How the data-driven CFO can drive business transformation

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The role of the CFO has changed from a financial controlling center to a more strategic one, driving innovation and transforming the business to adjust to fast-changing market needs. Around the world, data-driven CFOs are bridging the gap between strategic decisions like pricing and costs structures, and the operational side of the business – how their team (and others) can be better, faster, more efficient, and more accurate. We spoke to several financial leaders about how they have helped guide transformation at their organizations.

What are the steps a data-driven CFO can take to support data-driven transformation at their organization?

Every business, no matter how big or small, is already working with tons of data generated by the software systems they are using (CRM, ERP, purchase order and procurement systems, etc.). The question each financial leader should be asking is: “Does our organization maximize the value of the data to empower us to make data-driven, strategic decisions?” To support Financial Planning and Analysis (FP&A), the CFO works with all departments to create budgets and forecasts, which gives them a comprehensive understanding of each department’s performance and data analytics needs. Thus, the first step towards transforming the organization is identifying where the business needs better performance analytics.

1. Audit and assess internal systems and processes

Critical analysis of internal processes and systems can reveal crucial shortcomings that stall strategic decision-making, and limit the flexibility of an organization. Most of the problems organizations face are rooted in messy data. Throughout the growth of an organization, each department adopts favorable and self-serving systems without a consistent, comprehensive data architecture that would allow for seamless transfer of data from one system to another. Lack of continuity or automated processes creates opportunities for data loss, repetition, uncertainty, and mistakes.

We spoke to Mark Root, a finance leader with more than 20 years of experience driving operational efficiencies through data-driven decision making. He points at “Getting your house in order“ as the first priority in a transition towards a data-driven organization. If the data that you have is wrong, the adoption of a new system is not going to solve your problem.

“Garbage in, garbage out. We can’t put garbage data in a new system, because it will be garbage that comes out.“

Data-driven CFOs need to focus organizational efforts on validating the data and cleaning it. Data can be cleaned, conformed, and validated by comparing data from different systems – e.g. contracts, provisioning, and customer success – to identify missing, inconsistent, or repetitive data.

After the existing data has been cleaned, Mark suggests the next step is a validation of the whole process. This assessment allows the CFO to identify gaps in the system architecture and processes that cause the problems. Mark offers data-driven financial projections as an example: the assessment would include all systems and processes around the data used in the organization’s financial projections: everything from sales orders to operational costs. The assessment includes running a user acceptance test, during which each data point (e.g. date of the contract, size of purchase, etc.), will be validated from the entry point to the endpoint of the system, for example, form a sales pipeline to the labels printing system of the shipping and delivery system.

“When data is not good you have to ask why it isn’t, and this shows the core of the problem – Am I focusing on the right things? Am I tracking the right data, the right processes? Is my company organized correctly? Do I need to put the IT department under the CFO?“

We also spoke with Nikolay Boev, GA Costing & Profitability Controller at Coca-Cola Hellenic Bottling Company (one of the world’s largest bottlers for The Coca-Cola Company), about how they run data validation on his team. Recently the company centralized the projections and budgeting for the COGS for all countries in the Coca-Cola Hellenic consortium. The consolidated pool of data helped to improve the group analytics, empowered easier cross-countries analysis, and knowledge sharing. Nikolay explains his team must consistently monitor to ensure the quality of their results:

You must always check the numbers as mistakes could happen, especially when our calculations depend on a huge amount of input data entries – if someone makes a mistake in the price of the raw materials you will have an incorrect final cost of the product. However, we have data for each market and know how the prices of raw materials are expected to grow, thus we compare the final cost against the projections and the previous month to identify any deviations.”

