The lack of quality data and automated processes can hinder the rate of transformation at many businesses. Studies suggest that the potential for improved IT-finance collaboration is very under-explored. It’s important considering how much financial data supports the development of a positive strategy.

Jason Child, the CFO of Saas business Splunk, describes his time at Amazon within the Financial Planning & Analysis department. In 1999, his team performed a cost-benefit analysis of the free shipping system, a key driver of significant growth at Splunk. They compared free shipping to a 10% discount on each order and quickly found that free shipping generated far more business.

A focus group explored the feasibility of this idea with their CEO and created the concept of a 5-day delay on free shipping, separating it from those that pay for shipping. It resulted in the development of Amazon Prime, which has close to 200 million members, each paying $13 a month. This process is an example of data-focused financial analysis (FP&A), and the potential it has in transforming a value proposition, operational model or even the entire business plan.

Like most data-driven processes, FP&A is influenced by reporting, control and compliance. Inefficient data processes and inadequate financial reporting results in costs in the region of $7.8 billion every year, according to a study by DataRails.

One of the most common problems finance teams face is the overall quality and reliability of their available data. While they may have access to accurate information, the data is vulnerable to inaccuracies due to being shared with other members over time and analysed by multiple teams. Often, data is shared internally via manual copy and paste processes. Financial businesses work in a complex, data-demanding environment but are falling behind when considering automation and data integration processes.

Collaboration between IT and Finance is critical in scenario planning as businesses continue to shift towards a stage of recovery after the pandemic. A report by Workday stated that nearly half of C-suite leaders were concerned their business was incapable of analysing real-time data and making informed decisions or responding quickly to unpredictable changes in the market. Finance leaders are experiencing challenges in delivering, reconciling and assessing high volumes of data. These hurdles are mainly due to less than half of those working in budgeting and planning activities claiming to use digital technologies to do their analysis. In contrast, around three-quarters of sales and marketing teams typically use automation. In short, it is of no value to having an answer to a question a few months down the line when you have to make a critical decision on something in the next few days.

Strategic FP&A is vital for integration, performance management, risk analysis and forecasting for multiple business areas. The reality is that finance teams are allocating too much time towards manual tasks like account reconciliation, investing time in managing and data organisation rather than analysing the information.

Since the pandemic, financial planning and analysis have progressed as businesses actively look for a greater understanding of their figures. Despite the movement in this market, many FP&A professionals still rely on manual tasks, such as correcting errors, updating reports and collecting data.

Factors like operations, technology and productivity all take a lower priority to the bottom line. Revenue forecasts are at the top of importance for CEOs because, ultimately, that is what defines capital flow in a business. Despite this clear recognition, only about 1% of the biggest companies in the world achieve their finance forecasts accurately, according to a study by KPMG. Discrepancies can cause a decline in investor confidence and result in a negative impact on share prices.

Gartner predicts that by 2024, nearly three-quarters of all new FP&A projects will expand beyond the finance world into other business areas. Cloud-based solutions are supporting the potential of extending automation past FP&A to other areas such as HR, sales and supply chain management.

Traditional systems working with finance operations still predominantly depend on manual entries and are more susceptible to errors and discrepancies. AI-based software has increased financial automation. Businesses that apply financial automation can accelerate and improve particular processes like financial close. Often this involves a long monthly process for recording and reporting transactions. Automating selected steps to this area can improve accuracy and reduces time applied to laborious tasks.

Other technologies such as robotic process automation (RPA) allow the auto-creation of documents from the predefined text and screen scraping to validate and consolidate financial data. KPMG predicts that businesses can gain cost savings of nearly 75% by automating finance operations, providing a quicker turnaround and reduced human intervention. Automation cannot replace the human element in financial planning. Instead, it can allow financial analysts to shift their focus away from daily reporting to focus on more insightful analytics and dynamic planning.

Imperial College London has announced the UK’s first degree to enable students to study a combination of economics, finance and data science. The new undergraduate BSc in Economics, Finance and Data Science plans to launch in October 2023.

The first of its kind degree offers an innovative approach towards leadership and prepares the new wave of economists, policy professionals and business leaders. The new qualification takes a different approach towards the study of economics and finance by integrating the importance of data science. The course has been designed by several leading academics from each core discipline, with support from public policy and industry leaders.

