Data can be one of two things for a business: a major benefit or a major pain. While the goal is to utilize data for actionable insights that inform better business decisions and outcomes, many companies find themselves in data overload, not knowing what to do with all that information at their fingertips. Here’s how to avoid drowning in data and ensure results through data-driven practices.
1. Have a practical data strategy
The first and most important step to a data strategy is determining what data is important for a company to track and collect. Contrary to common beliefs, collecting every single data point around customer interactions is not a solid strategy and will definitely leave you drowning in data. To build an effective strategy, start by taking inventory: who is the usual audience of your current data and who is the target audience. Then determine what your goals are – brand awareness, engagement, sales, etc. Knowing these parameters will guide your team in tracking the most meaningful KPIs.
When it comes to the analysis portion of your strategy, think about the people that will be using the data, the process to gather insights, and the providers (or technology) that you will need. This, coupled with defining your business's objectives, will lead to a more streamlined structure and strategy for analyzing data. Then, ensure everyone is on the same page when it comes to both tools and processes so that you know your team has the access and information necessary to complete their tasks. A clear roadmap should create a more self-sufficient team, preventing avoidable roadblocks along the way.
2. Provide access to data training
Many teams face the issue of a lack of trust in gathered data. In this case, providing training can give them assurance and help them differentiate good data from bad data. Keep in mind that each job function requires different knowledge and understanding, so breaking up training into group sessions or one-on-one education may be beneficial.
Remember, data is not self-explanatory for everyone. Though advanced statistical knowledge is not required to understand data, teams will need to be instructed on how data works in their specific roles and how to effectively use it. Whether it's to create relevant reports or identify trends and patterns, training your people will allow them to make more informed decisions.
3. Offer expert support
Companies recognize the importance of having experts like data analysts, but these roles can quickly become overwhelmed with the numerous requests and handling data quality issues. To maximize output, consider these approaches:
- Offer self-exploratory data tools to empower them in their work.
- Limit requests to prioritize the most critical ones
- Automate as many reports as possible and make them easily accessible
4. Create motivation through inspiration
Asking your team to make time for data analysis in their already busy schedules may seem like it's adding to their workload, but it's worth it. To encourage their commitment, give them compelling reasons why data will make their jobs easier and more rewarding.
This motivation can stem from witnessing real examples where data has made a significant impact within the company. For instance, the marketing team might have found hidden opportunities to enhance their campaigns, or the product team improved customer satisfaction by understanding user behavior through data insights. You don't have to completely overhaul your data approach. Instead, look for small improvements that can bring you closer to your ultimate goal: gaining actionable insights.
Conclusion
You don't have to completely overhaul your data approach. Instead, focus on making small but impactful improvements that can effectively lead you towards your ultimate objective: attaining actionable insights. These incremental changes can make a significant difference in leveraging your data to make informed decisions and drive positive outcomes for your business.
