So, you want to dabble in the world of data? Maybe you heard industry buzzwords like “machine learning,” “predictive analytics” and “data mining,” and your interest was piqued. Or perhaps your boss made a company-wide announcement that data is king, and he wants in.
Data is king, but not if the castle is in shambles and the entire kingdom is running awry. In that case, data becomes this illusion of direction, while, in reality, having no impact on how the kingdom operates.
The same goes when you leverage data in decision-making at your organization. If your teams, tools and process don’t share a sound strategy, your data won’t generate any worthwhile insights.
Establishing a strong analytics foundation requires an organization-wide commitment. Here are four essential steps that can help you establish a strong foundation to your process.
Step One: Define
The first step of establishing your data analytics process is crafting a measurement framework to ensure all business goals and objectives are aligned with the data you are collecting. Define your immediate goals, as well as your long-term goals; are there any data points that may not report on current performance, but will support your benchmarking in the future?
Additionally, it is necessary to have an analytics governance strategy in place. This includes an exploration of roles and responsibilities within your organizations, as well as an organization-wide commitment to implementing and maintaining rules around data collection, analysis and report.
Defining your measurement framework and analytics governance strategy is a critical and mandatory step towards determining the roadmap of your analytics efforts. Take time to set goals for ways you’d like to leverage your analytics capabilities, within the realm of your allocated budget, resources, and timeline.
Step Two: Measure
Before you can track and collect data, you must determine the tools and platforms your organization will use.
Typically, these tools will span the following categories:
- Tag Management Solutions
- Digital Analytics and Reporting
- Advanced Analytics and Data Visualization
Picking the right tools is an important step to measuring data effectively and efficiently. Choose tools that support your internal team and allow you to collect and integrate data from various sources.
As they say, you can’t set sail with your anchor down, so deploy tools and tracking that allow your organization to measure the elements defined in your analytics framework and react to findings from your data.
Step Three: Analyze
Just extracting and reporting data is useless - it needs to be analyzed! That’s where your ‘data storyteller’ will come in. The data storyteller or interpreter dives deep into your data to identify anomalies, trends and changes.
The most successful analysis of data takes more than one perspective into account by involving team members from various disciplines. Leverage both technical analysts to manipulate and transform that data and subject matter experts with relevant business knowledge. Collaboration will bring context to the what, when, why, where and how of your data.
Whether you analyze your data in a report or a dashboard, remember: always be actionable. Before you report on a certain KPI, ask yourself if you would be able to use that metric alone to make a decision. Does it independently tell you how well or poorly you performed? If not, you may need to revisit your measurement framework.
Step Four: Decide
You’ve defined your strategy, measured the data, and analyzed your performance; now it’s time to develop an action plan and decide your next steps.
Gather stakeholders to present findings of your analysis by offering observations and recommendations. This may lead your organization to make some simple optimizations or react with a completely new strategic initiative. Without following the first three steps of the analytics process with diligence, you’ll find yourself in a bind trying to identify key insights and recommendations. Establishing a strong analytics foundation is critical to successfully informing business decisions with data.
Thinking that’s all easier said than done? Whether you need help developing your analytics governance strategy, picking the right tools, or creating actionable reports, Liquid’s data analytics team are here to help. Contact us today!
About Courtney Morris
Courtney Morris is a Data Analyst at Liquid, specializing in architecting custom data analysis strategies and implementation plans – transforming data into actionable insights for Liquid’s clients. She graduated from Moravian College in 2016, and made her mark at Liquid through the internship program before joining the team full-time.