What is data analytics?
Have you ever wanted a quick way to gain a deeper understanding of your clients’ or organization’s business to deliver greater insights and value?
What is data analytics?
And what does it mean for accounting
and finance professionals?
Have you ever wanted a quick way to gain a deeper understanding of your clients’ or organization’s business to deliver greater insights and value?
Data analytics
is your answer.
Data analytics uses raw facts and statistics to analyze trends and patterns, identify anomalies or extract other useful information to reach conclusions and see opportunities. It’s about using information to make data-driven decisions.
Read on to learn more about the opportunities for CPAs in data analytics.
Data Analytics in 60 seconds: What you need to know
Types of data analytics
There are four types of analytics, ranging from simple to complex.
- Descriptive analytics — focuses on past information; what happened?
- Diagnostic analytics — focuses on the cause of past information; why did it happen?
- Predictive analytics — focuses on the future; what is likely to happen?
- Prescriptive analytics — focuses on the best option; what action should be taken?
Most finance and accounting professionals use descriptive and diagnostics analytics in their day-to-day work. However, the real value for you and your firm or employer is in understanding how to leverage predictive and prescriptive analytics.
We’ll share more later about how you can develop those skills through our free CPE Digital Mindset Pack and other learning resources.
Why data analytics?
Data analytics offers tremendous advantages for organizations of all sizes. In fact, it may be especially beneficial to small- and medium-sized companies as it can result in low-cost ways to drive revenue and improve margins.
The insights gleaned from data analysis can help you make recommendations that can:
- Boost operational performance.
- Increase profits and reduce costs.
- Improve the customer experience.
- Identify and prevent fraud and risk.
- Meet compliance requirements.
- Raise competitiveness.
If you’re an auditor, you can use audit data analytics, or ADAs, to improve the efficiency and effectiveness of financial statement audits. You can use this technique to perform risk assessment procedures, tests of details and sometimes analytical procedures.
Need another reason why you, as a CPA, should embrace data analytics? It can boost your career. CPAs with data analytics skills are in high demand.
Organizations are increasingly looking to use data to make critical strategic moves, and CPAs have an opportunity to lead this charge. Your technical expertise, coupled with your analytical mindset and holistic knowledge of the business, positions you perfectly to leverage data analytics to benefit your firm or organization.
Big data is
big opportunity
The spread across sectors
Big data, or data of high volume,
high velocity and high variety, offers organizations an opportunity to tackle problems they would have otherwise not been able to handle.
Why? Because big data can give you a unique view of a situation. It aggregates data from multiple sources — both internal and external and financial and non-financial — and, if analyzed correctly, can provide insights to help organizations make important strategic decisions.
The definition of big data in Figure 1 illustrates how enterprise data and financial data can be viewed as subsets of big data now available to a business. And it’s growing rapidly — data from outside the enterprise are proliferating on websites, in social media and other forms of communication across the internet.
1. Financial data
Standard financial metrics, well-tracked and understood
2. Enterprise data
The above, plus broader operational and transactional data that may be used to bolster analysis and forecasting
3. Big data
The sectors that initially made the most use of data were those that had the most — retailers, insurance companies, banks and airlines. Now, businesses in almost every sector use data analytics to improve offerings, enhance the customer experience and make better-informed decisions.
Figure 1: Big data defined
Big data isn’t just about improving services and efficiency levels.
