How Data Skills are Changing the Future of Finance—Expert Panel

WebinarMay 2022

Hear from our panel of experts about the challenges that Finance professionals are facing today, and how embracing data can help overcome them.

Experts from Kaplan, the ICAEW, and DataCamp explore how data analysis skills have become the most sought-after skills in the industry. They discuss how data has changed the face of finance, and what leading organizations have done to embrace data and ensure their workforce are able to cope with rapidly changing demands.

After hearing about the biggest challenges faced by the industry today, they discussed how to overcome them.

Key takeaways:

How has data changed the role of Finance professionals, and why do we need to embrace data analytics now?
What are the biggest challenges faced by finance professionals tasked with utilizing their organization’s data more effectively?
What data skills are expected of the modern finance professional, and what is the risk of simply doing nothing?

Summary

In a rapidly transforming financial environment, data skills are becoming essential. The role of finance professionals is shifting from simply looking at historical data to utilizing data analytics for predictive and strategic insights. The proliferation of data necessitates the adoption of new tools and technologies, such as Python and BI tools, to handle vast volumes of information. Organizations are challenged to evolve by integrating data strategies that align with business goals while supporting a culture that embraces continuous learning and adaptability. The importance of non-technical skills like communication and problem-solving is highlighted to connect the gap between data specialists and finance professionals. Additionally, there is a significant generational divide in data proficiency, with younger professionals generally being more tech-savvy, highlighting the need for specific training approaches. The session also highlights the potential issues of poorly implemented technology projects and emphasizes the need for a clear data strategy to avoid such issues.

Key Takeaways:

The shift from historical data analysis to real-time and predictive analytics is vital for finance professionals.
Data volume and the demand for immediate insights require new tools and technologies.
Non-technical skills such as communication and strategic thinking are essential for effective data use.
Generational differences in data proficiency call for targeted training and development strategies.
Organizations must have a clear data strategy to leverage analytics effectively and avoid technological issues.

Deep Dives

The Evolving Role of Finance Professionals

The role of finance professionals is ...
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undergoing a significant change, driven by the increasing importance of data analytics in decision-making processes. Traditionally, finance roles focused on historical data analysis, recording transactions, and generating reports. However, as Ian Paye from ICAEW highlights, there is now a pressing need for finance professionals to adopt a future-focused approach. This involves leveraging data to predict trends and make informed strategic decisions. As Jim Hinschliff notes, the profession has changed from using paper ledgers to integrating business intelligence tools like Power BI, which enable more active and predictive insights. This evolution is not merely about adopting new tools but also about changing mindsets to embrace the role of data as a strategic asset. As Ian Paye mentioned, "In this digital age, we want information now. We don't want to wait for monthly or quarterly reports."

Data Volumes and Tool Adoption

The surge of data volumes presents both challenges and opportunities for the finance sector. Ian Paye explained how data sets have grown from hundreds of thousands to billions of records, making traditional tools like Excel outdated for such vast amounts of information. The need for instant information and analysis has led to the adoption of more sophisticated tools like Python, Alteryx, and Microsoft’s Power Suite (Power BI, Power Query, Power Automate). These tools offer the necessary capabilities to manage and analyze large datasets effectively. However, as Ian cautions, "You can't just start developing an AI function in your business." It is vital to first establish a clear data strategy that aligns with the organization's goals and capabilities.

Bridging the Skills Gap

There is a noticeable generational gap in data skills within the finance profession. Younger professionals tend to be more comfortable with technology, whereas older generations may lack confidence in their data skills. This discrepancy necessitates varying training approaches. Jim Hinschliff emphasizes the importance of developing both technical and non-technical skills, such as problem-solving and communication. These skills are essential for finance professionals to effectively collaborate with data specialists and leverage data insights. Ian Paye also highlights the need for finance leaders to understand the basics of data analytics to guide their teams effectively and make informed strategic decisions.

Challenges in Technological Implementation

Implementing new technologies can be fraught with challenges, especially when there is a disconnect between the finance team and data specialists. Ian Paye shares a story about an organization that implemented an AI solution without fully understanding its workings. This lack of understanding led to difficulties during audits, as the team could not explain the AI's processes or outcomes. To avoid such issues, organizations must ensure that they have a strong data strategy and a clear understanding of how new technologies will integrate with existing processes. As Ian wisely notes, "It is not about running before you can walk."