As we reflect on how COVID-19 has impacted businesses, there are clear contrasts: Tourism, airlines, and travel-related businesses have been hit hard by the pandemic. On the flip side, e-commerce, food, and fitness have all benefited from the restrictions. Some businesses were lucky – companies like Zoom, for example, were in the right place at the right time and got to ride the wave.
However, the most successful companies used data analysis strategy to design better products, make faster decisions, and innovate faster than their competitors. Let’s look more closely at three strategies:
1. Find practical applications for your data
The most successful companies aren’t theoretical about their data. While they may have comprehensive research programs, their data is on the frontline. They use it to affect tangible business outcomes.
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For example, Amazon uses its data to design warehouses that maximize shipping efficiency. Netflix uses data to recommend movies and shows that keep you watching. Even small businesses like bakeries use data to slim down their menu and focus on best-selling items.
In your business, think about your toughest challenges and how data could play a role. Here are a few ideas:
- Can you improve customer acquisition by reducing low-performing campaigns?
- Could data help increase customer retention and reduce churn?
- Is data the missing link between your current state and automation?
2. Enable everyone to use data
Successful companies empower everyone to use data in the most convenient format. Data should be everywhere, including reports, dashboards, offline files, Slack messages, emails, and more.
Don’t assume that your employees will go out of their way to look at a report – make it easy for them to view the latest numbers where they already spend time.
People should be accessing data naturally as they go about their work. Don’t assume that your employees will go out of their way to look at a report – make it easy for them to view the latest numbers where they already spend time.
Real people also need to support data. Data analysts, data scientists, and other specialists answer questions and solve problems. Self-service tools may be economical in some cases, but there’s always a need for people. Don’t skimp on these hires.
Remember that for most employees, data is just one part of their job. Make it easy for them to interact with data. Simplify the statistics and coach them on how to convert data into insights.
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3. Think about the future, live in the present
There are many data maturity models out there, but consider only three stages: the past (what happened?), the present (what is happening now?), and the future (what will happen?).
Focus on the present, the past, and the future, in that order. Once you have a good grasp of the present and past, shift your resources into the future. That is where you will encounter AI, machine learning, and automation. You can make some of the biggest gains here, but don’t lose track of what’s happening in the present as you consider the future.
Finally, don’t lose sight of the ultimate goal: Better decision-making. The purpose of data is to teach you something new that leads to better decisions. Amazing data and technology are meaningless if they don’t help you uncover actionable insights that can be converted into decisions.
The pandemic has become a modern-day kingmaker, bestowing record profits and growth in some industries. The companies that have come out ahead in these challenging times are innovating faster than their peers, investing in their people, and making the most out of their data. Combine these strategies with a little bit of luck, and you’ll end up in a winning position.
[ Get exercises and approaches that make disparate teams stronger. Read the digital transformation ebook: Transformation Takes Practice. ]