It can have applications in every aspect of the business model and across multiple sectors. Harnessing data thru data analytics can lead
to the following enhanced business outcomes:
1. Farming — Tractors with sensors can collect data on seeding rates, crop yield and ground conditions, allowing farmers to predict production rates more accurately. Farmers can also analyze weather patterns to better prepare for poor conditions.(i)
2. Manufacturing — Manufacturers use advanced analytics to manage the risk of potential faults in equipment and product anomalies during production. They also are using it for forecasting, inventory management and production planning.(ii)
3. Retail — Retailers use data to forecast customer demand and understand their preferences, allowing them to become more proactive and better able to predict behavior. Big data also is used to create new digital product offerings.(iii)
4. Transportation — Players in the transportation industries (such as airlines, rail and trucking companies) use predictive analytics to manage their costs through preventative maintenance scheduling, inventory parts management and warranty claim management.(iv) The airline industry uses analytics to understand customers, predict demand and optimize pricing.(v)
5. Telecommunications — Telecommunications providers use analytics and big data to reduce customer acquisition costs, segment target subscriber audiences and rank prospective subscribers according to their propensity to buy.(vi)
6. Financial institutions — Banks and insurance companies use predictive analytics software for fraud analysis,(vii) while credit card companies use analytics to manage credit lines and collections.(viii)
7. Cities — City administrators increasingly use big data to understand their citizens’ needs and proactively plan for needs in transportation, policing, health care and more.(ix)
8. Education — Educators use data from student tests and assessments to determine patterns and performance levels. Such information helps them adapt courses and tailor the way they teach.(x)
9. Health care — To improve health care delivery and reduce costs, health care organizations use big data analytics to examine large amounts of structured and unstructured data to improve the efficiency and quality of care.(xi)
How finance can leverage data analytics
Digitizing the finance function has always been a priority for CFOs, but COVID-19 has accelerated that mandate.
CEOs and boards are looking to finance to provide real-time financial information and data-driven insights to guide organizations in today’s uncertain times.
Global forces are also expanding and shifting the finance team’s role — from transactional, back-office support to a strategic partner to the business. In this role, finance is being asked to do more with less. The automation of manual, time-consuming processes, coupled with the use of data analytics, can help you and your team meet these increased responsibilities.
Elevating the role of finance
Data analytics and process automation can help you and your colleagues bring greater value to the organization through:
- More accurate and real-time reporting
- More efficient operations
- Continuous improvement in
business processes
Better understanding of the customer
- Identification and prevention of risks
- Greater insights to support business partners and drive strategic decision-making
Getting started
If your organization is ready to start its data analytics journey, consider these recommendations:
1. Figure out what you’re trying to solve
Identify the problem. Pinpoint one or two challenges that your company is trying to solve. This will help you zero in on collecting the right data. If you don’t know what you’re looking for, you might end up with an extraordinary amount of useless data and no real insights.
2. Start small
Don’t botch your first shot at data analytics by going too big. It’s easy to make an error that will cost the trust of your leadership. Go slowly and prove your successes one data analytics project at a time.
3. Tell the story
Collecting the right data to draw insights is just one part of the process. You also need to be able to present the data and your insights in a format that’s easy for non-finance people to understand. Leverage data visualization tools to help you tell your story to your CEO, board and business partners.
How CPA firms can leverage data analytics
Meeting your clients’
individual needs
Your clients have a lot of untapped data. You are in the perfect position to aggregate this data to better understand your clients’ businesses and what makes them tick. Data analytics will help you identify trends and anticipate client needs so you can provide strategies to help grow their business.
A holistic picture of your
clients’ finances
Some accounting firms leverage data analytics to better serve their tax and financial planning clients. These firms are extrapolating specific information from a tax return and then use data analytics to aggregate it with other financial data to get a holistic picture of their clients’ finances.
New business
opportunities
Many organizations recognize the value of data analytics but need help getting started. If your firm has the right expertise, you can offer data analytics advisory services to help companies implement the technology.
Improving the efficiency
and effectiveness of audits
Audit data analytics, or ADAs, are a technique that can help your firm leverage current technologies to move toward a more data-driven approach to planning or performing an audit.
ADAs make it possible for financial statement auditors to improve the efficiency and effectiveness of audits by:
- Enhancing their understanding of an entity’s operations and associated risks, including the risk of fraud
- Increasing potential for detecting material misstatements
- Improving communications with those charged with governance
You can use ADAs to perform a variety of procedures to gather audit evidence. As you process and analyze the data, you might gain new insights that you can share with clients.
The importance of good data
Data can be a powerful tool to guide business decisions. But first you need to make sure it’s reliable, complete and accurate. You need to know the purpose for which it was generated and whether it’s complete and reliable for that purpose. The AICPA’s criteria for evaluating a set of data can guide you in determining the relevance and integrity of data.
Audit Data Standards
The AICPA’s Audit Data Standards can also help create a standardized, repeatable process for gathering data in a useable format. These non-authoritative, uniform IT standards identify the key information that auditors need and provide a common framework to standardize client data. Before performing an ADA, check with your client to see if they follow these standards. If they do, you can spend less time formatting the data and more time on analysis.
