The treasurer is one of the people in finance who is sitting on the largest amount of data, and this is not likely to stop, as his role is growing. How do you make good use of this data and what are the pitfalls you have to face? Like salmons in rivers, we need to swim upstream to find the best way to optimize this incredible but too often untapped asset.
A wall stands in front of treasurers
Among the many reasons for not being able to go upstream and make (good) use of financial data, we can mention: the different data formats, the lack of standardization, the multitude of IT tools and solutions, the number of interfaces and APIs, the difficulty to find the right tool to aggregate the collected data, the lack of knowledge (in general) on the part of the treasurers in data engineering and the lack of time, resources and financial means allocated to such projects. Faced with this wall of obstacles, it is sometimes discouraging for a treasurer to dare to think that he or she can get there.
As we have seen, in the latest EACT survey, European treasurers clearly ranked the digitization of the treasury function as their second priority for the next 12 to 24 months. It is therefore an unanimously shared objective. But how to achieve it is a much more complex issue. We all agree on the existence of a problem and a need, we all would like to implement it and "digitize" even more and automate, without knowing how or with which technology. This is where the problem lies. The other blocking factor that we haven't really mentioned is the IT legacy and the complexity of existing architectures, often the result of years of accumulating and adding solutions on top of each other, to the point of making the whole building a cardboard house. The fragility of IT architectures and the lack of desire to invest time and resources in this colossal project at the end of COVID's term curb the enthusiasm of the most valiant treasurers, alas.
"Sometimes starting from scratch is easier than renovating, as in the construction of a building."
Know your starting point and destination
Know what you want before you start. It seems so obvious that we almost forget it, but it is crucial. You must start from the business needs and not from the technology. Technology is only a means to an end. We can certainly identify the "low hanging fruits" which will quickly prove to be few and far between. We must be sure that the solution will create value, with less work and more internal controls. But what is the right solution, the right supplier and the best technology is the question. Of course, we would all like to go for what creates the least number of problems, the least amount of work with the most plausibility and realism. We would like to have a cheap, individual solution with all the advantages and no disadvantages. Let's stop dreaming! The situation is so complex sometimes and the treasury so important in the complete review of the whole finance, that the problem must be decided by the CFO himself. The courage can be to put everything down and revisit the IT legacy from A to Z. Some MNCs have decided to do this, taking the risk, but with the certainty that they will eventually be able to manage the integrated data in a single system. Uniqueness has its good points... and its bad points. Because it will be necessary to choose a leading solution that will have to satisfy all the financiers, including the treasurer. A Cornelian dilemma, but the only way to quickly claim to make use of its data.
Sometimes starting from scratch and from a blank sheet of paper is easier than renovating, as in the construction of a building. But you can't ask the treasurer to rebuild one room of the house, when the CFO doesn't want to rebuild the whole thing. The risk is to complicate the IT architecture and system legacy even more.
Have the means to achieve your ambitions.
However, don't talk to us about "treasury on demand" or "real-time treasury" if you don't have the technical means to produce faster, in real time, what you are asked for. We are convinced that another problem, not yet mentioned, lies in the partial knowledge of CFOs of the technical capabilities of certain tools. They don't see or consider the finance tools as a whole, but as a collection of independent solutions. Finance IT is like management, often fragmented and siloed. A recent survey by one of the largest US IT vendors suggested that only 10% of CFOs have a command of finance-related IT technology and only 31% have a broad knowledge. This shows that the lack of knowledge, explains the reluctance, the lack of global vision and a certain lack of interest (Oracle 2020 CFO survey). However, it is not having suffered during the health crisis, nor seeing the shortcomings of their organizations that would prevent the CFOs from moving forward. The boldest have embarked on multi-year transformations made possible by technology. Think of SANOFI or ROCHE with an SAP4hana redesign. They have embarked on a multi-year business transformation journey, enabled by technology and one single global solution, to integrate all core end-to-end processes needed to run an enterprise into a global template using the latest large ERP technologies (why ERP? Because it remains the foundation of all finance IT architecture). They opted for rethinking and redesigning a standardized digital backbone of any enterprise, with the ambition to capture single data at source, and treasury is in the middle of it. Life of treasurers is never dull. And in such a long transformation journey, the most complex issue is to find the right consulting partner to support the implementation and optimize the investment. SANOFI did the right choice with INTENSUM, as it succeeded in implementing a completely new finance system architecture.
Data mining, the finance Eldorado?
What specialists call “big data” are at the end of the day an unstructured inundation of ones and zeros flooding into finance departments. Today, it seems that, conversely to what is often thought, do not require to understand how data mining thing works to be able to exploit it to the full. Providing you have the right tools and a fully integrated solution, what is often missing, it seems to be “easier” than thought, according to specialists. The blocking point is more the absence a one single data lake and integrated solution to crunch figures and zeros and ones, rather than technical skills in data engineering. The framework is more complex to set up than the use of data, paradoxically. Some treasury organizations have started hiring employees in treasury having Python knowledge. Treasury departments are data producers and not consumers. They maybe should be both.
Not drowning in a lake of data
When you think about it, treasury data, in general, is not unstructured terabytes. They are relatively centralized, organized, and available. They comprise cash balances, bank statements and financial transactions, internal and external. The focus must be placed on how to display existing data in a sufficiently meaningful way to quickly inform complex decisions. Treasurers should not have to manage huge data lakes. They should be able to get easy access to pre-treated consolidated and organized data, to accelerate the decision-making processes and make better recommendations to C-level.
Treasurers simply want to implement something fast and impactful using data analytics rather than speculating on future possibilities of big data. The difficulty is to set up the frame for inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting recommendations based on assumptions, and supporting the whole decision process. What would be needed cannot be afforded and they don’t have the capacity to implement it for treasury alone. It must be a global project, structured and organized. The challenge resides in the mindset rather than in technology.
Therefore, the starting point is, once treasurers have determined what they want, to convince the CFO that this transformation is part of a more global one aiming at revamping the whole IT architecture of the finance department. What is seen as a cliff, suddenly, will become easier to climb. We are not convinced that spectacular achievements can be reached without a global approach and trying to mine data only for treasury can appear to be an uncrossable mountain. And even if even the highest mountains have a path that leads to their summit, it may be a risky and very long route.
François Masquelier, Chair of ATEL – Luxembourg August 2021