Utilising global-leading expertise in science, tech and business at Imperial, the new degree focuses on the rising demand for new professionals with academic experience in economics and finance, with the analytical knowledge supported with data science and coding skills. Professor Emma McCoy of the Imperial College believes education represents one of the most critical elements of global economic recovery from the pandemic and preparing for global disruption.

Students will gain the necessary skills to pursue many roles in industries including technology, finance, consulting and the public sector. Imperial College emphasises that the programme includes societal impact, diversity and sustainability within its core elements.

Dr Pedro Rosa Dias, the Academic Director of the programme, explains that we now live in an era of big data and has transformed the workplace and the way we recognise the challenges facing our world. The programme design and feedback from employers were relatively clear. We need the next generation of economic and finance graduates to have the ability to use data science to navigate businesses, public groups and international organisations within the digital economy of today.

Professor Emma McCoy of Imperial College London believes education is the most powerful force of our economic recovery from the pandemic and to manage further disruption. McCoy highlights that the students will become the thought leaders of the future.

The launch of this degree represents Imperial College’s support towards the next generation, influencing the discussions that will shape our future society. Successful individuals should expect to complete the course with a diverse skillset, a broad understanding of tackling global challenges and a flexible approach towards applying data in important decisions.

Industry leaders are starting to understand the role that ESG has on how businesses operate; they are looking for solutions that help them manage their ESG analytics. Environmental factors have a significant influence on our quality of life as well as considerable financial implications. 

The cost of climate-associated disasters exceeded $650 billion between 2016 and 2018. This number is forecast to increase further, especially when factoring in the impacts of the pandemic on the global economy. Due to the financial impact environmental issues have, more governments and businesses focus on meeting ESG standards. 

In finance, businesses should be including various ESG metrics like ESG market analytics, risk assessment, compliance and portfolio management to manage the investment process. Meeting the different ESG standards is complex. ESG-focused procedures require accurate and updated ESG information, which is challenging to obtain due to fragmented, inaccessible and scarce data availability.

Businesses like tech startup Viridian are trying to mitigate these hurdles by creating a centralised information platform for the ESG market. Viridian utilises big-data analytics, real-time monitoring and AI-driven alerts.

Viridian use advanced technologies to one of the most pressing challenges facing humanity: the environmental crisis. Technology and data represent a vital element in tackling climate and environmental challenges. 

Many industry leaders recognise the risks we potentially face in the future, whether it be physical, financial, through business or new regulations. Today’s finance industry influences many industries and plays a vital role in the environmental movement.

In the finance world, climate and environmental risks convert into material business and financial implications, raising concerns for finance companies worldwide. The finance industry needs to adapt rapidly and incorporate environmental factors within many financial processes. Various climate factors, market trends and environmental performances have a significant influence on investments.

ESG needs to be incorporated into various financial processes to avoid any disruption and to remain competitive. The challenge that many financial businesses are experiencing is the lack of ESG and climate-related data needed for effective analysis and assessment. Obtaining this data is particularly complex due to the fragmented and inconsistent nature of ESG data. Data analysis is how new tech startups like Viridian can play an important role.

Applying innovative big data technologies, combined with advanced analytics and AI systems, businesses gather the most accurate and valuable information from multiple data sources and present the data clearly and insightfully. Viridian provides a knowledge graph that effectively bridges the gap between customers in finance or government to the array of relevant ESG data, which is vital for the new economy.

Enabling simple access to ESG data, emissions, pollution and compliance to evolving regulations is very important to the finance industry. Viridian provides a flexible analytics service, enabling consistent changes in data, which is ideal for sustainable investment and climate risk assessment since both continue to evolve.

Utilising wide-scale data collection capabilities provides businesses with an accessible platform that is particularly useful for the complex areas of the ESG and environmental economy sectors.

Climate change is becoming a growing concern, and more people are taking more responsibility to make changes. Businesses like Viridian are making their progress by providing a platform that will support businesses, governments make a conscious decision on the importance of ESG.

As the finance industry significantly transforms through the rise of digital and technologies like blockchain become more established, the shift of data will inevitably present opportunities to cybercriminals. Studies suggest that banking and financial organisations are nearly 300 times more at risk of cyber-attacks compared to other businesses.

With the UK financial regulator raising concerns of potential threats of new cyber-related attacks, the industry needs to be prepared and protect itself against an increasing variety of new threats. The conventional security tools are not enough, and businesses need to implement an intelligent stance towards cybersecurity on effective management of detection and response.

