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.
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.
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.
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:
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.
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.
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.
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The need to leverage data has created a new arms race for data science and AI professionals. Chisel Analytics can help organizations find the professionals they need to quickly scale their capabilities. #DataScience #AI https://t.co/rkrLit9Lju pic.twitter.com/kLrIhcPkEp— Chisel Analytics (@chiselanalytics) April 23, 2019
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