Many accounting professionals already use data analytics to identify trends in financial statements and zero-in on unusual items that require further investigation, but they have an opportunity to take their use of data to the next level.

Over the past decade, data analytics has become a priority for businesses of all sizes. Organizations in every industry must understand which products and services drive sales, know when to hire, gain insight into supply chains and prevent fraud. To do so consistently, they need to harness the power of big data, which can provide a significant competitive edge over competitors and enable better delivery of products and services.

Accounting professionals are uniquely positioned to help organizations avoid misrepresentation in data analytics, and to interpret the insights yielded by that data. Many accountants already use data analytics to identify trends in financial statements and zero-in on unusual items that require further investigation, but they also have an opportunity to take their use of data to the next level.

Benefits of data analytics

Businesses generate a rich variety of data, and that data contains valuable insights if you know how to unlock them. Some areas that an accounting professional can help your organization discover insights through data analytics include:

  • Customer data. Businesses may collect customer information from their websites, social media pages, phone calls, live chats, emails and point-of-sale systems. This data can be used to create comprehensive customer profiles and provide a more personalized customer experience.
  • Business decisions. How will changes in your pricing or product offerings affect customer demand? How might a new competitor entering the market impact sales? How much additional revenue could a new marketing initiative create? Firms can use data analytics tools to predict the results of changes and make better business decisions.
  • Operational efficiency. Gathering and analyzing data around an organization's processes and procedures can help to identify where loops and bottlenecks exist, enabling the organization to streamline operations and improve results.
  • Talent hiring and retention. Hiring managers no longer need to rely on their "gut feelings" to determine whether a candidate is suitable for a role, when to promote a valued team member and who is most deserving of a performance bonus. HR analytics tools can gather information for recruitment, onboarding and employee performance to help talent professionals make strategic decisions.

3 strategies for avoiding misrepresentation in data analytics

"You can have all the data in the world, but how you make sense of it to fuel your business forward is where the accounting professionals can shine as trusted advisors," says Heather Sperduto, ADP's Vice President of Sales Operations.

To that end, here are three ways accounting professionals can help ensure a firm's data leads to actionable insights.

1. Start with clean data

Whatever data analytics you're performing, your analysis is only as good as the data you start with.

You may have information spread across different databases, CSV files, spreadsheets or other formats. All of that data needs to be gathered, properly formatted, cleaned up and structured to be useful. This means removing corrupt, irrelevant and duplicated data, and pulling in any missing data to ensure you don't have any missing values or records.

There are numerous data cleaning tools you can use to facilitate these processes, so do some research to find out which options would be the right fit for your organization.

2. Ask an insightful question

It's tempting to jump right into running reports, performing tests or applying models to data to see if you can find anything. But you'll have better results if you start by determining which questions you want to answer and formulating hypotheses.

If you don't start with a hypothesis, data can play tricks on you. Everyone could be susceptible to confirmation bias, mistaking correlation with causation or other data myths, traps and fallacies. To help reduce errors tied to these factors, start with a question or assumption. For example, you might ask: "Why are we having trouble holding on to managers?" From there, you might hypothesize: "I think it's because we're not paying competitive salaries."

Then look at the data to see if it supports your hypothesis. For example, if your organization's management salaries are within the 95th percentile of your industry, you'll likely need to develop a new theory.

3. Tell a meaningful story

Once you find an answer to your question in the data, don't simply present the numbers to your manager, shareholders or other parties. Instead, use your data to craft a story that communicates context, insights and recommended actions.

Remember the "5 Ws framework," which asks Who? What? When? Where? And why? This framework — along with visual representations such as charts, graphs and diagrams — can make it easier to understand and engage with the data. When people can easily understand the data, they're more likely to take action based on it, and actionable insights are the key to success.

Learn more

If you're looking to generate deeper and more valuable insights from your organization's people data, ADP DataCloud can help you find them. And if you're an accountant, learn how Accountant ConnectSM can help you strengthen strategic advisory services with client insights and compensation benchmarking.

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