Cybercriminals understand that finance businesses contain a large amount of confidential customer data. The industry is expansive and connected to other industries, making it even more appealing to potential cyber-attacks. Individuals are becoming increasingly more sophisticated in discovering and targeting particular areas within the finance market. The rise of remote working has created further challenges when monitoring potential attacks.

The pandemic has accelerated the rise of digital across the UK. The finance industry recognises the importance of investing in new technology to meet customer demands, improve operational response and manage potential risks. This broadening process, however, creates more security challenges for the finance industry. Despite the progression in digital, many banks continue to rely on traditional systems that fail to address the requirements needed for effective risk and compliance management.

Traditionally, business leaders have viewed digital progression and cyber security as separate entities with varied objectives and goals. This siloed approach can often result in finance businesses overlooking potential security weaknesses that have emerged due to accelerated technology changes. Businesses that integrate new systems and upgrades without the necessary security in place are potentially at risk. Maintaining a clear mindset throughout the digital transition is a vital part of developing and maintaining resilience to possible cyber attacks.

Finance businesses need to explore ways to reduce risks without incurring costs. The focus of cybersecurity should shift from prevention to detection, containment and response. The Cost of a Data Breach Report by IBM explains the importance of detecting how and when a cyberattack has happened and how to respond appropriately. Businesses that take a short term preventative approach and don’t invest in future strategies are often the ones that take longer to recognise that a cyberattack has occurred.

Combining AI, automation and human analysis enable enhanced visibility over particular systems, allowing businesses to detect and prevent cyberattacks. The methods and reasons for cyber attacks will continue to evolve, so the finance industry needs to be one step ahead without impacting the digital capabilities that individuals demand. The best way to improve cyber resilience is by creating a cyber security strategy based around Managed Detection and Response (MDR). Success relies on ensuring businesses have the appropriate processes and people in place to manage new technologies. With many businesses lacking the necessary security talent and capabilities required for operating an efficient MDR, working with a separate security specialist will be critical.

By collaborating with a trusted team of experts, businesses can benefit from an agile solution that builds customer confidence and secures data. In today’s continuously evolving cyber landscape, it will be the businesses that apply a proactive approach towards security management and implement a cyber security process that generates the benefits of a more solid and structured IT system.

Finance leaders have had to make critical business decisions faster than ever before, causing an accelerated focus on the importance of big data and predictive analytics. Implementing strategic decisions has become essential for finance leaders while businesses transform their finance systems and adapt plans to continue growing. With this rising pressure, predictive analytics has become an even more vital tool in supporting the current challenges and providing a competitive edge over other businesses.

Businesses recognise that the more use they make of their data in developing plans and building scenarios, the more they can be ready for future disruption and changes. A blend of predictive analysis and simulations will enable clear insights and scenario development. This process is becoming more necessary as unpredictable events, ranging from climate change to geopolitical, continue to disrupt business plans and all need to be accounted for.

Predictive analytics today plays a distinctive role in strategic and operational decision making, with many industry professionals stating that a decision without data input has little or no value. A report by Deloitte suggests that just under 50% of senior executives believe that the main benefit of applying analytics is its influence in driving better decisions. 

The responsibility of a CFO has become more focused on balancing resource management and enabling the continued growth of other strategies that may lie outside of standard operations. If a business has access to data, they will likely want to generate insights on what is happening and determine why these activities are happening. Companies want to harness this information and apply predictive models to gain a better idea of future trends.

The pandemic created a seismic shift in the role of the CFO and their importance in business strategy and responsibility in business model transformation. Generally, any transition period involves a drop in initial revenue, followed by a long term plan to improve this. The more analytical support available, the better strategic and operational plans a business can make to reduce the impact of this change.

Predictive analytics is generally associated with supply chains, marketing and HR. In finance, there are many opportunities to improve and automate financial reports. CFOs can utilise automation and predictive systems. They recognise that it is necessary to enhance resources and apply new technology. Those finance leaders that have taken on predictive analytics into particular areas such as cash, audit, FP&A are likely to have a competitive edge over other businesses. However, it isn’t a simple transition and will require upskilling of employees to gain the benefits of this transition in finance.

Upskilling finance professionals and delivering an environment where knowledge is shared is critical. It will reduce time spent on particular activities and strengthen the relations across the business.

