Data Based Decision Making | 6 mins read

10 Easy Tips for Improved Data Based Decision Making

10 easy tips for improved data based decision making
Lauren Christiansen

By Lauren Christiansen

10 Tips to Improve Data-Based Decision Making

Big data is a buzzword that is frequently used in the business world to emphasize the importance of data collection and analysis. By harnessing all of the available digital information to enhance business intelligence, organizations can make decisions based on statistics rather than guesswork.

Data-driven decision-making is a procedure that requires gathering data contingent on quantifiable objectives or key performance indicators, pinpointing trends, and using them to generate plans and projects that help to make informed choices.

While most companies are effective at collecting all of the data used, they aren't always certain how to use that information to their advantage. By understanding how to make data valuable, an organization can minimize inefficiencies, conduct progress monitoring, generate more profit, and maintain a competitive edge. Here are the top 10 tips to use based data collections to optimize the decision making process in the workplace -

  • More data was created in the last two years than in any other time in data analysis history
  • 99.5% of businesses that are using data never analyze it
  • Over 30% of businesses will make data uploaded into the cloud by 2022
  • Less than 50% of structured data is used to make data based decisions

1. Data-Based Decision Making - Keep Unconscious Bias in Mind

An instructional decision made in the workplace is too often based on intuition and bias rather than evidence and the data used. Executives collect data and find the points that fit their agenda rather than create a strategy based on the findings.

Receiving valuable feedback from team members can prevent one executive's bias or instinct from taking over and making a poor decision. Tips to eliminate bias include being aware of it, collaborating with other members, and finding and asking the correct questions to oneself and others.

2. Data-Based Decision Making - Identify Goals

Businesses should identify their key goals before analyzing data in order to optimize decision-making.

Strategies should meet company needs and not get sidelined by fleeting trends. It is also critical to identify KPIs to know exactly what information should be tracked. While there are several different KPIs to choose from, an organization should begin by choosing the most critical industry-based ones.

3. Data-Based Decision Making - Identify Goals

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Businesses should identify their key goals before analyzing data in order to optimize decision-making.

Strategies should meet company needs and not get sidelined by fleeting trends. It is also critical to identify KPIs to know exactly what information should be tracked. While there are several different KPIs to choose from, an organization should begin by choosing the most critical industry-based ones.

4. Data-Based Decision-Making - Collect Information Now

Any data gathering should begin on the first day of operations to ensure findings are accurate and reliable. Because startups are not exactly sure how to make decisions in the first few years, tracking and logging most data can optimize decision-making sooner than later.

Investing in an data make decisions dashboard that improves project management and generates reports is essential for ensuring all valuable data is collected and placed in a centralized location.

4. Data-Based Decision Making - Ask Good Data Analysis Questions

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Once goals and strategies are determined, the business should decide which questions they need to have answered. This will make certain the company stays on track to meet those objectives rather than getting distracted with unnecessary projects.

Good data analysis ensures the correct information is gathered and optimizes resource management so the business saves money and eliminates waste. Once these questions are addressed, the company can collect only the information needed rather than unnecessary information.

5. Data Based Decision Making - Find Answers to Questions

Because there are usually large quantities of data collected, it's critical to find only the data that answers the critical data analysis questions. When all required data sources are identified, the business can see if the information should be collected internally or externally.

Internal data is anything related to operations such as employee performance, workflow management, or financial data. External data includes customer data, transactional information, market information, website data, or any other information that comes from outside the company.

  • What problems does the company solve?
  • How does the company generate income?
  • Which portions of the company are not profitable?
  • Is cash flow positive or negative each month?
  • What is the decision-making process behind the pricing plan?

6. Data-Based Decision Making - Analyze and Extract Insights

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Once data is gathered, it's time for the company to extract the most valuable insights to optimize decision-making. Generating reports through a customized dashboard, gathering user feedback, and asking customers for their input are all effective ways to improve this process.

Hiring an experienced analyst who specializes in pinpointing trends, analyzing historical information, and making predictions are critical for growth-driven organizations.

7. Data-Based Decision-Making - Revisit and Assess Findings

It's human nature to jump to conclusions once initial findings are made. Most individuals prefer finishing a project the way it is rather than starting all over, even if current methods aren't working out the way they should be.

Unfortunately, a poorly devised project will have to be redone eventually, so it's better to do it sooner than later. Frequently revisiting and reevaluating findings always leads to better results, even if it's time-consuming and frustrating.

8. Data-Based Decision-Making - Present Findings Effectively

Extracting valuable insights is critical, but it's more important that findings are displayed in a way that everyone can understand them. Any insights should be easy to reference so they can be used for future problem-solving.

By utilizing an automated software solution to generate reports with powerful visuals, everyone can easily understand what the data is trying to say. Charts, graphs, and intuitive reports are quick to read and effective for meeting presentations with management.

9. Data-Based Decision Making - Objectives Should be Measurable

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To optimize decision-making, all of the findings should be aligned with the organization's vision statement and core values.

Establishing measurable objectives to track time spent on projects, the allocation of resources, and performance will ensure the company is on target. It's also important to note that even if the data is contradictory to the company's needs and core values, any decisions made should still be aligned with those values.

10. Data-Based Decision Making - Never Stop Analysis

It's critical to never stop reevaluating and revisiting every single data-driven choice made. Because businesses are constantly collecting more data each day, it's imperative to ensure that decisions are based on the latest insights. Evolving company goals when data findings change is required for meeting the needs of consumers and maintaining a competitive edge.

  • Data analysis helps businesses avoid additional expenses
  • Thoroughly understanding any data collected
  • Data-driven analysis helps to understand required capabilities and progress monitoring
  • Decision-making data shows which market to tap
  • Redesigning workflows to optimize productivity and improve data based decision making

Data-Based Decision-Making - Key Takeaways

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In conclusion, here are the top tips to improve data-based decision-making

  • It's critical to keep unconscious bias in mind and make decisions based on evidence rather than guesswork. The company should also identify goals and a set of KPIs.
  • Information should be collected in real-time to optimize future decision-making. Good data analysis questions must be answered to make sure the correct information is gathered.
  • The business should find the data that answers all of the questions rather than collecting anything just to be safe. Next, it's time to extract insights by utilizing an optimized software solution.
  • Findings should regularly be revisited and reevaluated to keep findings up to date. Insights should be presented by using powerful visuals and reports so they are easily understandable. All objectives must be measurable to track progress towards goals and executives should never stop questioning and analyzing as company needs do evolve.

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