How To Improve Your Data Analytics Results
Today, the biggest challenge with accounting data analytics is how quickly the sheer amount of data available can become overwhelming. As the utilization of data in accounting continues to grow, it becomes a challenge to determine which data is relevant and essential to make more informed decisions. How do you find and separate the relevant data? You need to know your audience and what you’re trying to accomplish and utilize technology to prevent information overload.
Identify Your Audience: While the data does not change, the story that it tells may vary from person to person. Different stakeholders may have very different questions. Knowing who will be asking these questions is just as important as the question itself. Considering time and billing data, staff and seniors would be interested in how they compare to their peers, such as details about where they are exceeding expectations or falling behind. However, managers will not want quite that level of detail, preferring a summary view that highlights only those who fall outside the first or second standard deviation.
Managers and partners may be interested in learning more about staff efficiency. They would benefit from an analysis of which staff are most effective at various types of engagements to assist with planning. If the audience is just you, it is also important to identify that. All too often, when we are the only audience, the question becomes secondary, and analysis becomes the purpose – which is not the best use of time.
Know What You Are Trying to Accomplish: To perform an effective analysis, you need to have a question, purpose, or objective. A poorly constructed question can lead to costly and time-intensive data reviews that do not accomplish anything. Before diving into the data, determine what you are trying to discover. Data analytics results will only be as good as the questions you ask. When preparing your questions, consider your audience, strategic goals, and budget. If you are struggling with understanding what questions to ask, start broad, but do not stop there. While it is often helpful to start broad, the question needs to be specific to get valuable and actionable insights. Some questions to ask yourself include:
- What is the goal of this analysis?
- What decision-making will it facilitate?
- What outcome would be considered a success or a failure?
Implement Automation to Prevent Information Overload: Consider the data accounting firms and tax preparation businesses often track without thinking about it. There is internal data, from time tracking and how clients are served to practice management data such as billing, collections, business development, and client data, which is information about the client collected during the engagement process. Also, some data is a mix of the two: client and prospect interactions with internal content such as emails, webinars, websites, and social media. Technology has allowed us to collect the data listed above and so much more. Technology has also allowed us to perform our data analysis faster and on a much larger scale. But there are downsides to all advances – and for accounting data analytics, information overload is one of them.
Although technology created the problem of too much data, it can also help find the relevant data. Advanced technologies like machine learning and AI can automate the base data analysis, which gives structure to unstructured data and provides accountants with the most pertinent information. With automation sifting through the data, we can perform higher-level data analysis and understand how to shape the answer for intended audiences.
From technology-based accounting solutions to management information, analysis, and reporting, Talley LLP is the premier business consulting firm for entrepreneurs and their closely-held businesses. For more details about leveraging your business’ data technology, contact Talley today.