Automation analytics will create a competitive advantage for businesses as it creates additional time and resources that work towards high-value activities. With the correct insights and processes, the overall time to value is reduced considerably. It allows for more time to focus on value-added activities and to establish new opportunities within a business. Companies today are working with a range of data sources which means that it is even more vital to have the necessary tools to analyse this information.

Establishing a clear data plan that can effectively combine different sets of information and make it available to decision-makers with the right insights is probably one of the biggest challenges businesses face right now. When a data plan comes together, it can deliver significant benefits to businesses and create a distinct competitive advantage over other companies.

How storytelling can create deeper connections and allow your audience to relate to critical financial data

In the world today, finance professionals have greater access to a range of data and information. More information, however, may not necessarily translate into meaningful and decisive action. What is vital for people in finance is deciphering how these numbers affect their role and the business. 

Factual information, numbers and lots of data can be challenging to understand. If information is displayed more interestingly and humanely, people are more likely to connect, remember and take action. Storytelling is one of the most impactful methods that has emerged over time to connect and share information with others. 

Becoming an efficient storyteller may not necessarily have to be such a challenge. It does, however, require time to discover a story that relates to your data and then determine the most appropriate way of presenting the information to your audience. One method of reducing time spent on this process is utilising automation, allowing finance professionals to focus on discovering and delivering key insights.

The concept of storytelling has grown in popularity, as more businesses adopt automation and recognise the impact it can have on finance professionals. Storytelling is establishing itself as a vital tool within finance, creating deeper connections within an organisation and building the required company culture.

Storytelling is often considered as something that requires a sophisticated narrative, but it doesn’t have to be this complicated. The key is creating an accurate and logical way of sharing insights and ideas. The concept of storytelling is predominantly focused on improving communication. The important part is ensuring you highlight what discoveries you have found with the data, particularly information that is important to your business or a client. If this step is forgotten then the rest of the process is redundant.

After determining the key data points, the focus is on presenting the main findings and delivering the core theme. Considering the problems and how this impacts your audience, followed by a summary of insights and possible solutions is an efficient way of developing your story. 

When converting detailed, data-focused financial details that many will not understand, you are effectively transforming numbers into something that is relatable and allows individuals to recognise the importance of the data. Visuals are often a useful complementary part of a story, displaying a visual representation of the information. Visuals, however, should support a story, and not tell the story on their own.

A business needs to understand its audience and its language when putting together a report or presentation. Considering what’s important to your users, what motivates them and ensuring they recognise the insights is critical.

How can finance leaders leverage analytics and cloud systems to improve their business functions?

Our workforce today is experiencing significant change. Technology and the rise of automotive products are transforming how processes are done and how senior leaders manage their business, particularly in the case of CFOs. In the last year, digital technology has accelerated the need for businesses to adapt their working models to remain flexible, smarter and efficient.

Businesses that enhance their focus on data and analytics to support their transformation are often considered more successful. Investing in these products, however, is only the beginning. There are several things financial leaders should consider to leverage the potential of analytics on the finance service.

Investing in cloud technology

Businesses are consumed in data but yet are still hungry for additional insights. The ability to utilise data insights can determine the success of a business, and while many leaders believe they are capable of leveraging data, studies suggest that those leading the way are experiencing a 7% higher revenue growth.

This process involves the following measures:

1. Real-time insights in data allow businesses to be proactive and explore what is happening through analysing trends and analytics.
2. Businesses will often interpret data in various ways. Cloud technology will allow finance leaders to measure data more flexibly and transparently. This will support overall decisions and ensure finance avoids any unnecessary or time-consuming efforts.
3. Being capable of benchmarking information is important for businesses to understand how they compare to others.

Businesses are looking towards the future and appreciate that investing in cloud and finance technology will ultimately benefit their organisation. For over 50% of businesses, the cloud has moved beyond an idea to a reality in terms of integrating cloud-focused HR tools. This represents a key force in transforming today’s workplace, enabling businesses to make smarter decisions. 

Create a clear plan

To enable growth, remain resilient and flexible, businesses need to ensure they have a clear strategy on how they can operate in the cloud. Consistent planning represents a key factor for exploring new growth options. An annual report is no longer sufficient. Applying tools like AI, ML and predictive analytics enable businesses to deploy reports and plans more effectively while reducing potential risk to their business.

