7 Steps to get Meaningful Insights from Data

November 2020

Australia is home of some of the most precious metals in the earth. Highly specialised processes and equipment are often required to extract, refine and use these precious resources. As technology evolves and becomes more sophisticated our ability to tap into these resources is improving all the time, allowing previously untapped deposits to become accessible and viable for production. 

In the world of digital technology there is a focus on extracting and using another valuable resource – ‘data’. In the digital world, ‘data’ is the new gold, ‘meaningful insights’ from data is the new platinum and ‘actionable insights’ are the most valuable of resources. Mirroring the mining world, as businesses become more sophisticated at tapping into data, they are able to go deeper and extract more valuable and actionable insights.

All well and good you say, but what does this talk of resources have to do with the CFO? Well, when it comes down to it, money is the most critical resource in any business – and who controls the money? The CFO. 

The new role of the CFO

A CFO’s traditional role has been to focus on strategy and the end-state aspects of financials. But in today’s data-rich environment, CFOs are expected to understand and use it to predict, influence and shape decisions that drive financial results.

When a business can extract meaningful insights from data, it has the knowledge to become more competitive, tap into new markets, better develop products and services, provide a better customer experience and generally increase profits.

But just like mined ore, data alone is of no particular value, it must be processed and shaped into something more ‘actionable’ before it can add value to a business. This transformation is often wrongly termed as big data, Internet of Things, predictive analytics, machine learning and artificial intelligence. A more correct reference is ‘integrated data’. 

Every business has a plethora of specialist systems that collect data from various operations and many external sources.  The data from these sources needs to be integrated, validated and current in order to get a complete and accurate picture of the financial health of a business. Companies are turning to their C-level people, specifically the CFO, to lead this operation.

So how can modern CFOs turn data into actionable insights? Here are our 7 steps to get the right data alchemy.

Step 1: Identify key success drivers

Based on our experience, there are typically 15 to 20 non-financial metrics which are drivers of enterprise performance. CFOs need to find what these performance drivers are and then ensure that the right data is continually collected, shared and used. If you are unsure or just starting your data analytics journey, use this as a starting point and progress from there.

By way of example, one of our mining contractor clients that supplies mobile crushing and haulage services to remote mine sites determined two of the most important drivers of success are cost per tonne and cost per kilometre.  When the client decided to collect and post the data daily on these two metrics to the enterprise dashboard, the enterprise’s focus completely changed.

Step 2: Look for relevant data everywhere  

Data is everywhere. CFOs must step away from their financial data lens and start to survey and analyse the different data that exists outside the chart of accounts. 

CFOs must also identify which data sources are essential for the success of their organisation. For instance, the requirements for a project-based business might require in-depth insights into every project, past and present. On the other hand, a mining company would be more interested in data that helps analyse daily production results and costs.

Most importantly, CFOs must have the ability to cross-compare multiple sources of micro and macro-level data to identify and understand correlation and causation.

Step 3: Clean your data

Unfortunately, unless it is collected by systems without any human intervention, enterprises have to live with “dirty data.”

We’ve all heard the saying “garbage in, garbage out, so it’s important we know the information is right ”  So, whether data has not been consistently recorded, is missing or hasn’t been maintained, it will likely need some refining before it can be trusted for use.

One small but critical change is to make the names of fields understandable and recognisable. Data stored in ERPs and other systems has naming conventions that will mean nothing to business users, or any users for that matter.

A disciplined approach must be used for ensuring data is scrubbed clean and is consistent across different systems. Otherwise, information and insights will be derived from misleading and incorrect information.

Step 4: Integrate data

Very few companies have all their data available in one system. We find Internal data often exists in multiple business systems and external data often arrives piecemeal. This “disconnected” data means we might have to deal with “islands of data”.

It is becoming more viable and more common for companies to create their own centralised data warehouse/data marts/data lakes where data from various systems is extracted, transformed, loaded and then linked and analysed.

CFOs have the responsibility to identify islands of data and initiate the centralisation of data for use.

Step 5: Upgrade your data visualisation

Data by itself is essentially unreadable. It has to be refined, packaged and viewable from every angle for data analysis to shine with insights.

Many companies use Excel for visualisation of data at the cost of many administrative labour hours. 

Don’t get me wrong, Excel is an excellent tool when used for what it is designed for – a personal productivity tool. Sure it can do a lot of ‘good stuff’, but this usually has to be driven by the business’s Excel guru – which that’s fine if you can chain them to the desk and they stay with your organisation indefinitely, but not really practical if you’ve got multiple people needing to make sense of information at the same time. Excel is not a scalable or sustainable solution for data delivery.

It is the CFO’s role to invest in data visualisation or business intelligence tools that are able to provide an intuitive display of historical information, and which also allow for sophisticated data analysis that will help drive strategy and action for the future.

Step 6: Drive accountability for data usage

When a business makes a significant investment in its data (as per the previous five steps), it is the responsibility of the decision-makers to use this knowledge. I hear so many stories of key executives who are reluctant to ‘take Fred’s spreadsheet away from him’ –  a classic case of the tail wagging the dog. This does not make sense.

Like any other investment, CFOs need to monitor the usage of this “data-to-insights” investment by the key decision-making people in the business. 

I typically recommend that companies start using their enterprise dashboards (data) as a wall of fame for leaders and provide full transparency by kicking off monthly, quarterly and annual performance meetings with the dashboards displayed front and centre for everyone to see. Then the business decision-makers can use the dashboards to elaborate on insights and action that helped move the needle.

The only way to convert your data into results is to make sure leaders and decision-makers are making the most from it.

Step 7: Ensure security and governance

As a valuable resource, data must be protected and governed. There are immense benefits to becoming a data-driven enterprise, but there are also risks:

Data validity and ethics – ensure only valid data is used and reasonable insights are inferred.  CFOs need to outline strict and monitored data collection and storage and interpretation methods, and ensure that all involved are held accountable to the highest standards of ethical behaviour.

Data security – prioritise data protection and privacy. Like any other precious resource, data is vulnerable to theft. When an enterprise starts to collect and mine data, there’s a risk that it may be breached or accessed by external entities that exploit it for their benefit. A CEO should take the necessary action to be able to ensure data security.

Like any other precious resource, data is vulnerable to theft. When an enterprise starts to collect and mine data, there’s a risk that the data can be breached or accessed by external entities that exploit it for their benefit.

Final thoughts

Data-driven, high-performance companies require CFOs to be on top of understanding the business model and performance/value drivers of the organisation (which can’t be found in the chart of accounts or financial statements). It requires investment in not just data collection systems, but analytics and visualisation platforms.

CFOs are stepping up to lead the data-to-insight revolution and work with other business leaders to build a solid foundation of data mining, refining and reporting that can transform already valuable information into actionable insight to drive better decision making.