2021 highlighted the urgency and need for quality data and information for business leaders to make key decisions as well as pivot in a rapid manner. Data is only as meaningful as the intent and purpose behind analyzing it. This has become even more important in the last year as brands focus on truly understanding their customers’ needs through a human-centred and empathetic lens.
Using data can feel intimidating, but it doesn’t have to be. Removing internal barriers and building high-level strategic direction on why teams are gathering and analyzing data – not just how – is fundamental.
If an organisation doesn’t already have a Business Intelligence Strategy and Data Management Capability in place and is looking to start, instead of heavily investing in scattered areas right away, what’s more important is to review the existing data and try to put things into perspective.
Identifying and collecting key data from essential data points is the first step in data analytics and integration. Start small and start with what you have with an MVP mindset, chances are your core systems can generate some good data already. Leveraging useful data tools such as Looker, Qlikview and Tableau can also help you easily generate some early insights.
A 7-step approach for faster, valuable data insights
1: Create a true value proposition
At its core, it’s simply why your customers would choose you – why they’d buy your product, subscribe to your service, or even use a feature on your website. Take the time to develop more than a superficial understanding of this, otherwise, everything else in the framework will suffer.
2: Identify hypotheses & questions
Nothing ever gets built with perfect, complete knowledge. What business questions do you need to answer?
3: Identify decisions that need to be made
If you’ve ever looked at a report or analysis and thought, “What am I supposed to take from this?”, there’s a good chance this step was omitted. Step 3 is the “Why?” to support Step 2’s “What?”
4: Draw connections to your KPIs & metrics
This step is critical because it ties together the previous three steps and starts to pivot into facts. Creating solid, documented linkages between the previous steps and specific metrics is a strong way to ensure that rogue metrics don’t sneak into your work.
5: Sourcing your data
Organisations need to evaluate it and see if it’s the right data to answer the business question and impact decisions.
6: Structuring your data
When you combine multiple data sources, opportunities for data to be duplicated or mislabeled inevitably arise. Bring all the disparate data together, transformed and aggregated as necessary, ready for developers to work with quickly.
7: Build reports & assets
Build out sample reports and mock-ups and share them with stakeholders to review and iterate from.
Now, more than ever, is the time to go back to basics and make sure your data, research and business intelligence fundamentals are there to support how your organisation chooses to adapt, whether it be existing approaches to extreme change, or finding the right insights to enable a pandemic pivot. The right data that matters for your business needs to be looked at to focus on the business outcomes that are relevant and can be used across the entire organisation.
Every data and analytics program, at its core, should be planned and delivered to enable businesses to make better, more timely and very accurate decisions. Now is the time to enhance the power of your own data. By finessing your own business approach, you’ll change how you and your entire organisation think about the data that drives decision making, problem-solving, and creating opportunities.