Leverage the potential of collaborating data

Consolidating finance, HR and data in one place can create multiple benefits. It can lead to better outcomes while enabling each area to reach its own goals. Consolidating all information enables a business to think more holistically and ultimately make better decisions for the long term.

The success of a business will depend on whether your team has the necessary tools to be more efficient, flexible and operate securely. Being open and capable of collaborating are the new ways of working, and the cloud allows this in many ways. Not only will this lower time spent on manual tasks, but it also enables businesses to make real-time, data-driven plans to grow and attract the best talent.

Measuring results

For most, salary and benefits represent the biggest expense, meaning two major cost drivers are people related. Businesses often spend money on products and technology that fail to show ROI or direct benefits to employees. If employees aren’t satisfied, engagement will drop, and benefits to a company will be lost. This has become even more challenging as the pandemic has made it easier for people to move jobs.

With finance playing a critical part in business decisions, it must be capable of determining what data is needed and analysing it effectively to deliver the necessary actions. Measuring employee engagement and goals is one big step in talent retention.

Making the commitment

Cloud systems enable businesses to target specific talent and identify the skills and experience needed for the most vital roles. Not only will it improve finance functions, but it also enables HR teams to determine the best candidates, highlight potential engagement issues and identify what employees are looking for in a business.

Consolidating finance, HR and data in the cloud integrate valuable insights across your organisation, enabling teams a better understanding of their data, where there may be potential gaps and how to optimise particular areas to generate better and smarter results.

Unleashing the power of new data cloud solutions requires a smarter approach towards BI. For those operating in the financial services industry, Snowflake has become an established leader. The cloud-data platform is already used by approximately 6 out of 10 of the financial industry Fortune 500 companies. Now the business is looking to introduce a new financial services data cloud, a platform that integrates industry data and governance capabilities, including a range of customer solutions. By combining financial data and industry-specific tools into a single platform, Snowflake intends to support further innovation, collaboration and drive a new wave of fintech products.

For financial services businesses, connectivity is important, but to make the most of these new offerings, businesses need to explore ways to really put their data to work effectively.

Tell your story

Don’t assume that having large data sets means your business is smarter or will lead to better decision-making. Instead of having data spread across several platforms and lost in silos within your business, a new cloud solution let you access and deploy data where and when necessary. 

Connectivity and access to data represent only one of the challenges; you have to be able to use your data effectively. In reality, only a small fraction of financial employees appreciate how to use data effectively. For many, data tends to become overwhelming and complicate workflows or possibly be ignored altogether.

To unlock the value of their data businesses need smart systems that enable them to access data and allow for impactful storytelling tools to support managers, users and customers find value and meaning in their data. Individuals need data infrastructure that facilitates, rather than distracts from the creative process.

Personalise your data

This is particularly important for financial services businesses because when money is involved there is a potential risk that data can act as a barrier between a business and its customers. Providing people with numbers doesn’t necessarily empower them to make better decisions. It can lead to an assumption that customers will defer to what the data says without really comprehending what the information means.

New cloud solutions bring data closer to the customer and the related teams but we need storytelling tools to reveal the value and meaning within data and to be able to deliver real insights. Data’s value often comes down to the way it is used in genuine human interactions. Including a data storytelling element enables employees and customers to relate to information more freely and integrate it into workflows and other interactions.

Applying your data effectively

As new financial services data cloud gains momentum, businesses can use their connectivity to support data storytelling. We’ll see more benefits including, an accelerated path towards fintech innovation, smarter and more accessible data products and more effective collaboration. 

Using data efficiently is a multi-step process. Businesses have invested time and money collecting data from other sources and spent even more moving data into the cloud. Modern cloud systems are enabling organisations to unify their data systems and make them far more accessible.

The businesses that will lead the financial services industry will continue to innovate and utilise new cloud solutions. Today’s world is more connected, and data is far more accessible. To utilise the true potential of data we need to dedicate ourselves to innovation, leveraging and communicating our data. This means developing ways to make data more accessible to everyone and finding creative ways to tell compelling stories with it.

Big data has been a trending term for some years and represents a significant potential that many businesses are only starting to appreciate. Years ago, most big data came from a range of sources such as CRMs, billing and browsing activity. Today, data science is more dependent on external data sources, generating information that could be obtained internally. 

Through the challenges faced in the past year, big data has become a pivotal part of recovery and growth across many sectors. According to a survey by Oxylabs of the UK finance industry, the majority of businesses have increased their data budgets in the past year or intend to make changes very soon. 

