If you’ve been listening to the news lately you’ve most likely heard that data in itself is the holy grail for businesses everywhere. However, the business value of data isn’t fully realized until it’s transformed into knowledge that you can apply. Big data and analytics are popular buzzwords for many organizations, but there is often a key piece missing that can make or break an organization’s workforce intelligence strategy: the data has to be actionable.
Actionable data is information that is specific and relevant enough for a company to know how to leverage it to impact the business. Many companies do surveys with their employees. However, it is the rare organization that takes the steps to make sure the data is useful and actionable once the data set is gathered. This process is supported by three key steps: asking the right questions, collecting information effectively, and using reporting tools that allow you to make sense of the data.
Asking the Right Questions
Consider the difficulty in trying to sift through employee perception data to find answers about employee satisfaction, motivation, and engagement after your survey results have already come in. It is much easier to start at the front end of the process and craft the questions to target these areas during the question development phase. It virtually ensures that your root questions will be answered to some extent because they were purposefully built into the flow of the survey from day one.
The questions need to be relevant and specific to your business needs. Megan Younkin, Consultant at Strategic Programs, explains this concept well:
Think of doing online research to find a house to rent or buy. If the online listing simply tells you that there is a kitchen and that it’s a satisfactory kitchen, well, you have a little bit of information but probably not enough to make a decision. Does the kitchen come with appliances? How big is it? What kind of flooring? How much cabinet space? These are the kinds of things you need to know in order to make an informed decision about whether or not that part of the house is right for your needs.
The same can be said for your survey feedback. For example, in regard to the immediate supervisor relationship, if you only know that employees are satisfied or dissatisfied with their supervisor, you may have more info than you started with, but it’s more helpful to know which aspects of the relationship employees are more or less satisfied with. Do supervisors hold people accountable? Do they provide performance feedback? Do they treat employees with respect? These are the types of things you need to know in order to take action on your data.
In addition, consideration should be given to the length of your survey. Asking fifty matrix-style questions in a row is a death knell for your data-gathering efforts. Instead, focus on those key areas you need answers on, mixing up question types, and keeping the length as short as you can while still being clear and understandable. With each question, ask yourself, “How will we use this piece of data once the survey closes?” If you don’t have a good idea, then it might be a candidate for removal.
Finally, be sure you’re using language that’s relevant to your workforce. Make sure the survey uses language that is comfortable and familiar to your workforce. For example, this might include industry or company-specific jargon or technical terms. It could even mean simplifying your questions to meet the needs of a high school-level employee base. This helps to make sure they are at ease when answering, not puzzling out question formats and trying to decipher what sort of information you are looking for.
Collecting the Right Data the Right Way
Since actionable data is the goal, we need to make sure we are collecting enough information to inform business decisions appropriately. An effective data collection process allows for higher response rates, resulting in the data being statistically significant enough to accurately represent the overall population being surveyed. The more representative the data, the easier it is to act upon. Some tangible benefits of having enough data would include:
- Greater confidence in business decisions, basing choices on solid facts.
- The ability to drill down and make decisions at department levels.
- The understanding of smaller sub-populations and specific group needs.
In addition to having enough data, the data also needs to be high enough quality to be meaningful. While online surveys and in-person interviews can generate some success, we’ve found that phone interviews by third-party surveyors generate better responses. By using a third-party, the interviewer has the ability to ask detailed and probing questions, and get to the real reasons behind the responses. They can be highly responsive to the data given, without leading or intimidating the employee. Here’s an example:
One of our phone interviewers asks an exited respondent why they chose to leave the organization and are told “I chose to retire early”. Our interviewer then follows up by asking why they retired early, and are told “I took early retirement because I was having conflicts with my supervisor.”
The impartial nature of a third-party interview allows the respondent to feel candid and confidential, avoiding the fear of retaliation while still adding a personal touch to generate rich responses. When surveying a current population of employees, it’s a best practice to remind them of the general timeline for data analysis and reporting once the survey closes. This helps employees feel like they’re being kept in the loop and have a better idea of what to expect.
Discovering Insights with the Right Reporting Tools
Data can also be made actionable through the use of a flexible reporting platform. Reporting systems capable of displaying data in different ways make it easy for you to apply filters to see the most relevant data and push this information out to specific departments. For example, if your survey asks certain questions related to union vulnerability, you can filter down to just these items and isolate the data, allowing a detailed analysis of this issue to help guide how you might act on the problem. Reporting tools should also allow leaders to explore issues at increasingly granular levels, offering insights into things like team culture and performance. Younkin reiterates the need for a reporting system that allows both big picture and deep dives as needed:
A flexible reporting tool can allow you to find the opportunities for improvement in your employee data, target critical areas, and make action plans that fit within your organization’s current goals and initiatives. You can see the big picture, organization-wide feedback and then dial down to specific areas and sub-populations that may need targeted interventions. For example, if you identify interdepartmental communication as a topic for actionable improvement at the organization level, you can drill down and see which departments have lower scores and may be in need of an action plan.
As far as the people aspect, those that are analyzing the data should have an analytical eye for relationships and correlations within the data to be able to make sense of the information. Often a well-practiced analyst can see relationships in the data that others might miss, which is a great reason to partner with an organization that performs these kinds of analyses often.
Simply put, actionable data is more valuable than reams upon reams of data with no ability to be acted upon. By asking the right questions during the survey design phase, we can ensure a smooth foundation for the rest of the process. Incorporating best practices into the data collection process will help keep response rates high, strengthening data quality. And combining the right tools and people will set organizations up for reporting success on the back end. These steps will lead to stronger data sets and better decisions, a win-win for organizations adopting this methodology.