You have more data than you know what to do with.
Having an abundance of data seems like a good thing, right?
But without the proper infrastructure for storing and analyzing it, you lack that essential “single source of truth” that underpins effective decision making.
Creating the most informed strategy, asking the right questions, and backing up your ideas depends on having the right tools and teams in place to ensure data accuracy.
But that’s not all.
Unless you have a data-driven culture, it won’t matter what infrastructure or tools you have.
Getting your organization to use data correctly requires a shift in attitudes and workflows.
It isn’t easy, but without a data-driven culture, you’ll end up saddled by unnecessary costs and missed potential.
The costs of misusing your data are high
Making decisions based on instincts — or worse, unreliable data — makes it impossible to achieve optimal business results
It’s like trying to navigate unfamiliar roads in the complete darkness. There’s a chance you’ll reach your destination, but it’s highly unlikely you’ll find the easiest, fastest route.
There are two major problems with misusing your data (or not using it at all).
Problem #1: You never even know the problem exists
Unless data analysis is a routine activity, it is unlikely that you’ll be able to identify costly problems or high-potential opportunities.
For example, only after analyzing our customer engagement
data was I able to identify an opportunity to reduce customer churn
For all SaaS companies, churn is inevitable. But by analyzing our data, I could see an important correlation: The more a customer engages with WalkMe (i.e. creating content via the editor), the less likely they are to churn.
In other words, the customers who make the most of the solution’s capabilities also realize the greatest value and are more likely to renew their contracts.
Based on this finding, our customer success
managers changed their strategy. They began focusing more time on encouraging customers to increase engagement and better utilize the editor. This is a win-win — better value for our customers and lower churn.
Dive Deeper: Analytics Rock Stars — How to Boost Your CX With Big Data
Problem #2: Your “truth” isn’t reliable
When you lack standards and protocol for analyzing data, you’ll be left with unreliable and even inaccurate insights.
A common example is cherry-picking, which means presenting data that backs up your claim or agenda while disregarding data that doesn’t.
For example, say a content marketer needs to present the performance
of his latest blog post to his team.
Instead of explaining the full range of data metrics he analyzed, the writer cherry-picks the data that makes his post appear most successful.
He notes that there were 3,000 visitors in the last week, but doesn’t mention that the bounce rate was 95% and the conversion rate is virtually nonexistent.
By cherry-picking the data that seems to signify positive performance, the content marketer gives a false impression that his blog post performed better than it truly did. Not only does his presentation lack credibility, but he’s also ignoring opportunities to optimize the post.
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Build a data-driven culture and achieve greater success
The scenarios above represent two specific examples, but there are countless ways data misuse can negatively affect your business.
The way to avoid these issues is to develop a data-driven culture.
When everyone in the organization adheres to a higher standard of data analysis, you can be confident that key decisions are backed by information that is objectively true — not half true or based on intuition.
Here are five steps for developing a data-driven culture in your organization.
1. Start at the top
must take the first step to build a data-driven culture.
First and foremost, all strategic decisions should be backed with data — this is the only way to know you’re heading in the right direction.
Secondly, if senior executives make data analysis a key part of their decision making, they will set an example that will trickle down throughout each subsequent tier of management and among employees, leading to lasting organizational transformation
2. Initiate a change in mindset
Like any cultural change
, a key component of developing a data-driven culture is changing the way people think about data.
It’s critical that employees don’t view data analysis as simply another tool or a task that they need to perform. Instead, it should be viewed as a key focal point of every decision and strategy.
Instead of only looking for data to answer your questions, you should encourage employees to routinely analyze data and then develop questions and observations from it.
3. Create a data warehouse to serve as a single source of truth
Creating one central data repository is absolutely essential. Your data warehouse will become the key infrastructure to help ensure consistency in the tracking and consolidation of data.
By housing all of your data in one place, you’ll be able to eliminate the frustration
of identifying incongruent data and needing to rely on guesses or assumptions to gauge reliability.
4. Build a solid team of analysts
Whether you do it in-house or outsource to a third-party, you need experienced, technical people who are equipped to support a data-driven culture.
Your team of analysts will be responsible for building and maintaining the data warehouse. Their focus will be on eliminating data analysis systems that rely on Excel spreadsheets and manual calculations across the organization.
On top of the technical work involved, your analysts must be champions
that reinforce the data-driven culture. That means lending support to other departments for structuring and understanding data on top of performing their own business insights.
5. Make data analysis a standard part of decision making
Simply put, I would never make a strategic decision that isn’t based on data.
Using data to inform decisions not only lends you credibility, but it’s also objectively the only way be sure your decision makes sense.
Steer your organization to success
By now, you’re probably generating more data than you know what to do with.
You have customer data, employee productivity
data, cost data, revenue data… the list is virtually endless.
Without an infrastructure for storing and analyzing that data, most of your information will be lost in the overflow. And without a data-driven culture to support it, you could be left with critical decisions that lack credibility — and impose a heavy cost.
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