People tend to overly rely on their gut instinct when making a decision. Gut instinct, gut feel, intuition—all terms that share a common thread that people “just know” when something feels right or wrong. According to a study conducted by R. Kelly Garrett and Brian Weeks, 50.3% of Americans agreed with the statement, “I trust my gut to tell me what’s true and what’s not.” Intuition is most certainly a valuable tool, sewn into the very fabric of our human DNA, but humans also make mistakes. It’s unwise to base all decisions on intuition and in the business world, a world now flooded with invaluable data, it just doesn’t make sense to rely on your gut.
According to Northeastern University’s Kelsey Miller, data-driven decision making, “is the process of making organizational decisions based on actual data rather than intuition and observation alone.” Data generation is happening in a multitude of forms—surveys, user testing, analytics, passive analytics. In fact, the “last mile” of data-driven decision making exists to make that data usable—to reduce misinterpretation, to add context, and empower ANYONE to make the best possible decision at a given time.
Operationalizing your data across your organization gives you a unique opportunity to understand the cost levers within your organization. By establishing a baseline of inputs, outputs, and cost associations you can also measure the effectiveness of a new product, software, or initiative.
Gut-based decisions are inherently reactive. You receive a stimulus, your brain quickly analyzes it, and you make a decision. If your company falls into the reactive bucket, a data-driven overhaul will empower the company to become more proactive. You’ll be able to identify risks and threats to your business, identify new opportunities, and even get ahead of things like attrition, burnout, and churn. The most important part of using data to become proactive? It gives you a huge competitive advantage in your industry.
When you aggregate, analyze, and interpret data in a meaningful way, you’ll find it is a lot easier to not only reach a conclusion, but decide with more confidence because the risks have been mitigated. It’s important to remember the roles that data can play within any given organization. While data serves as a valuable benchmarking tool, it also serves to quantify the impact of any decision that has been made.
The most important aspect of improving confidence in decision-making is that intuition is taken entirely out of the equation while simultaneously adding a layer of context for easy understanding. Relying on subjective measures and feelings may have worked in the past, but it’s dangerous to continue with that logic, particularly when your competitors are undertaking data initiatives as you read this. By empowering your team to make decisions with confidence, you’re also going to see an increase in buy-in—your team should be more easily swayed into fully committing to a data-driven strategy.
When big data and analytics hit the mainstream, so too did Data Analyst and Data Scientist roles. Often these domain experts’ skillset are in such high demand it’s impossible to secure a high-quality data expert at a smaller, growing organization. Likewise, the market was flooded with tools to help aggregate, analyze, and visualize the massive amount of data being generated—which can add complexity, time to realization, and exceedingly high costs.
Even with all of these tools, a problem still exists. Most people are not comfortable analyzing and interpreting massive amounts of data and information in a meaningful, statistically significant way. This adds a layer of risk to the business as someone may make a confident decision using a wrong conclusion, or even worse, using bad data to begin with.
As artificial intelligence and machine learning have started to be deployed in more impactful ways, it’s now possible to reduce the risk of misinterpretation. A tool like Peoplelogic serves as a manager's personal automated data analyst. The tool seamlessly connects to the tools your team already uses, tools like—Asana, Freshservice, Git, Trello, Salesforce, and many more—and automatically aggregates and analyzes the data for you. On top of that, Peoplelogic adds a contextual layer by pushing automated recommendations and insights directly to you—and even offering a way to explore your data using natural language processing (NLP).
These technological strides are vital to making data-driven decision making more accessible. By leveraging the power of technology, we’re closer than ever before to ensuring everyone, no matter their comfortability or level of expertise in interacting with data, can rest assured that they are making the best decision possible—and doing so confidently.
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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