Are you a finance professional who is constantly at the beck and call of your CFO with never-ending requests while you’re trying to watch your kid’s soccer game? Or are you the CFO who would rather have information at your fingertips instead of bothering your staff with questions after hours? If your answer is yes to either of these questions, read on!
Imagine having all reporting and analysis information on hand rather than doing a fire drill to answer a question about the latest management report. The push and pull of information is constant, and it is possible to ensure management has the information they need when they need it. There’s a way to make reporting and analysis easier for everyone in the organization by developing what we call a data model. Below are four steps to align information availability with what management needs for decision support:
The first step in creating the right reporting data model is making a strategy map to align the organization around measurable goals. Leadership must discuss and determine the desired strategic direction of the company based on the company’s core competencies. Based on the high-level strategy, critical success factors can be identified, which must be based on quantifiable metrics. The core competencies will be the framework for reporting.
For example, an E&P company wants to find oil. Therefore, the company wants to be competitive in exploration. A critical success factor is identifying and pursuing all attractive exploration opportunities. It’s measured by bidding success ratio, winning bids, losing bids, and $ bonus per acre.
The next step is to identify and define the performance metrics by which management will make decisions and measure the business. Once established, define how each metric is calculated and determine who is accountable for capturing and maintaining data for the metrics. Designating who is accountable for each metric’s data quality creates clear ownership and lets the organization know who to reach out to for questions regarding specific data points. For example, suppose management wants to measure per well volume, which is calculated by dividing total volume by well count. They would assign the metric to someone from the production group who would be accountable for it.
The third and most challenging step is determining which company hierarchies to report on. The hierarchies need to align with how leadership wants to view data (by location, by product, by customer, etc). The difficulty comes in deciding at which level of the hierarchy to view data. Organizations shoot for the moon by saying it’s necessary to capture metrics at the lowest level. But it’s important to consider if this level of detail will change the business decision or make the organization more profitable. And if so, by how much? Find the hierarchies and level of detail that enables the organization to make more informed business decisions and add value.
Lastly, the organization must determine how to obtain information. The team must identify the source of the data and where it is located. If it exists in multiple locations, which system has the correct information and is the ultimate authority? For example, production data can live in multiple systems—field data systems, production modules, and revenue modules—and data can look different in each location, so the system of record must be identified. Identifying the authoritative source helps organizations build a data model that enables them to obtain the right data that drives business decisions.
Getting the right information quickly is the basis of the decision-making process. With a comprehensive data model, organizations will be able to easily access the right reports to measure a company’s success and progress.
