How to become a data-driven business | Mode - EU-Vietnam Business Network (EVBN)

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What is a data-driven organization?

Just about every business leader today wants to build a data-driven company. Pitch decks are stacked full with promises of AI and machine learning, real-time data, and intelligent insights, with companies investing millions into tools and data initiatives designed to add value.

But what does it really mean to be data-driven?

A data-driven organization is one that embraces a culture of data exploration, has company-wide policies and guardrails in place that ensure accuracy, and one that provides solutions that both analysts and non-analysts can use to find answers to important business questions. In a data-driven company, everyone is able to make decisions based on reliable, standardized information across many platforms, time zones, and teams.

When data is democratized, everyone can benefit from it without being overwhelmed by manual tasks, being confused about how to interpret it, or the need for a specialized data science skillset. This, and the fact that leadership and employees view data as a critical asset that’s worth investing in, makes a company data-driven.

What does a data-driven business look like?

It can be difficult to understand how effective your business is at using data to inform decision-making. One way to assess an organization’s data-driven capabilities is by benchmarking against the Mode data maturity model—take a look at the five stages below to see where you fall.

1. Patchwork analytics

At the first stage, the company has no official data team. Data analytics is decentralized, with a patchwork of tools and data sources—each department assesses their own data and tries to connect them through exports, spreadsheets, and some integrations. Most analysis is done on historical data, with little to no real-time streaming data sources. At this stage, the manual nature of data management often leads to errors, inconsistencies, and inaccurate reporting.

There’s no company-wide data strategy to enable decision-making, partially because the culture isn’t there. Leadership still leans heavily on instinct over data.

2. Departmental analytics

At this stage, there’s still no centralized data team. However, a data analyst might exist in some departments. Data collection is a little more streamlined but analytics is still siloed from team to team, with some departments taking the lead in data maturity or using different tools than others.

3. Reactive analytics

In the third stage, data becomes centralized but still is not accessible to everyone. The company has a data team but their analyses are mainly reactive to data requests from different departments. Internal stakeholders typically put in a request for reports or dashboards, then wait for the data team to get through a backlog to fulfill it.

By now the company likely has an enterprise-wide BI tool, along with a data stack that pipes data from  different sources into a connected warehouse. They have some data governance in place, and are likely working toward self-serve analytics.

In terms of culture, people think of data mostly as a tool to track performance.

4. Proactive analytics

At this stage, the company does have a data-driven culture. Team members proactively seek out opportunities with data, with non-analysts taking it upon themselves to analyze data using self-serve tools. Data team members and business stakeholders collaborate often, predictive analytics are in play, and the culture encourages viewing data as a product rather than just a performance-tracking tool.

5. Democratized analytics

The holy grail of data-driven companies, an organization at this stage uses data to inform nearly all decisions. The majority of domain experts are also citizen analysts, and are active in ongoing experiments to uncover more value from company data. There’s a clear process for when and how data teams should invest in data applications, and the company culture is completely intertwined with data—every crucial decision is data-driven.

A Data Maturity Assessment

See where your team falls on our data maturity assessment.

How to become a data-driven organization

Before you do anything, it’s a good idea to make sure your team is ready to embrace data at the next stage. You’ll want to have buy-in from your stakeholders on investing in a data analytics solution that works for your company’s goals and structure. Once you get the go-ahead, it’s time to invest in a platform that can deliver value quickly.

1. Connect your disparate data on one platform

The first step is building a pipeline for your data. Mode was made to bring data sources together quickly—integrate data from each business function, like marketing, sales, and customer support. Believe it or not, you can build and deploy a complete data stack in just 30 minutes or less, regardless of how big your company is. Once data is connected and analysts can start exploring, you can deliver rapid impact, which can go a long way toward driving cultural change and convincing key stakeholders to trust and utilize data in their daily operations.

2. Establish key metrics to guide the company’s strategy

To become data-driven, Stancil recommends companies focus on key analytics — or north star metrics — to separate truth from opinions and make objective, reasoned business decisions. This, Stancil says, is more important than focusing on generating revenue or padding the bottom line.

There are some specific conditions that are necessary to make this happen. For example, key metrics need to be singular.

“Companies can’t chase dozens of performance indicators, with each team having their own preferred set,” Stancil writes. “If they do, everyone ends up confused; at worst, people proxy their opinions through weaponized KPIs. This doesn’t end arguments; it escalates them.”

