Data-informed tech culture

Data-Informed Tech Culture

The most straightforward way to figure out if a company is data-informed is by looking at how individual contributors use data to plan, analyze, and act. In a data-informed culture, contributors justify their decisions with data and challenge the management team to do the same.

It’s fast and effective to use data, and it increases transparency across the organization. Emotions and intuition take the back seat. When there’s no robust data-informed culture, there may be a lack of backing in decision making. Ill-informed decisions can lead down a long road of unfruitful iteration and create a lot of organizational waste.

Data-Informed Leadership

Turning an instinct-driven enterprise into a data-informed organization starts with fostering leadership.

Data-Informed Leadership understands the necessity of data, which connects the business to customers and products, drives measurement and accountability, and guides prioritization and resource allocation.

The following are methods for shifting the leadership mindset and techniques so that they can become more reliant on data.

Cultivate a data-informed mindset among company leaders.

Company leaders need to buy into the value of data-informed decision making. They will need to become better at asking questions, figuring out what data is essential, diving deeper into the numbers, testing assumptions, and introducing useful metrics.

Adopt tools that provide accurate insight.

Transitioning to a data-informed culture doesn’t have to be complicated. DISQO uses a few tools to empower leaders and team members. These show us what happened last year, last quarter, and last week so that we can better forecast upcoming trends. We use Flow (Git Prime), 15Five, and Jira.

Empower and foster transparency.

In the journey of building a data-informed culture, it’s essential to create a transparent environment. With transparency, employees can understand company strategies. Being in the know encourages employees to suggest improvements, new metrics, and new ways to collect and analyze data.

Leadership has a significant role in creating transparency. Some indications of transparency are regular all-hands meetings and sharing important business news.

OKRs are a great way to encourage and cultivate a data-informed culture. OKRs in themselves are not enough. The OKR methodology requires its logical adjunct, CFRs (Conversations, Feedback, and Recognition), to provide the communication element. When appropriately implemented, OKRs and CFRs can boost team execution, create an environment of achievement, and produce multiplied results.

This upside-down pyramid shows how OKRs are distributed across DISQO.

The Benefits of Data-Informed Management

Data-informed management has several benefits, including the following.

• Uses standardized processes
• Leverages managerial judgment more thoughtfully
• Encourages faster decision making
• Universalizes the same version of the truth
• Increases productivity
• Reduces risks
• Fosters expanding of skills
• Creates a culture of transparency and inclusivity

Data-informed management relies on transparency, so leaders of these organizations will announce measurement metrics to individual contributors and make tools for measurement accessible to the team. It’s essential to explain what is measured and how.

Data-Informed Performance Reviews

Let’s look at some example performance reviews and promotion discussions between a manager and employee. You’ll see that reviews improve as more data and facts color the conversation.

Unsubstantiated review of an underperforming employee

Unfortunately, you are underperforming, so I cannot give you a salary increase. I think you can do much better by spending less time in meeting and contributing more to the codebase.

Unsubstantiated review of performing employee

I’d like to promote you. It seems like you’re doing a great job, working hard, and helping your team members.

Partially substantiated review of performing employee

I’d like to promote you. You’ve been doing a great job this past year. Everyone seems happier that you’re here. You ask the right questions, and it seems to affect team performance positively.

Substantiated review of performing employee

I want to promote you. You’ve been doing a great job this past year. For example, the velocity of the team increased by 30%, and as a result, we started having more successful sprints. Plus, the number of successful sprints increased by 20%. I got this number from a Jira report, which I’ll share with you.

I want to point out that you’re getting some excellent feedback on 15five from your team members. They seem happy with your contribution, and that’s helping with morale. Tangibly, team satisfaction has increased by 1 point since you joined.

While your contribution is excellent, I’ve also noticed that your team members often thank you for hosting meetings. I’m going to challenge you to think about this — are all of these meetings necessary? Are they long-winded? Are they useful? Do you come out of meetings feeling invigorated and ready to take action?

Addressing some of these questions about meetings can help us determine if they have had a negative impact on qualitative performance. According to the Flow, team efficiency decreased by 10%, and commits per day decreased by 1 point.

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Promotion can be demotivating when done without the proper set-up, context, and thorough backing. In these examples, you may have caught a glimpse of what it would be like on the receiving end of these statements. Qualifying appreciation with details and facts can have a notable impact on communication. And providing feedback can help individual contributors track their performance. For example, in the above example, the individual can come out of the meeting knowing to look at Flow more frequently and ask themselves valuable questions about quantitative performance.

This 15Five user dashboard shows us how the user says they have been feeling at work.

Data-Informed Transformation for Leadership

The following are key questions and concepts that your organization should address if you want to become a data-informed or increase your data-informed culture.

1. What is Data-Informed Leadership? Understand the goal.
2. Do you know your business quantitatively? What are your business objectives for the year and the quarter? Are there metrics attached to these objectives?
3. Use the metrics you identified to make decisions. Each objective should be tied to metrics.
4. Instrument everything. Employ tools that make measurement easy.
5. Store your metrics in one place that’s easy to access and share.
6. Organize and understand your metrics. Cultivate and narrativize insights.
7. Measure progress. Cross-check and validate your progress.
8. Reward progress. Celebrate successes and milestones.
9. Talk about your metrics and progress.
10. Test and adapt your metrics repeatedly. The cycle continues.

Data-informed leaders are not necessarily analysts or data scientists. They recognize the value of these roles and fill these within their companies. They are also not possessive of data. They understand that, like with all knowledge, it is more powerful when shared. They use numbers to set priorities, maintain focus, and allocate resources. Analytics is a driver of a decision-making discipline that ushers in an era of cultural change and improved performance.

Analytical Leaders should use the right metrics, employ decision-making transparent promotions, share KPIs across the organization, and encourage access to data. Leaders stress training and spread analytics throughout the organization.

It’s also important to emphasize that being data-informed means you acknowledge the fact that you only have a limited subset of the information that you need to guide a successful team. Data-informed culture is only valid when it’s used in conjunction with mentoring, coaching, and the human side of management. So while data is used as a basis for decision-making, it’s not the end-all-be-all. The human element cannot be set aside for the sake of numbers. To drive performance for the whole organization, it’s vital that leadership teams learn to balance the humanness of decisions with what’s being demonstrated with data.