As a wind project ends and groups gather to analyze the outcome of the endeavor, they soon realize they were not capturing all of the data required to fully understand the reasons why the project was a monumental success or an epic failure. Companies who proactively engage in capturing as much data as possible have a better understanding of what is going right and how to reduce the risk of inefficiencies and disasters. The definition of data is listed as “facts and statistics collected together for reference or analysis.” The broad initiative to collect data is not one to begin without orchestration, and must be strategically formulated prior to the project start date. Think of this process as a “Who, What, When, Why, and How” strategy. These questions are the foundation of capturing data and utilizing the most valuable outputs to develop KPIs.
The initial questions in the progression of collecting data are to determine: what data needs to be captured; and more importantly, why should this data be collected? Most people think of data as numbers, but as the definition states, it is a collection of facts as well. These facts would present themselves in the form of a checklist, receiving document or even a labor schedule. Facts from documents such as these are factors in the success of a project, and yield valuable information that can be reviewed to determine what worked and what did not. Capturing statistical data such as number of components delivered on time, number of delays caused by weather, damage claims, duration it takes for a truck to be unloaded are all data points that can be collected for review during and after every project.
After establishing the “What” and “Why,” it is essential to determine: who should collect the data; and when should the data be collected. Identifying and assigning the individual who has the most real time exposure to the data point is the key. For example, the responsibility of capturing the times trucks arrive at a project checkpoint or pad site should be logged by the receiving team who is escorting the truck to the check point or pad site. If having an eye on the data point is not possible, a communication process must be established to obtain the raw data. Capturing inaccurate data is as useful as not capturing the data in the first place.
The final question in the initiative is: How should the data be stored and formatted? The entire purpose of collecting the data is to analyze it to reduce risk and enhance processes. The method to which the data will be stored and formatted is as important as the previous strategic points. Automated methods such as RFID and barcode scanners generate input into an ERP that can be exported as needed. Large ERPs are not always able to capture the exact information needed and thus alternative methods are created using Excel spreadsheets as well as Access databases or SharePoint Lists. Regardless of the tool used to log the data, the need for key identifiers and conforming columns and headers is extremely important. In order for a database to function as it should, the user must be able to sort by the relative information and get the results they need without having to pull random unrelated data out. If using an Excel sheet or SharePoint list, it is best to create drop downs sections to eliminate data entry errors and entries that are not conforming to the column. Creating validation rules also assist with ensuring the cells will only capture the data in the requested format.
Once you’ve answered all of those questions—What data you want to capture; Why it should be collected; Who should collect the data; When the data should be collected; How the data will be stored and formatted—it’s time to analyze the data. Filing through rows and rows of information is a pleasure of some but not for most. The way the data is presented is as important as the means of capturing it. The intent of capturing the data is to paint a picture of the operations and identify what adjustments need to be made prior to the next project. Summarizing the results via text or chart can easily illustrate the results of the data captured and reiterate the significance of capturing data in your day to day operations.