What’s more, metrics also have to be achievable, and they have to endure. In other words, you shouldn’t be changing key metrics regularly. Instead, as Stancil points out, the metrics you’re optimizing need to point to the spot where you want to be on the horizon.

3. Break down silos and democratize data

To become data-driven, companies must actively work to break down data silos and provide teams with shared definitions and clean data sets. The end goal should be complete data democratization, where everyone in the organization can feel comfortable gleaning insights from different data sources and using them to make better decisions.

4. Make reports easy to read

Most employees today have limited skills when it comes to analyzing and interpreting data. According to a recent Harvard Business Review article, just 25% of workers feel confident in their data skills. For this reason, it helps to optimize reports by making them visually appealing and easy to read. By doing so, people can explore them with confidence regardless of their skills and experience. Clear visualization makes it easier for non-technical teams to access and understand data and know how to apply it in everyday scenarios.

Making reports easy to access and use can also help improve data literacy. The more employees interact with data, the more comfortable they will become using it and relying on it to make decisions.

5. Encourage data-driven meetings

Another great way to become more data-driven is to provide cross-functional, data-driven updates with different teams. Best practices say that organizations should ask their data teams to participate in such initiatives. Including the data team enables employees to ask questions to their colleagues who know how to answer them. It also provides additional opportunities for learning and growth.

6. Use interactive data dashboards

Many teams are having success using interactive reports and dashboards that enable employees to access and interact with data in a place that’s secure and user-friendly. For example, Mode dashboards makes it easy for team members to analyze data and iterate, ask questions, and receive answers in one platform.

Becoming data-driven takes time

Organizations can’t become data-driven overnight. It takes substantial resources and buy-in to get from stage one to five, but doing it will pay off in dividends.

As Mode Co-founder and Chief Analyst, Benn Stancil, explains in a recent blog post, being data-driven is a long game, and it takes time to accumulate an advantage. Business value comes from putting in the effort of accumulating small wins, which add up over time.

To move toward becoming a truly data-driven company faster, you should choose software and partners that have data built into their DNA.

What are the benefits of becoming a data-driven business?

When you can confidently make decisions based on your company’s data, you’ll more easily forecast the future, measure and improve performance, and uncover critical insights about the organization—sometimes ones you weren’t even looking for.

1. You know when to pivot or double down

Being data-driven gives executives and managers the facts to support their decisions, reducing risk and making it easier to know when to pivot or double down.

2. You can begin to build a culture of data literacy

Because data-driven businesses establish a culture of data literacy, they talk about metrics early and often. Everyone feels a sense of accountability are more self-sufficient when they need quick answers.

3. Make better choices, faster than your competitors

Finally, data-driven businesses just make better choices. Armed with a constant flow of information about their company and customers (plus technology to keep up with and interpret it), these companies move faster and more confidently than their competitors.

4. Identifying financial risks before they arise

Data can be helpful for identifying and mitigating financial risks. For example, streaming companies use predictive analytics to anticipate when users are likely to cancel a subscription. By adjusting the customer experience or sending special offers, they may be able to avoid churn.

How can Mode help your company become data-driven?

At Mode, our philosophy is that analysis is only as good as the decisions that are made with it. Mode empowers analysts to get closer to the business and non-analysts to get more comfortable exploring data for maximum decision impact.

Here at Mode, we work with companies that have different levels of data maturity and needs. For example:

Lyft, Patreon, and Domain all used Mode to improve their data usage and navigate the pandemic.
We recently helped Cash App’s product team drive strategic business decisions and focus on deeper analysis. Thanks to partnering with Mode, Cash App experienced a 30% increase in data team productivity.
We’re helping Shopify become more data-driven by empowering employees with the data they need to think ahead and make strategic decisions every day. With Mode, Shopify is able to deliver reports to teams in just minutes — not hours.

Data-driven companies come in all shapes and sizes. But they share one important thing in common: making data accessible and valuable to all. Take a look at any data-driven company and you’ll find talented data officers, a data-oriented culture, well-governed data access, and a modern stack that connects every source and solution.

From the outset, becoming a data-driven organization may seem like an intimidating process, especially if your business is behind the curve. But any company can become data-driven—it’s just a matter of prioritizing data investments and being willing to instill it into your culture.

Take your first steps towards becoming a data-driven business

At the end of the day, your business can become more data-driven if you’re ready to make the commitment. As a next step, we recommend taking our assessment to identify where your data team is on the maturity scale.

If you’re ready to see what Mode can do for you, request a demo today.