documentation and validation, you’ll have less need for multi-year, multi-million-dollar legacy hardware investments. Instead, you’ll have design schemas that empower LOB leaders across your insurance business.

Overcome barriers to change for insurers.

Change is challenging, but the leading insurers have made big strides over the last five years in overcoming barriers to change, allowing them to unlock enterprise-level practices. Barriers include:

  1. Many insurers have a lengthy business case review process, making it more difficult to get approval for even a needed new system.
  2. Sunk cost fallacy. If your company has spent over 15 years in time, money, and resources building homegrown assets, there can be a resistance to change.
  3. Too many stakeholders. A company with stakeholders across finance, actuarial, compliance, group, and more will have lots of people and lots of processes that need to come along with the new solution—not to mention the numerous technology systems that it’ll need to integrate with.
  4. Key person tech dependency. With any of the three challenges above, you often also have a shortage of SMEs who can make major changes to the system—a key person who all decisions go through.

All of these barriers come down to change management, and to move forward, organizations will need a strategy to overcome the fear of change. The common misconception is that change management begins when new systems/processes are implemented. But the only successful transformations, especially within the Insurance industry, happen where change begins as “forced storming” from internal stakeholders. These stakeholders are often referred to as change agents, or champions who challenge the process status quo, often to be met with expected conflict.

Get your transformation started.

Insurers should be ready for more change to come. AI/ML and natural language querying show that organizations that invest in forward-looking systems can take advantage of predictive scale. Organizations that have their models already solidified before AI/ML change everything will be better positioned to make better predictions and smarter decisions.

If you’re an insurer aiming to get your forecasting in order, a strategic partner can be a major help. Spaulding Ridge uses Anaplan to help companies in insurance and across the financial sector improve their systems for better financial performance. We’d be happy to help you too—just reach out.