How to get started
with data analytics
Where are CPAs and where do they
need to be?
The gap is widening between the skills business leaders are looking
for in professionals and the skills accounting and finance
professionals possess.
Our Agile Finance Revealed research showed that only 10% of finance teams have the skills necessary to support the organization’s digital ambitions. A similar skills shortage also likely exists within CPA firms.
So, what does this mean for you? It’s time to upskill. CPAs with digital intelligence — knowledge of new technologies (such as data analytics and automation) and an understanding of how to apply them — are well-positioned to bring incredible value to clients and employers. Plus, firms and employers are seeking talent with this unique skill set.
Here’s the good news. CPAs already have a head start. Your technical expertise and analytics skills, along with your knowledge of the business, make it relatively easy for you to learn and leverage data analytics skills to bring greater insights to those clients and organizations. Some of the data analytics skills you’ll need specifically include:
- Finding and generating data and data sources
- Understanding your clients’ or organization’s data ecosystem
- Understanding the business requirements of data gathering
- Ensuring data quality and strong governance
- Relating data to ROI, financial value and executive decision-making
- Being able to look at data and see patterns and trends that lead to greater insights
- Visualizing and storytelling
Start your data analytics journey
When it comes to data analysis, partnering with those outside your organization (like vendors and experts), as well as those inside (like IT and your research team), is the area of greatest opportunity for CPAs. These partners can help you identify and aggregate the right data sources so you can focus on analysis and insights.
Know your role
Employers and firms don’t need you to take the role of information technologists or data scientists. They want you to be the champions of evidence-based decision-making. They need you to translate analytical insights to improve clients’ or the organization’s prospects, performance and compliance. CPAs also have the professional discipline and ethics necessary to help ensure data quality and security.
Develop your skill set
Growing your knowledge of data analytics will enhance your employability and value to your organization and clients.
To future-proof your career, you’ll need to develop an ethos of self-reliance, adaptability and lifelong learning start by downloading the free CPE Digital Mindset Pack offered to all AICPA® members. Check out additional free resources in the next section to get yourself up to speed.
Chartered Global Management
Accountant® (CGMA®)
CGMA is the most widely held management accounting designation in the world. It distinguishes more than 150,000 accounting and finance professionals who have advanced proficiency in finance, operations, strategy and management. In the United States, the vast majority also are CPAs. The CGMA designation is underpinned by extensive global research to maintain the highest relevance with employers and develop competencies most in demand. CGMA designation holders qualify through rigorous education, exam and experience requirements. They must commit to lifelong education and adhere to a stringent code of ethical conduct. Businesses, governments and not-for-profits around the world trust CGMAs to guide critical decisions that drive strong performance.
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Association of International Certified
Professional Accountants
The Association of International Certified Professional Accountants® (the Association) is the most influential body of professional accountants, combining the strengths of the American Institute of CPAs® (AICPA®) and the Chartered Institute of Management Accountants® (CIMA®) to power opportunity, trust and prosperity for people, businesses and economies worldwide. It represents 650,000 members and students in public and management accounting and advocates for the public interest and business sustainability on current and emerging issues. With broad reach, rigor and resources, the Association advances the reputation, employability and quality of CPAs, CGMA designation holders and accounting and finance professionals globally.
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Association of International Certified Professional Accountants
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Footnotes:
i IT ProPortal, “How big data is transforming every industry”
ii eWeek, “BMW Using IBM Predictive Analytics in Auto Production, Repairs”
iii McKinsey & Company, “The seven traits of effective digital enterprises”
iv SAS Global Forum 2012, “Leveraging Analytics in Transportation to Create Business Value”
v Datanami, “How Big Data Helps Airline Profitability”
vi Deloitte, “Opportunities in Telecom Sector: Arising from Big Data”
vii Computer Weekly, “SAP: UK, US companies hit automation barrier with predictive analytics”
viii TIBC blog, “How Predictive Analytics Turns Banks into Fortune Tellers”
ix The Programmable City, “Predictive analytics in the city”
x Disrupter League, “big data in education big potential or big mistake”
xi SAS, “4 ways data analytics is changing and benefiting healthcare”
