Businesses are quickly recognizing the importance of data in decision-making processes. Leaders understand it presents facts that can be used to predict trends, inform strategies, and optimize processes. But getting from point A to point B is not so easy.

Companies must know how to harness data and what to look for to use it efficiently. They must determine their organization’s pain points and how data can help them find solutions. With the right approach, they will move their company forward.

Identify the Issue Data Solves

The first step involves determining why you need the data. Here are some common instances where data comes in handy in an operations environment:

• Complex decision-making: Complex decision-making can refer to any aspect of operations. Data can reveal valuable insights that provide clear guidance and foster unanimous decision-making in board environments.
• Identifying the best technology for operations: With so much tech available, finding the right systems for your company can be challenging. Data gathers statistics across various resources to help you determine which is suited to your needs.
• Optimizing business supply chain processes: Companies can collect data to help them identify breakdowns in supply chain processes so they can run their companies more efficiently, saving time and money.
• Predicting trends: Data can predict trends within the industry and customer behavior, guiding inventory management and various aspects of customer service.
• Improving logistics: Logistic-related data can reveal the best systems for delivering goods efficiently, helping companies save time and money.
• Predictive maintenance: This data type detects anomalies within systems so they can be addressed before they lead to expensive repairs.

Once you know your issue, set goals and objectives and define key metrics that will allow you to measure your progress.

Determine Which Data You Need

With so many data types to choose from, you must determine the one that is best suited for your organizational needs. Data generally falls into one of two categories as follows:

• Operational Data: Operational data provides information on all aspects of your operations, including order processing, financial transactions, fraud detection and risks, customer service, and predictive maintenance.
• Analytical Data: Analytical data involves mining and processing historical data to look for patterns, trends, and insights that guide decisions. It can optimize pricing strategies, predict customer behavior, and determine marketing campaigns.

Operational and analytical data are not mutually exclusive. They often complement each other. For example, if fraud activity is detected, operational data will reveal when and how it happened, while analytical data helps uncover why.

Putting the Data to Use

Once you have determined your goals and data type, you must embark on several processes that will ensure you get accurate results:

1. Determine Data Sources: You may refer to internal databases, such as metrics recorded by your company, or external sources, such as customer surveys and reviews.
2. Data Quality: Ensure data is accurate. Data cleaning may be required to address inconsistencies, errors, and missing values.
3. Data Structure: Organize data in a way that facilitates analysis.
4. Data Analysis: Analyze data by looking for key trends and patterns. Investigate their causes.
5. Predictive Analysis: Use data to forecast possible outcomes.
6. Prescriptive Analysis: Recommend actions based on the predictive analysis.
7. Apply Human Insight: Don’t rely on data alone. Run analytics by board members to gain human insight. Consider the context in which the data will be applied.
8. Document Decisions: Document your decision and work out an action plan.
9. Monitor Results: Continue monitoring your results. Adjust your plan as needed.

What are the Benefits of Using Data in Decision Making?

• Leads to Faster Decision Making: Leaders are more likely to make decisions quickly when presented with the facts. It minimizes the need to mull over choices and determine the best outcome. Faster decisions lead to more efficient systems, speeding up processes and improving customer service.
• Better Outcomes: Decisions guided by data are backed by facts, often leading to better outcomes.
• Unify Organizations: When board members disagree, it slows decision-making and can promote a hostile work environment. Data makes stakeholders more likely to agree on decisions promoting positivity and efficiency.

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