So you’ve heard companies talk about how important data is to their operations and revenue. Everyone from Fortune 500 companies to small startups seems to talk about being “data-driven” or using “big data.” But if you’re not planning to become a data scientist, do you really need to learn how to manipulate data? As the founder of data bootcamp Promotable, I’ve spoken with executives from across the spectrum – tech, non-tech, Fortune 500, middle market, and startup companies. All are making investments in data. And I’ve learned that everyone can benefit from a data skillset, even if you’re not working in a technical role.
Across the board, data helps companies find insights, new customers, and behaviors that can help them sell more products to the right people, increase efficiency, and stretch their dollars further. But there remains a significant data skills gap of individuals with the data analytics skills to fill the abundance of available, data-related positions. As companies hire more data scientists and become increasingly data-driven, even non-technical employees who can read, analyze, and communicate data will become increasingly important.
As someone who isn’t a data scientist or data practitioner, you might be thinking “Data is important, but not for me.” I firmly believe that not everyone needs to be a data scientist. However, to be successful in today’s data-driven economy, everyone needs to have a basic understanding of data. Here are 5 reasons why everyone should learn data analytics basics:
In your job, you likely work with people in a range of different roles. This could be on your immediate team, in a cross-functional project, or when requesting resources from another department. Data analytics knowledge can facilitate your interactions:
By understanding how data works and what data analysts and data scientists do, you’ll be better equipped to ask the right questions, have the respect of the technical team members, be more productive, and be a better team leader.
Have you ever been in a position where you know what you need, but are reliant on others like engineers, data scientists, or data analysts to get that data or solve that problem? By becoming data literate and understanding data analytics basics, you will no longer have to constantly rely on the engineering team. Even better, when you do need to request something data-related, you will understand what you are looking for, how long it should take, and what the process should be to get what you need.
The more time you can save, the more time you will have left to be productive and drive value. Having a strong grasp of data means you can save time by not relying on others to pull data, make dashboards, automate simple tasks, and derive insights.
Likewise, without the analytical skills to make data-driven decisions, it’s very easy to make wrong decisions which are very costly in terms of time and money. You could end up costing your employer thousands of dollars, or waste valuable time fixing mistakes that could have been prevented with the right application of data.
Learning to ask the right questions can be the difference between wasting millions of dollars, and solving your company’s most pressing problems (and getting a promotion)! Understanding how to approach a problem and analyze data helps you figure out which questions to ask to find those key customers, to increase sales, or understand what policies or products might be inefficient or lead to wasteful spending.
Decisions are made at every level of businesses. Whether you are in marketing, sales, operations, or other functions, you likely contribute to critical investment and budgetary decisions. These could be as small as deciding which tools to purchase, or as large as the company’s profits and losses. Either way, every employee and manager needs to be able to get the most out of their budget, and make the best investment decisions using data.
In every job, you need to convey the value of your work to stakeholders. Stakeholders can be clients, a boss, or another department. One of the central components of any pitch is being able to clearly and concisely communicate your value proposition, and why it’s good for that stakeholder. If you are able to show your idea, value proposition, or insights, with data to back it up, you are more likely to get that budget approved or close that deal.
According to McKinsey & Company, in 2018 there was a shortage of 1.5 million managers and analysts who were able to use analytical concepts to make data-driven decisions. According to PwC and Iron Mountain, in 2015 only 4% of companies had the skills or technology to make the best use of the data they collect. This mismatch or “skills gap” between the skills companies have, and what they need to make data-driven decisions, represents significant opportunities for non-data scientists to fill some of that technical skill gap while bringing their other functional expertise to the table.
In addition to Data Scientists, an equally important role that companies need in order to incorporate insights into daily business decisions is what McKinsey calls an Analytics Translator:
This role is especially critical because while Data Scientists are experts at extracting and analyzing data, they do not have expertise in other functions of the business. There are many people with skills in marketing, sales, or product analysis. However, having data knowledge and analytical expertise will set you apart from the crowd.
As companies seek to become increasingly data-driven, having the skills to put yourself in the middle as the go-between for the Data Scientists and other functions will make you invaluable and irreplaceable compared to others without the cross-functional expertise.
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