Why Financial Analytics is Failing Your Business, and What You Can Do

Most leaders today understand the importance of financial analytics and have invested their time and effort to monitor and disect their financial performance.

Oftentimes, however, financial analytics can be simple repetition of outcomes, and masque the actual drivers of performance, while failing to provide a sense of the road ahead.

Why Financial Analytics is Failing Your Business

According to Gartner, the misuse of financial analytics can cost companies almost 1% of revenue per decision.

This misuse frequently comes down to a lack of clarity in the business problem, and and ineffective use of data and insights in a way more commonly applied to operations, marketing or sales. But, there are changes you can make to your approach to financial analytics that will help drive outcomes and insights.

Establishing a Collective Outlook of Business Goals and Triggers

Developing a financial analytics blueprint is a foundational aspect of any strategy for financial insights, and there are a variety of foundational building blocks you may consider.

Business Unit performance: Which functional and operational areas are most driving financial outcomes, and which are unprofitable or under performing?
Business case evaluation: If you’re considering making further investments, understanding the expected return on investment or outcomes relative to the objectives of the business case is foundational. These business cases can be product, technology or even human capital related, depending on the investment.
Customer financial analytics: Which customers are adding the most value to your organization, relative to their cost of acquisition and support? Which customers are underperforming?
Key Financial Performance Indicators (KPI): What are the most tangible and relevant indicators of your organization’s financial performance? How will you measure and maintain insight on these?
Operation costs: Controlling costs is critical for any organization, and maintaining insight and monitoring trends is a vital aspect of any financial analytics process.
Predictive analysis: Both internal and external factors can drive outcomes. Understanding and leveraging past outcomes and current factors together can help you understand and forecast what’s to come.

Key Questions to Ask as You Embark:

Team size: Are you properly staffed and supported by a team that can provide the insights you need? While your team doesn’t need to be massive, it needs to have the scale and capacity support you.
Skill sets: The line between financial analyst and data scientist is becoming more blurry by the day. You need skills to acquire, analyze, present and interpret information in a meaningful way.
Data: Does your financial planning tool have the supporting infrastructure to capture and analyze information? Are you leveraging macro economic or other external information to help derive insights and projections?
Tools and technology: Legacy financial systems can inhibit analysis or require so much management overhead that your team can’t spend time on analytics. Consider new, more flexible and cloud-based tools for financial insights.

Create Simple Pathways to Act on Financial Analytics

Your team should create insights that use relevant data. This kind of data will engage the user and prompt discussion. As a result, taking action will become easier. To do this, your organization could:

Use situational analysis
Bake commentary and opinion into the reports
Enhance access to the reports
Adjust You Approach Financial Analytics

Most companies that successfully use financial analytics regularly realign their approach. These companies first focus on business decisions and the information needed to support them, and then concentrate on the analytics.

This approach enhances the company’s ability to expect and better plan for failure. These companies also place data scientists on their finance team. Having these professionals in the finance department makes any change easy to execute.

The Importance of Working With Qualified Data Scientists

To ensure you effectively incorporate this strategy, you will need well-qualified data scientists possessing advanced analytics skills and experience with financial information. They will also need experience working with financial reports.

In addition, they should know statistics, operations, and predictive analytics. They need these skills to help the finance team define, develop, and apply this technology. They can also create clear data governance roles and responsibilities.

Realistically, you may require more than one person to accomplish all of these projects. The expertise required for each stage differs, and certain stages precede others. Strategically staffing to help your organization optimize your financial analytics will be key toward long-term success and succeeding in a competitive market.

How an Analytics Talent Partner Can Help You Find The Top Data Scientists You Need

Because of the data science skills gap, competition for talent is fierce. However, working with a talent partner will help you find the right candidates. These candidates understand the hard and soft skills to get the job done. A talent partner can help you find temporary or permanent team members. With the range of software and computational knowledge required across all data positions, evaluating the hard skills for these financial analytics roles can be challenging. Are you comfortable assessing the competency of these candidates?

Chisel Analytics can find the right data science and analytics talent for your team. Our proprietary skill assessments use six key elements, which allow us to vet top talent. This assessment ensures that you hire the most qualified analyst for your critical needs and accelerates your meeting your revenue goals.