Network Guidance
Data & analytics: 10 skills that will set you up for success
We used to talk about the way the traditional Finance role - crunching numbers and managing transactions - was increasingly being outsourced and automated, and nowhere more than in multinationals. If that was a trend a decade ago, what we’re seeing now is a significant acceleration into redundancy of core accounting skills, hastened by artificial intelligence.
Data and analytics are at the heart of this a profound transformation in the way businesses see Finance. Machines are now influencing how financial decisions are made, risks are assessed, and strategies are formulated. Finance professionals are now expected to possess a deep understanding of data analysis, interpretation, and the application of insights to drive business outcomes. The big question is is this: will we see a day when machines can also make decisions?
What’s driving this change, aside from the technology itself?
Speed of decision-making: Facing rapidly-changing competitive environments and a risk matrix that’s in a state of flux, large multinationals - which already operate in incredibly complex environments - are being forced to make decisions ever-faster. It’s the only way they can stay ahead of the competition. What’s the role for Finance? The ability to extract valuable insights from data empowers Finance professionals to make informed decisions that align with broader business objectives.
Risk Management: To dig deeper into the issue of risk, market volatility - whether it be a big-picture issue such as stability of US regional banks, or US-China tensions, or a regional issue such as Myanmar’s ongoing conflict - remains a driver. Analytics enable Finance leaders to identify potential risks, anticipate market trends, and devise risk management strategies that protect the organisation's financial health.
Operational efficiency: Ever heard a CFO say they are focused on driving productivity? We do, almost every day. Data-driven insights enable CFOs to identify inefficiencies in Finance processes and recommend process improvements. Automation combined with data analytics can streamline operations, reduce costs, and enhance overall efficiency.
Strategic Planning: Yes, all that volatility means it’s harder than it ever was. But data-backed insights enable Finance leaders to identify growth opportunities, assess market demand, and align financial strategies with market trends more accurately than human insights alone. And we can give examples of where this is being used.
What does that mean for Finance skillsets?
As companies increasingly rely on data-driven insights, the demand for Finance professionals with data and analytics expertise is soaring. This has led to the emergence of specialised roles within the function, such as data analysts, business intelligence managers, and data scientists. These roles require a combination of financial acumen and data proficiency, creating new avenues for career advancement and specialisation.
Beyond those specialists, it’s important that all Finance professionals master a core set of 10 skills.
1. Data interpretation and analysis
Finance professionals need to be adept at dissecting complex datasets and extracting valuable insights. Proficiency in statistical analysis, including concepts like variance, correlation, and regression analysis, enables them to understand relationships within the data, identify trends, and forecast future outcomes.
2. Financial modeling
Creating accurate financial models is a cornerstone skill for Finance. Proficient Finance professionals can build models that incorporate historical data, market trends, and variables, allowing them to project financial scenarios, assess risks, and make informed decisions.
3. Data visualisation:
Presenting data in a visually engaging and comprehensible manner is essential for effective communication. Mastery of data visualisation tools such as Tableau and PowerBI allows Finance team members to convey complex insights to non-technical stakeholders, aiding strategic discussions and decision-making. As we say in our data storytelling workshops, a picture really is worth a thousand words.
4. Coding (yes, it’s not just for kids)
A foundational understanding of programming languages like Python and R is valuable for data manipulation, analysis, and automation. These languages enable Finance professionals to work efficiently with large datasets, automate repetitive tasks, and perform advanced analytics.
5. Advanced Excel skills:
Ah, Excel, the technology that refuses to die. It remains a staple tool in Finance departments (much to many CFOs frustration), and mastering advanced features like pivot tables, data validation, macros, and Power Query enhances data manipulation, analysis, and reporting capabilities.
6. Business intelligence tools:
Proficiency with BI tools such as Power BI, and QlikView, allows Finance professionals to create interactive dashboards and reports, enabling real-time monitoring of financial performance and facilitating strategic decision-making.
7. Predictive analytics:
Familiarity with predictive analytics techniques, including time series analysis, regression analysis, and machine learning algorithms, empowers finance team members to forecast trends, identify opportunities, and quantify risks.
9. Data cleansing and pre-processing:
Raw data is rarely clean and ready for analysis. Skill in data cleansing and preprocessing techniques, such as handling missing values, outlier detection, and data transformation, ensures the reliability and accuracy of analytical results.
10. Finance data integration:
Many Finance professionals work with data from multiple sources. Knowing how to integrate and consolidate data from diverse systems, databases, and sources enhances the accuracy and completeness of financial analysis.
