Ahh… the decision-dilemma: data-driven or gut-feeling?
Making decisions on intuition alone is quick but risks moving ahead without knowing the fundamentals or patterns. Using data to inform choices can take a little longer but gives you a clearer view of the whole picture.
The thing is, it doesn’t need to be one or the other - it can be a mixture of both. Many entrepreneurs and business leaders claim a mixture is necessary for short- and long-term success: without gut feelings there’d be no new ideas or products and without data guiding the way new ideas wouldn’t be around for long.
The three fundamental barriers to data-driven decisions
Data are seen as complex and time-consuming. In a fast-paced digital environment agile decision-making can be the key to keeping or gaining an advantage. There isn’t time for long-winded data-driven decision processes when there are new users to be had this very second.
It doesn’t help that accessing data stored in databases requires specific skills all of its own or that reporting and analytics tools tend to be complex. Learning SQL to query databases and build SQL reports generally isn’t high on the list of things to do. Yet even if you use a database query builder that doesn’t require SQL knowledge, there are still three fundamental barriers to incorporating data into your flow:
1. Accumulation: The need to easily integrate new data sources
Life would be simple if all data came from the same place and was recorded in a central location. Sadly, life isn’t that easy. That’s why accumulating data – collecting data from different places and easily accessing it – is one of the major barriers to data-driven decision-making.
As it stands, web, app, in-store, customer, financial and all other sorts of data are stored in their own databases. This isn’t inherently bad - keeping different data separated makes for clean data warehousing.
Yet these databases are effectively siloed away from each other, creating information silos and blocking access to the full view of what’s going on in a business.
The sheer effort of crunching through different data sources and combining them stops many would-be data-driven decision-makers in their tracks. This restricts clarity, reduces likelihood of collaboration, and has detrimental effects on decision-making.
2. Analysis: Needing faster and more sophisticated data analysis
After accumulating data you need to analyze it. Traditionally, this has been a lengthy, complex process involving SQL queries and database query builders. Again, this is a major barrier in incorporating data into an everyday decision flow.
Despite masses of data, things are easier than they were. It’s now very simple to hook up a database to a SQL reporting tool and not even need to build SQL queries. Dropdown menu and drag and drop interfaces make it very easy to filter and analyze data and build reports and visualizations.
All of this can take literally minutes to do, massively speeding up data analysis time. Even building SQL queries is made easier by user-friendly tools that streamline the process of filtering and analyzing data.
3. Action: Difficulty of extracting insights that lead to improved business performance
Analyzing data is one thing but it’s using that analysis to inform business decisions that sets organizations apart.
One of the hardest things is knowing which data are valuable or which data you should be consulting. With huge amounts of data analysis paralysis is common and data-driven decision-making falls by the wayside, regardless of best intentions.
Countless experts believe the ability to quickly analyze data and use those insights to inform future business direction and strategy is going to be a defining factor in successful businesses of the future.
How can you overcome the fundamental barriers to data-driven decision-making?
Define your tools
For each of your data sources (website, in-app, payments, customer info etc.) define a specific location (database) they will be stored in - this might be MySQL, PostgreSQL, MS SQL or other types of database.
Once you know where your data will be stored select a couple of tools to access, analyze, report, and visualize all your data - think Google Analytics and QueryTree. You shouldn’t need vast amounts of tools to do this - you can get most of your data reporting needs from two or three tools.
Ensure you and your team use only these tools for your data needs.
Give data a common purpose
Data for data’s sake is pointless so don’t collect data and do nothing with it.
Data needs a purpose to be useful - align it with your business or growth goals.
Use your assumptions/hunches/gut feelings as an excuse to verify your thoughts against data - if you know precisely which tools you need to use to do this then it becomes less of a barrier.
When you ask a question, ask that same question of your data - you’ll likely find answers to further you along your path to growth.
For example, if you’re wondering why you aren’t getting as many new leads or users you could assess your email funnel. A simple question (which you can ask by filtering your data) might be “how many people signed up for a free trial, received the whole drip-feed sequence, and didn’t sign up?” If these numbers are high your emails or CTAs probably need work.
Communicate and collaborate
Analyze data, build reports, share them with your team, clients, managers.
Empower people to explore data so they can make their own insights.
Organizations that prioritize data communication perform well.
Nearly all data are valuable – if you have clear goals and purposes then finding value in any kind of data shouldn’t be too hard.
The future is filled with data so it’s essential to start incorporating data-driven decision-making into your natural workflow.
You can begin by overcoming accumulation, analysis, and action with simple tools that work for you and your team, aligning all your data to your business goals, and collaborating across teams and organizations.