Strategic Data Use: Focusing on the Metrics that Matter
In a recent white paper, International Data Corporation (IDC) predicted that the world will generate 163 zettabytes of data per year by 2025. For all you nerds out there, a zettabyte is a trillion gigabytes! Computers, smartphones, sensors, and monitoring systems have made the collection of hard data almost automatic and relatively inexpensive. Even soft data like opinions, suggestions, and interpretations can be collected quite easily through online surveys and social media activity. It’s easier to access data than it ever has been before, but the availability of so much data can make it hard to know what to do with all of it.
Following these simple steps should allow your organization to focus on the most important metrics in a sea of data that keeps getting bigger and bigger.
In large organizations, even the smallest efficiency, cost reduction, or revenue increase can mean millions of dollars. As a result, these organizations often invest a lot of money in data analysis, employing teams of analysts who mine data looking for any discernible pattern. This type of data strategy makes sense for them, but what about smaller organizations with more limited resources? Smaller organizations want to be data-driven too, even if they are not able to make such a large investment in collecting, storing, and analyzing data. For these organizations, it’s much more important to be strategic about data use. Here are a few simple steps for developing a scaled-down, yet effective, strategy for data use that will allow your organization, no matter its size, to focus on the metrics that matter.
Start with the questions, not the data. Too often, we hear people ask, “What data should we be tracking?” or “What things should we be measuring?” The easiest way to answer these questions is to first identify important questions that your organization needs to answer. To do this, you’ll want to involve people from different areas of the organization, especially leadership. You could ask them to brainstorm and come up with some questions that would help the organization operate more effectively. Then you could meet as a group to discuss the questions that everyone has generated and work to arrive at a consolidated list. Identifying exactly what you need to know is the first step in developing a strategy for effective data use. The questions you identify will help you determine exactly what data you need to collect and analyze.
Prioritize your questions. At this point, you will likely have generated a fairly large list of questions. Given limited resources, it will be important to prioritize these questions in some way. If your organization has a strategic plan, consider which questions, when answered, are most likely to help your organization realize its mission or meet key objectives. If you don’t have a strategic plan, simply think about which questions are likely to have the largest return for your organization. Don’t forget to consider the potential costs of answering each question as well. Generally, complicated questions cost more to answer, but they also tend to have the potential for larger returns.
Start small. Once you’ve considered both the cost and potential benefits of each question, you should be able to rank them according to expected return-on-investment. You don’t always have to start at the top of the list though. Sometimes it’s easier to tackle questions that require little investment first, saving the more involved questions for later. This is especially important if your organization is resistant to making an initial investment in data use. In this case, starting small is better than not starting at all.
Create a plan for gathering your data. Once you’re focused on a few important questions, you’ll want to list out all the data elements you’ll need to answer them. There’s a good chance that some of the data you need is already being collected. Be careful though. Existing data that rarely gets used is likely to be collected inconsistently and imprecisely. When using existing data, make sure it is up-to-date and accurate. There’s a good chance you will also have to collect some additional data to answer your questions. The data collection method you choose should be based on the type and depth of information you want to collect and the resources available to collect it. Case studies, observations, and interviews provide complex information from what is usually a smaller sample size due to the time required to conduct them. Focus groups and surveys allow one to collect data from a larger audience with less of a time investment, but the data provided can be less rich.
In addition to deciding how you will collect your data, you’ll also want to consider how often to collect it. If a metric is likely to fluctuate rapidly and is closely aligned to your mission, it makes sense to monitor it more frequently. Sales numbers or clients served are good examples of metrics that should be monitored regularly. Metrics that require more time to change can be monitored with less regularity. Employee engagement is a good example of a metric that probably only needs to be measured once a year as it can be slower to change.
Create an analysis plan. Now that you know what data you will collect and when you will be collecting it, it’s important to come up with a plan for analyzing it. The plan should include the specific questions you are trying to answer, the variables you will examine, and the analyses you plan to run. Make sure you use appropriate analyses to answer your questions but try to keep things as simple as possible. Not all data analysis requires someone with an advanced degree and expensive statistical software. Once you have a plan, make sure you stick to it. This will ensure you’re not spending time collecting unnecessary data or conducting unnecessary analyses.
Deliver results in a way that drives action. After all this planning, it’s time to put your data to use. That means presenting findings in a way that will drive action in your organization. There are many ways to deliver results including reports, dashboards, scorecards, and stories. Consider stakeholders’ skill, interest, and time as you choose a format for your deliverables. Stories take a long time to develop, but they are often the best way to drive action. No matter the format, make sure you provide clear recommendations and action plans based on the data, and don’t forget to evaluate the impact of whatever actions are taken. This is the best way to demonstrate the value of your newly developed data use strategy.
Following these simple steps should allow your organization to focus on the most important metrics in a sea of data that keeps getting bigger and bigger. Although there is no hard and fast rule for the number of metrics an organization should monitor, data collection and analysis should never distract it from its mission. Thinking about and developing a data use strategy should help prevent this from happening.
If you would like additional support developing or implementing an effective data use strategy in your organization, feel free to reach out!