Developing a data-driven culture is easier said than done. While many organizations do rely on fragmented data to help inform decisions, smaller to medium sized businesses are often stuck in a sort of data maturity purgatory. They have tons of data at their fingertips—but it’s spread across a TON of disparate platforms, siloed amongst teams and functions, and only pushing out bits of the story.
Here are five easy things to keep in mind when trying to make the leap to a data-driven culture:
Companies that have excelled in creating a data-driven culture have leadership teams that have unapologetically gone out of their way to align expectations with the notion that decisions must be rooted in data. Likewise, that same team needs to invest in the tools, training, and access to data across an organization to ensure their team members are well equipped to make data-driven decisions as fast as possible and monitor the results of their choices as well.
Leading through example is a critical component and having a data-driven leadership team can be more difficult than it sounds. After all, your top brass was likely hired due to their experience and expertise—often relying on split-second gut feelings. Gut isn’t good enough anymore; you need decisions rooted in fact.
Becoming data-driven is nearly impossible if your employees don’t have access to the data they need. In today’s landscape that can be exceedingly difficult for small to medium sized businesses that can’t afford hefty infrastructure changes and data warehousing solutions. That’s exactly why we take all the work out of aggregating, structuring, and showcasing the data from across your company’s entire tech stack in one centralized location automatically.
If your teams are generating valuable data—but they and other team members can’t use the data to create informed decisions—you can’t become data-driven. The more people with cross-functional access to data the better. Truly great data-driven companies also showcase tendencies high in candor, accountability, and transparency.
When data does become universally accessible—you must nip the risk of misinterpretation in the bud. Not everyone will have the same expertise, comfortability, or capability to analyze data in a way that is most impactful. It falls on the leadership team to make sure employees have the appropriate knowledge, understanding, guidance, data dictionary, and training to ensure everyone is rowing in the same direction.
Creating and bolstering data literacy is a continuous methodology—the more opportunities employees have to interact and use data in a meaningful way, the better the results will be. Likewise, tools like Peoplelogic can augment data-driven decision making—by automating analysis and insight discovery, while prescribing actionable recommendations to capitalize on data. This is a great way to help build your team’s confidence with data.
Often, preliminary efforts to become data-driven begin within one function, on a single team, and mature into a siloed, self-isolated system. To get superior value and results it’s important to get a holistic understanding of the data being generated by the entirety of an organization—not only internally, but externally as well (I.e. your customers.)
If your teams know too little about each other, or your executive teams knows too little about other groups in the organization—you can’t become a well-oiled data-driven machine. Data and analytics don’t add broad-based value if the respective programs operate separately from the rest of your business. It’s important to have a centralized location where you can weave a significant, comprehensive contextualized story based on the data across a company.
What good is rolling out an analytics program and driving a data-driven culture if your employees don’t feel empowered to take risks and make decisions? If you have ways in which to monitor and measure the downstream effects of a data-driven decision, you should implore that all employees at all levels should feel comfortable making suggestions around what they are seeing.
Even if something goes wrong, you’ll be able to get back on the tracks faster than your competition because you are actively monitoring the data streams. That’s why Peoplelogic makes a point to surface potential risks and opportunities for growth in real-time based on how the data in your organization is evolving.
In this guide, you will find:
- OKR principles
- Formulas & scores
- OKR methodology
- Step-by-step guide
- Free OKR templates
- Common mistakes
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