04.24.2023 Executive Data Bytes – Every Company Is A Data Company!

Executive Data Bytes

Tech analysis for the busy executive.

Welcome to another edition of Executive Data Bytes! This week, we are discussing why every company is a data company, and why every company should strive to be one, even if they aren't.

Focus piece: “Why Every Company Is A Data Company ”

Executive Summary

Companies must be able to collect, analyze, and use data in order to succeed in today's business environment. Companies that can efficiently harness the enormous amount of data generated by businesses and consumers alike will have a competitive advantage over those that cannot. This Forbes article discusses how data is being used to drive decision-making and innovation in a variety of industries, including insurance and apparel, and emphasizes the significance of investing in data analytics tools and personnel.

Key Takeaways

• To begin, it is possible to state that every corporation is a technology company. Because having the correct technology in place is a major, if not the only, way of efficiently acquiring data. As a result, in order to convert to being a data company, it is necessary to first be a technology-centric organization.
• With the importance of technology as a crucial chord in the firm's backbone established, you can today declare that every company is a data corporation. The main reason for this is that every encounter a company has with a customer or client generates data that allows them to better understand the company and the product/service. This data reshapes corporate operations, enabling new revenue streams throughout the global economy, and data will soon become a major product for practically every organization, with data analytics at the heart of every company's business model.
• An illustrative case from the article is Lemonade, an insurance firm that uses AI and analytics to evaluate premiums and accept claims in seconds. It accomplishes this by asking a few simple questions through its virtual assistant and cross-referencing the answers with critical data points retrieved from the internet and other sources. This strategy replaces the former method of spending many hours filling out paperwork and waiting for days for insurance underwriters to review their information using semi-manual processes. This strategy eliminates many error-prone bottlenecks while also improving the client experience.

Focus piece: “Every Company is a Data Company (But Not Every Company is Good at Data)”

Executive Summary

While all businesses now create and use data in some form, not all of them are adept at managing it properly. This Monte Carlo essay underlines the need of companies having the necessary tools, procedures, and people in place to handle the massive volumes of data they generate and extract relevant insights from it. 

Key Takeaways

• Before we proceed, it is required to define a data business. To put it simply, being a data company is being data driven. It means that data drives the majority of the company's operations and choices rather than guesswork or gut instinct, which some organizations still use today.
• However, if not carefully considered, the goal to be data driven has the potential to backfire since organizations may focus on the applications and uses of the data without paying attention to the source and veracity of the data. Because garbage in, garbage out, and unreliable data will almost certainly lead you astray.
• Knowing this, it is critical to ensure that the data used is comprehensive, integrated with other relevant data, and dependable and accurate enough to be used to make judgments. This is significant because it is preferable to have no data than untrustworthy data. Because, while no data moves you forward or backward, inaccurate data will undoubtedly lead to unpleasant and undesirable outcomes. Having accurate data fosters trust, which implies that employees understand where the data came from, what it signifies, and what assumptions it is based on. While focusing on data should be a company's primary responsibility, monitoring the dependability of products derived from data, such as dashboards and machine learning models, is crucial.

Focus piece: “Every Business is a Data Business” 

Executive Summary

So, what's in it for you and your business? You go out of your way to collect data from various sources and process it for consistency, reliability, and correctness. What do you stand to gain from all of this? Dan Martines' post illustrates the concept of every firm being a data company and the benefits that come with it.

Key Takeaways

• Data, especially big data, provides a company with honest information, and having this information allows firms to validate hypotheses and previously held assumptions about consumers' actions or how well a product is functioning. This information also enables personalisation, considering each consumer as an individual rather than categorizing them and offering general information, and thus personalizing experiences to their interests. And once a customer receives such treatment and specific attention, there is typically no turning back.
• Data also allows for the improvement of causality. This means that you not only get to figure out what, but also why. Why do your clients purchase your service? Why do some people like your product while others don't? When this question is answered, it reveals the core cause of certain organizational obstacles, which, if resolved, improve the company's operational efficiency and bottom line.
• To sum up today's topic, it's best to say that in order to be a data firm, which demands being data driven, the organization's culture must evolve. Leaders and executives must instill in their organizations the value of data and the consequences it can have on the business. Also, executives should keep in mind that developing this consciousness may necessitate the formation of previously unknown jobs like as data scientists, chief data officers, and so on. This role will provide the necessary expertise on how the organization may leverage the potential of its data resources in an efficient and effective manner.

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