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Last updated on 2024年5月10日

How do you determine which drivers to back up and which to ignore?

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In the world of Business Intelligence (BI), knowing which data drivers to focus on is crucial for the success of any analytics project. Data drivers are factors that significantly impact your business metrics and outcomes. They can vary from customer behavior patterns to economic indicators, and identifying the right ones is essential for making informed decisions. You might be wondering how to pinpoint these drivers amidst the vast sea of data. This article will guide you through the process of distinguishing which drivers to back up with further analysis and which to set aside.

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1 BI Basics

Business Intelligence involves the use of tools and processes to transform raw data into meaningful insights for strategic decision-making. Before diving into data drivers, it's important to grasp the core elements of BI. These include data mining, which is the extraction of hidden patterns from large datasets; reporting, which is presenting data in summaries for analysis; and performance metrics, which are standard measurements used to assess the efficiency and effectiveness of actions. Understanding these concepts will help you better identify the drivers that are most relevant to your business goals.

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Jaouid Bourquia

LinkedIn Top Team Leadership Development - Strategy and Technology -Executive in Technology and Perpetual Seeker of Wisdom.?? +80 x Top Voice badges
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In addition to considering the criticality and frequency of updates, it's valuable to back up drivers that are difficult to source or replace, especially for older hardware or niche peripherals, as this ensures continuity of functionality in the event of hardware failure or system reinstallations. Conversely, excluding drivers for easily replaceable components or generic hardware can optimize backup storage space and streamline the recovery process, focusing resources on preserving essential system configurations and minimizing downtime.

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Thomas Hosepian,CPA MBA

Fractional CFO | M&A | Exit Strategy | Strategic Planning | FP&A | Start-up + Middle Market growth acceleration
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Many software providers provide reports that are not customizable and don't provide the information needed to make meaningful analysis. We experienced this with our POS provider and were only provided with "canned" reports which did not provide the information needed to make meaningful analysis, nor did they provide information in real time. Fortunately, we were able to extract the raw data into a data lake and customize reports into a real time dashboard. This allowed us to verify the integrity of the data, provide a single source for all reporting, and customize our reports, which allowed real time tracking and better analysis. This was an essential necessary step which became the catalyst for our growth plans.

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Charitha Sovis

Fabric Analytics Engineer | Microsoft Fabric & Power BI Expert ? | Open to Roles in UAE ????
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Understanding BI fundamentals informs driver selection in my financial performance analysis. Performance metrics measure effectiveness, data mining reveals patterns, and reporting summarizes findings. I am able to identify drivers that are critical for strategic decisions by comprehending these ideas, which guarantees that our analysis successfully complies with business goals.

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2 Identify Goals

Firstly, you need to clearly define your business goals. These objectives will serve as a beacon, guiding you towards the data drivers that are most pertinent. Whether it's increasing revenue, improving customer satisfaction, or streamlining operations, your goals will determine which metrics you should focus on. For example, if customer retention is your aim, you might want to back up drivers related to customer service experiences or product quality, rather than those related to new customer acquisition.

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Charitha Sovis

Fabric Analytics Engineer | Microsoft Fabric & Power BI Expert ? | Open to Roles in UAE ????
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My first step in financial performance analysis is to determine our company's objectives. These goals influence driver selection, whether they are increasing revenue or maximizing operational efficiency. To effectively align our analysis with our strategic goals, I give priority to drivers that are related to expenses rather than revenue growth, for example, if our goal is to reduce costs.

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3 Gather Data

Once your goals are set, gather data from various sources within your organization. This might include sales figures, customer feedback, or operational efficiency metrics. Ensure that the data is accurate and comes from reliable sources. The quality of your data is paramount; basing decisions on faulty data can lead to misguided strategies that may harm your business. Therefore, it's vital to back up drivers supported by robust data and ignore those with questionable or inconsistent information.

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Charitha Sovis

Fabric Analytics Engineer | Microsoft Fabric & Power BI Expert ? | Open to Roles in UAE ????
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I collect information for my financial performance analysis from a variety of sources, including operational and sales metrics. It's critical to ensure data accuracy because trustworthy data helps people make wise decisions. I support drivers that are backed by solid data, like revenue growth trends, and disregard those that have dubious information in order to preserve the integrity of my analysis and effectively guide strategic decisions.

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4 Analyze Trends

With your data in hand, it's time to analyze trends and patterns. Look for correlations between different variables and the impact they have on your key performance indicators (KPIs). Tools like data visualization can help you spot trends that might not be immediately obvious. For instance, you may notice that certain marketing channels lead to higher customer lifetime value. These correlations can point you towards the drivers that deserve your attention and resources.

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5 Evaluate Impact

Evaluating the impact of potential drivers on your business outcomes is a critical step. This involves assessing how changes in a specific driver are likely to influence your KPIs. For example, if an increase in social media engagement correlates with higher sales, this driver has a significant impact and should be backed up with further analysis. Conversely, if a driver shows little to no effect on your desired outcomes, it might be best to ignore it and focus your efforts elsewhere.

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6 Test Hypotheses

Finally, test your hypotheses by conducting controlled experiments or pilot studies. This will confirm whether the drivers you've identified genuinely affect your business metrics. For instance, if you hypothesize that extending customer service hours will improve satisfaction rates, try implementing this change in a limited scope and measure the results. If the data supports your hypothesis, you can confidently back up this driver with broader initiatives.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How do you determine which drivers to back up and which to ignore?

1

2

3

4

5

6

7

1 BI Basics

2 Identify Goals

3 Gather Data

4 Analyze Trends

5 Evaluate Impact

6 Test Hypotheses

7 Here’s what else to consider

Business Intelligence

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How do you determine which drivers to back up and which to ignore?

1

2

3

4

5

6

7

1 BI Basics

2 Identify Goals

3 Gather Data

4 Analyze Trends

5 Evaluate Impact

6 Test Hypotheses

7 Here’s what else to consider

Business Intelligence

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感谢您的反馈

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