Play With Numbers: How To Turn Data Into Actionable Insights For Business Growth

Irrespective of the role that you play in your organization, having the right aptitude to convert raw business information or turn data into actionable insights is slowly becoming a must-have skill needed for the growth of carriers in all industries across the globe. In fact, according to an HBR (Harvard Business Review), it has been found that more than even 60% of business enterprises wants their senior leaders to have proper data-analysis skills that can help to contribute to providing strategic business decision-making skills that can turn them into an indispensable member of any team. Therefore as one of the most popular vendors of Salesforce Alternative CRM tools with hundreds of active users across the globe, to help you build the right mindset and skills here are some of the key strategies and skills that can help you to turn data into actionable insights which can predict rapid business growth.

Irrespective of the role that you play in your organization, having the right aptitude to convert raw business information or turn data into actionable insights is slowly becoming a must-have skill needed for the growth of carriers in all industries across the globe.

74% of CRM software users said that their CRM system gave them improved access to customer data. - Capterra (2021) Click To Tweet

In fact, according to an HBR (Harvard Business Review), it has been found that more than even 60% of business enterprises wants their senior leaders to have proper data-analysis skills that can help to contribute to providing strategic business decision-making skills that can turn them into an indispensable member of any team.

Therefore as one of the most popular vendors of Salesforce Alternative CRM tools with hundreds of active users across the globe, to help you build the right mindset and skills here are some of the key strategies and skills that can help you to turn data into actionable insights which can predict rapid business growth.

1. Do Not Make Things Too Complicated

Primarily once you start learning how you can turn data into actionable insights for your business, it is imperative that you must understand that every business or company has problems that need to be solved or even things that can be improved for finding more revenue growth.

Hence look for an opportunity to reduce cost, meet evolving customer needs, dive efficiency and thereafter prepare a set of questions that will help to generate insights and decisions through analysis.

Now, for finding insights from raw and unstructured data, you do not always need to use Python or R programming to perform basic analysis tasks.

Therefore start by using Excel or other simple tools to uncover insights, trends, and patterns and thereafter convert a few rows of data into a chart which can help to reveal unexpected and hidden things about your business.
Do not worry to get things right the very first time, but rather accept your mistakes and thereafter try to improve.

In fact, if you just have the basic technical expertise of how you can work with a business CRM solution or an Excel chart, have knowledge about your business domain, and proper communication skills, you practically have everything that you need to get started with data analysis for your company.

2. Work With What You Have Got

Remember while you are building your skills to turn data into actionable insights for your business, data is messy and there are bound to be gaps, holes, and imperfections in your datasets.

Now this is true since most useful raw data required for solving business issues is often collected from social media platforms and webpages where symbols like hashtags, ampersands, dollar-signs, etc., will remain in the data, and so you have to be able to work with what you have got.

As one of the award-winning vendors of CRM for small and medium businesses, we can assure you of the good news that the underlying information for turning data into actionable insights does not have to be perfect to provide useful insights, as long as you keep a few things in mind.

For example, before analyzing the data you need to understand where the data comes from and thereafter determine which sources will be most useful to solve your problems.

Additionally, never make assumptions about the completeness poor quality of the data.

Rather go through each dataset and verify that everything is (relatively) clean and useful. Hence always perform a visual inspection of your raw data since missing data or large gaps in data needs to be taken into consideration when making observations or drawing conclusions from the finding generated from those data.

Finally, remain vigilant and extra-careful when handling missing values or filling in the blanks in machine-learning datasets, since such things might produce biased conclusions.

Therefore, to remain on the safe side, apply common sense to the insights that you have discovered from the data before recommending actions.

3. Sell Your Ideas Effectively

Remember even great business growth ideas, cannot survive bad presentations. And sadly many new and even veteran analysts fall short when they reach this part of the data analysis process since they lack the ability to sell their ideas to stakeholders in a concise, confident, and effective manner.

Hence even before you learn how to turn data into actionable insights for your business, enrich your skills of telling a story without graphs, charts, or PowerPoint slides.

Learn to condense a story into a single line “sound-bite” that will resonate appropriately with your audience.

Never use data as a crutch.

Therefore ask these simple questions to yourself before selling your ideas, which includes (but is not limited to):

  • What does this information ultimately mean?
  • What point are you trying to make?
  • How do your results and conclusions tie back to the original problem in your business?

Once you have all the proper answers to these questions craft a narrative that should resonate instantly with your target audience, since a good data analyst has to be able to present their ideas in a way that everyone can understand and you really do not need a crystal ball to predict the future or act wisely to make a lot of sense in real life.

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