The Dark Side of Democratized Data: Why More Isn't Always Better

I’ve been thinking a lot about the rise of ‘democratized data’ lately. Getting access to the right customer data to make decisions is one of the most important things a business can do. But there’s a point where more data stops being helpful. And with the surge of new data tools in the market, I think many brands are reaching that point.

I’m seeing more teams struggle to manage their ever-growing piles of customer data. There’s endless unsolicited data to mine, speckled across social media, customer chats, and online reviews. And AI-powered Q&A bots now enable unlimited layers of data questioning and analysis. Most teams today have more data than they know what to do with.

The Insight tools market has moved towards full democratization: providing all the data, to everyone on the team, all the time. But I don’t think this is necessarily a good thing. In fact I think for most teams, this creates a major distraction.?

Without the training, or proper frameworks to select and interpret the right data, putting infinite data into the hands of everyone is a recipe for frustration. Cue information overload, decision paralysis, and general confusion about what it all means.

Increased access to data is great – but only when paired with proper data literacy. For insights professionals, the question of how to best manage your own deluge of data will inevitably come up if it hasn’t already. Here are some things to consider if you’re feeling the data overload, and seeking new ways to communicate insights back to your organization.

Arriving at democratized data – the not so silver bullet

Before I offer up some tips, I first want to acknowledge how we got here.

Somewhere along the line, Insights tech decided on a core idea: that the more people have access to data, the better decision-making, efficiency, and employee alignment there will be across teams. The rise of business intelligence tools sparked this trend, coupled with organizations leaning into big data as a competitive advantage.?

As a result, the insights tools market has seen robust growth in recent years. The text analytics category alone was valued at $9 billion in 2023, and is expected to grow by more than five times that (to $55 billion) by 2030. Much of this is being driven by a ballooning amount of unstructured data, which will account for 80% of the data collected globally by 2025.?

So, we’re all accumulating a lot of data. And we have a lot of tools to help us manage it all. We have dashboards to see everything. We have access to everything. We connect all our data sources into one big data brain.

But none of this means teams have insights.?

To go from data to wisdom, you need structure. You need to know how to take action on the data. You need training on how to layer business context into data in a way that unlocks insight and doesn’t reinforce bias.?

And that’s the problem with democratized data: putting data in front of people who don’t have the literacy to work with it is unproductive.

It may be tempting to delegate this work out to a Q&A bot, or run AI summary reports on trends. But that’s not the answer either. You want to put data interpretation squarely in the hands of a trained VoC team, who knows the questions to ask within your unique business context – something AI cannot do.?

How VoC teams can win with democratized data

Getting the most out of your data is tough, but it can be done. Establishing clear ways of working for the VoC team, and how it supports the rest of the organization is important. Here are some helpful tips to approach sharing insights across your tea, to make the most of your mountain of data:?

Go beyond company level KPIs: for VoC teams that are inundated by data requests, or don’t have the tooling in place to efficiently mine through nuanced insights, there’s a risk in only reporting on the bare minimum. For example, delivering on NPS or CSAT scores, and leaving it at that. Don’t fall into this trap. While helpful top-line metrics, these scores alone do nothing to move the needle on further understanding customer sentiment, trends, or equipping teams to operationalize insights. Get set up with tooling that allows you to quickly dig into insights a layer deeper.?

• Match insights to business units: the insights you provide to the head Head of Customer Support, should be different from the ones you provide to the C-Suite or board. The aim with big data, and getting a centralized ‘feedback brain’ in place is to be able to surface specific things for specific areas of the business. Proactively serving up appropriate insights to the appropriate teams helps not only helps build trust, it also reduces the likelihood that you’ll fall prey to the biggest trap of democratized data – untrained leaders attempting to self-service their data needs. This is when you start to see major assumptions made from small sample sizes, and business decisions made in silos.

• Pick a reporting cadence and stick to it: aim to set up a system to send reports on a weekly, monthly, and quarterly basis to people across the organization. There may be value in setting up an automated weekly report that’s more operational in focus, responding to product changes or marketing campaigns for example. Monthly or quarterly reports to the executive team should be highly leveraged insights, designed to assist strategic decision-making.

• Elevate your tech stack: of course, all of this rests on having a great tech stack to make analysis and reporting efficient and accurate. Look for tools with the capability to do automated reporting, and also broad analysis on high volumes of data.

The bottom line? Be deliberate in the design, timing, and level of granularity of your reporting.?

Don’t be tricked into thinking that giving wider access to data will create better outcomes. Educate your team on the difference between data and insights, and let them know you’re available to be that trusted source of intel that they need.?

Just like getting to the core of a customer insight, setting this up well can take time. Set your standards upfront whenever possible, and your team will be the better for it.