2. Link data transformation to company strategic goals to engage leadership

Transforming an organization towards efficient data analytics is a huge effort that requires the buy-in of many stakeholders. A data-driven CFO can take the lead, but will always need the support and the input of the other departments. To ensure alignment and engagement from all leaders, the CFO must build a shared understanding of how data analytics links to the strategic goals of the company. Organizational leaders are looking to solve complex problems such as “Why does it take so long for us to bring products to market?“ and “What should be the price point of the new product?”. Showing fellow leaders how quality data will empower them to answer these questions can engage cross-functional teams that are motivated to transform the business.

A small showcase is the most effective way to gain support and raise the priority of data transformation on everyone’s agenda. A CFO from an established EU SaaS provider (who asked us to stay anonymous) has told us that, together with their sales team, they ran a number of short-term experiments using simple product landing pages to determine the optimal price point for each target group, before officially launching a new product on the market. They used the experiment as a Proof of Concept (POC) to gain support for introducing new data analytics practices throughout the company.

3. Understand the organization-wide needs and challenges

The next step of the business transformation process is understanding the needs of each department. As Peter Loos, a veteran consultant in business process optimization and financial analysis calls it – “Gather all the orders before you start to cook.”

Before starting to build a plan, one should talk to everyone who would be affected by the change, in order to understand all the requirements. What does the business team need to be efficient and achieve their goals? What are the IT requirements? Are there any technical limitations to the solutions the company is already using? What are the strategic objectives of the CTO/CIO, and how do they fit in the picture? “

Open communication with the IT department is crucial at this step of the process. Introducing a new system can lead to a number of long-term implications, and therefore requires careful planning for how the new system will fit the larger IT architecture of the company. The IT department could build a custom integration, but this can produce ongoing costs to support and update the system. The CFO must partner with organizational leaders to facilitate compromises – rarely can one software solution satisfy everyone’s requirements. To achieve this compromise and secure long-term buy-in from internal teams, the CFO and CIO must work together to prioritize requirements and get everyone on the same page.

One of the first questions the financial leader faces is whether to buy a ready-made solution or develop it internally. Both decisions have pros and cons. Mark Root views these as solving two types of problems:

Generally, you are going to buy a solution for the obvious things like tracking hours, tracking projects, everything that involves tracking or accounting – that is going to be your software solution. But usually what CFOs are trying to solve are things that are more nuanced than what a system can provide for them … What could make a greater difference is when someone has solved a similar challenge before. This someone could be the CTO or the CFO, but also could be a data analyst specialist who has worked in that environment before and gets hired on a consultation basis.”

Data-driven CFOs can leverage the insight of someone who has worked on similar projects to learn from what others are doing, how organizations are solving a similar problem, and what vendors are trusted in that space. A consultant can also provide a risk assessment based on their previous experience, which would empower the CFO to anticipate potential problems, ask tough questions early, and create a backup plan. Large-scale business transformations such as a migration to a new ERP system rarely go without delays, however being aware of challenges and controlling the process is what leads to successful transformations.

4. Choosing the right vendor

When selecting a vendor, an organization must plan for the long run. There are a number of criteria the financial leader should consider, such as whether the vendor offers reliable, on-time support. Mark Root shared his criteria when deciding on a vendor:

When you are picking a vendor, you want to make sure that the vendor will be around in 5 years, so you want to pick a vendor that has a good reputation for support. In the accounting world, you want vendors who don’t risk being a “going concern”, which means the risk of going bankrupt. So, financial health is important, but also there is the risk the vendor is acquired by someone else. It begs the question if your solution is OK and not subject to potential sunsetting (removing the software solution from the vendor’s offerings and eventually not supporting it).

There are also some important qualitative considerations when hiring a vendor. Consider:

  • Are they a good match for the organization?
  • How do they plan and organize?
  • Do they communicate difficult topics in a way that nurtures clarity, understanding, and alignment?
  • Do they have a bias for action?
  • Can they truly help the leadership team to embrace and act on business transformation?

In our next post, we will look in detail at the next step the data-driven CFO should face on the business transformation journey – how to build a strategy and a roadmap, as well as how to assess risk and prepare for them. Stay tuned!

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