These patterns are similar across other industries, and while many organisations are managing budget cuts, the overall spending on big data continues to climb to remain ahead of the competition. In terms of competition, it will become increasingly challenging for businesses that are yet to integrate big data into their organisation. There are several key reasons why a company should focus on implementing big data.

Competitor Research: Big data takes competitor research to a higher level. A competitors website can provide only limited information on their values, products and pricing. However, all this information is complex to follow manually. Automated web scraping can be useful in these particular scenarios. Automation enables regular monitoring of many websites simultaneously. For example, in eCommerce, a business can explore how their competitors are changing prices, how long it takes to sell a product and the popularity of particular items. This information can make certain decisions about products and pricing strategies.

Precision Marketing: Data-driven marketing is more effective, as high-quality data allows businesses to discover new opportunities, to customise the message and target more effectively. While many have been using data for years, the pandemic spurred many to adapt their strategies. Global lockdowns resulted in a considerable surge in more data. It became particularly challenging for older data systems that weren’t capable of capturing the changes in customer behaviour. This is when external data became even more important. McKinsey refers to these changes as the big reset in data-driven marketing. Businesses that have adapted to the new normal and adjusted their data approach have experienced growth, while others have fallen behind the competition.

Supply Management: Data supports the management of your supply chain in various ways. It can support you in selecting the right products, developing your catalogue, predicting demand and improving the efficiency of other processes. Applying public data collection tools allows businesses to determine the popularity of particular products, assess reviews and other recommendations. 

Protecting your brand: The online world is full of alternative products that are based on successful branded products. Big data solutions can help identify instances where your brand name may be used illegally. Web scraping can determine fake online goods, scanning marketplaces and eCommerce sites to discover the best products. This process represents an essential part of business and will continue to be a challenge for many companies.

Improve the efficiency of business operations: If used appropriately, big data results in more efficient business processes. Data provides vital information on where to focus your efforts to generate the best results, enabling a business to reduce costs and resources.

A report by the MIT Sloan Management Review discovered that the most analytically focused businesses use a wide range of data sources. Often viewed as an added feature for larger businesses, applying big data has now become the new normal. Today, there is information everywhere that can help your business make more efficient decisions. Companies shouldn’t miss an opportunity to utilise this data within their daily operations.

The pandemic has increased the focus on the importance of data analytics in measuring risk, encouraging businesses to invest more in training and upskilling their employees.

We are in a time where information is critical. Data is generated faster than ever before, and more specifically, data analytics enables businesses to maintain pace with technological advancements in their chosen industry.

During the pandemic, many businesses transformed their focus from the potential risks associated with remote working to shifting their environment and risk framework by using data analytics to generate significant value. Implementing resource monitoring enables a smoother transition towards remote working and enables visualisation of the necessary KPIs that support the overall decision-making process.
In finance, data literacy isn’t an option anymore. It is a critical factor in maintaining pace with competitors, generating new insights and providing a better customer experience, as well as monitoring overall risk.

As market and technology progress, the business talent requirements expand too. Studies suggest that many businesses are now experiencing skill gaps or expect to face skill shortages in the years to come. A report by McKinsey states that 43% of those surveyed expect these talent gaps to be in data analytics. Upskilling individuals, especially in data analytics, is critical in supporting businesses with digital and data transformation plans.

Alongside the movement towards data analytics, the pandemic and shift towards remote working have created an opportunity for employers and employees to focus further on learning and development. Remote working during the pandemic has reduced the commute time and enabled people time to focus on other things such as advancing their skills. People have shown great interest in enhancing their analytical skills via online platforms.

The ICAEW Data Analytics certificate supports finance professionals in playing a vital role in data and business, connecting commercial skills and business knowledge with data analytics experience. There are many relevant courses available to support professionals with widening their skills in data and analytics.

Tailoring an upskilling strategy to fit the individual and the team supports the best learning experience employees can get from each course. By doing this, individuals with varying knowledge support each other and collaborate to develop a stronger data analytics culture.
The progress of analytics has enabled internal audit teams to deliver a more comprehensive picture of their business and operations. Not only does this improve the quality of results, but it also enhances overall communication with stakeholders and senior management.
The increased use of analytics will enable businesses to become more efficient, explore new data, identify new risks and ultimately gain a better understanding of their organisation. For many businesses, data literacy is no longer desirable, it is essential.