Skills shortages mean that it will become challenging to fill future emerging opportunities in the data industry.

Business data continues to rise in scale and spread across more platforms, but data literacy skills struggle to maintain pace. Most companies have the equivalent of an average of six platforms of data. While leaders are reasonably assured that their teams can analyse data, many employees are not as confident. New research concerning data literacy and management highlighted this pattern in several businesses worldwide.

The 2022 State of the Data and What’s Next report from Red Hat and Starburst explore how businesses gather and manage their data. Data Literacy: The Upskilling Revolution explored what skills people require to deliver data-focused strategies compared to the viewpoint of senior members.

The data literacy report from Qlik presented several predictions concerning how data-driven work will transform leadership teams over the next few years. Nearly all of the leaders surveyed stated that they intend to create and hire for these new data-focused roles within their organisation over the coming decade.

People are demanding data literacy training, but as in many work situations, there is a disconnect between senior leaders and their employees. C-level executives believe that over half of employees are data literate, while only 11% of employees agree with this statement. Furthermore, over 50% of senior leaders are confident in their data literacy, but 45% rely on their instincts rather than data to make critical decisions.

Employees are actively looking to improve their data skills, but the report suggests that only 27% have had formal training with practical experience. Individuals in customer service, finance, marketing and sales stated the need for data literacy exceeds the amount of training available today. People are also concerned that businesses fail to see the responsibility of supporting their teams with developing these skills. According to the survey, senior leaders tend to allocate training opportunities for people working specifically in data-focused roles but fail to recognise people working in other general fields.

This way of thinking can cause certain business areas to fall far behind, like HR and Procurement. This method can also create a decline in enterprise value, with the report suggesting that companies with higher data literacy skills can achieve a considerably higher value for their organisation. The report describes the efforts at PwC UK, which trained 17,000 of its 24,000 employees in data literacy and advocated a shift in the overall mindset of data.

The latest data report from Red Hat and Starburst indicates the scale of the ongoing learning challenge with data. Businesses have an average of 4 to 6 data platforms and up to 12 individual data systems. The complexity of systems increases as an organisation spreads its data over various platforms, and the risk of security heightens too. Respondents to the survey highlighted the automation of IT and data operations as the top priority to enable data systems to work together. Aside from the increase in data spreading across more platforms, the volume of information has increased rapidly.

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.