In the rapidly evolving world of business, the ability to make informed decisions is paramount. Data analytics has emerged as a powerful tool, enabling professionals, including those with CGMA credentials, to derive actionable insights from vast amounts of data. While the emphasis here isn’t solely on CGMA professionals, their financial expertise combined with data analytics can be a potent combination.
Here’s how data analytics is reshaping the decision-making landscape:
1. Unveiling the Essence of Data Analytics
Data analytics is the process of examining raw data to draw meaningful conclusions. Through advanced algorithms and statistical techniques, it reveals patterns, correlations, and trends that might otherwise remain hidden. This process transforms a sea of numbers into actionable business intelligence.
2. Spotting Trends with Precision
One of the standout benefits of data analytics is trend identification. By delving into historical data, businesses can discern patterns that suggest market shifts, evolving consumer behaviours, or potential operational bottlenecks. Recognizing these trends allows for timely strategy adjustments, ensuring businesses remain proactive rather than reactive.
3. Comprehensive Risk Assessment
Every business venture carries inherent risks. Data analytics offers a refined lens to assess these risks. By pooling data from diverse sources, potential challenges—be they financial, operational, or market-driven—can be identified. Armed with this knowledge, businesses, with the guidance of professionals like CGMAs, can devise strategies to navigate these challenges effectively.
4. Peering into the Future: Forecasting
While crystal ball gazing isn’t within the realm of data analytics, forecasting future performance comes close. By analysing historical data in conjunction with current market dynamics, businesses can generate projections for sales, revenue, and other key metrics. These forecasts serve as invaluable roadmaps, guiding future endeavours.
5. The Agility of Real-Time Decision Making
In today’s fast-paced business environment, agility is crucial. Real-time data analytics equips businesses with current insights, facilitating swift and informed decisions. Whether it’s a pricing adjustment in response to market fluctuations or a resource reallocation to meet a surge in demand, real-time data ensures businesses remain nimble.
6. The Role of Professionals in Data-Driven Decision Making
While the focus isn’t solely on CGMA professionals, their expertise in financial analysis, coupled with an understanding of business operations, makes them well-suited to interpret data analytics insights. Their role, though not exclusive, is pivotal in translating complex data findings into coherent business strategies.
How data analytics has helped businesses
Here are some real-world instances where data analytics has helped a business.
Money Lending
Upstart is a US-based online lending platform that uses data analytics to make personal loans to borrowers with limited credit history. Upstart collects data from a variety of sources, including education, employment, and banking history, to develop its own proprietary credit scoring system. This system allows Upstart to make loans to borrowers who would otherwise be rejected by traditional lenders. As a result of using Upstart, borrowers have been able to access credit at lower interest rates than they would have been able to get from traditional lenders. For example, one borrower was able to get a personal loan with an interest rate of 7% from Upstart, while he would have been offered an interest rate of 20% from a traditional lender.
Consumer Credit
PeerIQ is a US-based data and analytics company that uses data analytics to help finance companies manage and analyze risk in the consumer credit market. PeerIQ collects data from a variety of sources, including credit bureaus, loan originators, and asset managers, to create a comprehensive profile of each borrower. This data is then used to develop risk models that can predict the likelihood of a borrower defaulting on a loan. As a result of using PeerIQ, finance companies have been able to reduce their loan losses and to make better lending decisions. For example, one finance company was able to reduce its loan losses by 20% after using PeerIQ.
Smart farming
Farmers Edge is a Canadian precision agriculture company that uses data analytics to help farmers improve their yields and reduce their environmental impact. The company collects data from a variety of sources, including satellites, sensors, and weather stations, to create detailed maps of each farmer’s field. This data is then used to develop personalized recommendations for farmers on how to manage their crops. For example, Farmers Edge can recommend when to plant, irrigate, and fertilize crops, and how to control pests and diseases. As a result of using Farmers Edge, farmers have been able to increase their yields by up to 15% and reduce their water usage by up to 20%.
Fraud detection
Sift is a US-based fraud detection company that uses data analytics to help businesses identify and prevent fraudulent transactions. The company collects data from a variety of sources, including credit card transactions, login attempts, and device fingerprints, to create a risk profile for each transaction. This risk profile is then used to identify transactions that are likely to be fraudulent. As a result of using Sift, businesses have been able to reduce their fraud losses by up to 90%.
Cybersecurity
Darktrace is a UK-based cybersecurity company that uses data analytics to help businesses identify and prevent cyberattacks. The company collects data from a variety of sources, including network traffic, email, and endpoint devices, to create a baseline of normal activity for each organization. This baseline is then used to identify any unusual activity that may indicate a cyberattack. As a result of using Darktrace, businesses have been able to detect and prevent cyberattacks that would have otherwise gone unnoticed.
Challenges of Using Data Analytics in Business Decision-Making
While the benefits of data analytics are numerous, it’s essential to recognize the challenges that come with it:
- Data Quality: The foundation of any data analytics endeavour is the quality of the data itself. If the data is riddled with inaccuracies or is incomplete, the subsequent analysis will be flawed, leading to potentially misguided decisions.
- Data Volume: The digital age has ushered in an era of data abundance. While having a wealth of data can be advantageous, it also presents challenges in terms of storage, management, and analysis. Sifting through vast datasets to find relevant insights can be a daunting task.
- Data Complexity: As businesses evolve, the data they generate becomes more intricate. This big data complexity can pose challenges in analysis, requiring advanced tools and expertise to extract meaningful insights.
- Data Security: With the increasing value of data, it has become a prime target for cybercriminals. Ensuring data security is paramount. Businesses must invest in robust security measures to safeguard their data from breaches, cyberattacks, and other threats.
Conclusion
In the contemporary business landscape, data-driven decision-making is not just an advantage; it’s a necessity. Data analytics provides the tools to unlock insights hidden within data, facilitating informed and strategic decisions. And while CGMA professionals are just one of the many players in this arena, their financial acumen combined with the power of data analytics ensures businesses are well-equipped to thrive in an ever-competitive market.
