How to Climb Out of the Four Greatest Data Strategy Pitfalls
For one, don't think data is telling you to go one way when, in reality, the world is going in another.
You know that data matters. Not just to you and your team, but to your long-term business success. You rely on data to evaluate programs, monitor your place in the market, prioritize new initiatives and more — so why does it sometimes feel like data is a battle, and you're losing?
Data initiatives can falter or fail to bring in the promised results even in the most sophisticated or well-intentioned companies. We've all heard the stories: Google Glass, Quibi, the Samsung Fold. They thought the data was telling them to go one way when, in reality, the world was going another. If that sounds familiar, then you've fallen for one of the four greatest pitfalls growing companies encounter in the course of their data journey. These missteps can be frustrating, but they are fixable.
Pitfall #1: Thinking about data last
Too often, leaders and data teams become shoehorned into a reactive role within the business. A new strategy develops, or an opportunity arises and the data team is the last to hear about it. As a result, they must think on their feet to pull reports, plans, tactics — anything slightly useful — out of thin air.
The thing is there's always a new opportunity just around the corner. As a result, teams invested in data integrity and compliance act more as a service center rather than playing a pivotal role in defining the company strategy from the outset. It's an easy trap, especially for businesses that are moving fast.
As a leader, it's your responsibility to question your data early and often. And when you do, it's crucial to connect the dots between the data and business outcomes. When you talk to the CRO, point out the impact of healthy CRM data on shortening sales cycles and improving cross-sell and upsell. Ensure the COO understands the implications of inefficient data processes across the company and suggests practical solutions for saving time and money. Let the CMO know you understand the vital function of customer data in marketing programs — and emphasize that collecting healthy customer data requires a sound data infrastructure.
As a data-driven leader, you become a champion for all kinds of issues in every line of business. So don't be afraid to raise that voice and ensure that data is part of every strategic conversation.
Pitfall #2: Overestimating your data readiness
Everyone says they want to be data-driven — but how realistic is that goal? As much as we would all like to be a shining example of putting data first in every single decision, not every business has the time, resources or drive to make that happen. Research by McKinsey Analytics reveals that 61 percent of companies acknowledge the impact of data and analytics on core business practices are still taking an ad-hoc approach to analytics instead of developing a full-fledged data strategy.
What matters is doing the best you can at every step of your data journey. Even if you aren't the pacesetter for how your industry handles data, that doesn't mean you can't make data an essential part of every decision. The truth is that progress is what matters. And there's no one perfect approach to becoming more data driven.
Wherever you are on your data journey, you'll need to focus on getting the most out of your data strategy and making sure the data you're leveraging to inform business decisions is healthy. Invest your time in small, concrete steps to help better use data and align your data experts to the most critical parts of the business. An honest look at your data culture involves ensuring your analysts have the time and resources to support growth in the right areas of the company, even if it means a slightly less responsive relationship with some other parts of the organization and their data.
Pitfall #3: Failing to think from first principles
When it comes to data, it is very easy to lose track of what matters. As a result, companies frequently fall down a rabbit hole of irrelevant metrics, spinning cycles on complex dashboards that chart dramatic changes over time without ever answering a single question about the core business. How often have you found yourself staring at yet another report detailing monthly engagements on social media, or the number of support tickets logged in a week and asked, "Sure, but…what does it mean?"
It's an easy trap to start your data initiative by measuring the easiest things to measure, but those are rarely the things that make a difference to your business. So instead, take a step back, take a breath and take the time to formulate the questions you would most like to answer.
If your primary goal is to make sure sales are getting more high-quality leads, tracking website traffic alone will not tell you much about how people enter the sales funnel or where and why they fall out of the process. Instead, make a list of everything you wish you could know to answer that question thoroughly. You may not be able to capture or process all that data right now, but it will help you frame your reporting and use it to build meaningful context instead of spitting out numbers.
Another common misstep that companies make is investing in a shiny new tool without building a solid foundation. If you've ever found yourself working on a data analytics dashboard for project planning and implementation that should have been the customer intelligence project, you know how self-defeating that can be. Technology will help you move faster and more efficiently, but everything needs to start with a clear strategy. Before bringing in a new tool, make sure that you know the problem you're trying to solve. Take the time to build enthusiasm around the initiative, not just within your team but also with other groups who may use the new tool. Set up a time to train new users, and schedule regular refreshes to keep adoption and enthusiasm high.
Pitfall #4: Using unhealthy data to make critical business decisions
There's a difference between data-saturated and data-driven. Companies have more access to data than ever before, but there's very little way to make sense of it. Only half of the executives highly rate their ability to deliver the basics: timely, accessible, complete and accurate data. Data management companies have been offering to solve these problems for years — but they're focused on the mechanics of data like moving it and storing it.
Companies need a holistic system of preventative measures, effective treatments and a supportive culture to actively manage corporate information's well-being. It should be designed in a way to allow companies to answer basic questions about their data that remain challenging for many to address — where it resides, who has access to it, whether it's accurate and how much it's worth. When you know how to answer these questions, you can then begin to understand and communicate — in a quantifiable way — the reliability, risk and return of this highly critical business asset.
If you look for inefficiencies within your company, chances are you'll find some unhealthy data at the heart of it. However, organizations can improve data that is trustworthy and make healthy data a way of life by taking a holistic approach to your quality of data, similar to how we think about a healthy lifestyle. This shift in perspective from focusing on the mechanics of data to concentrating on its overall health can help leaders be more confident in making data driven business decisions.
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