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Home»Startup»3 Common Mistakes In Data-Driven Decision-Making
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3 Common Mistakes In Data-Driven Decision-Making

December 26, 2022No Comments4 Mins Read
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3 Common Mistakes In Data-Driven Decision-Making
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By Yongxing Deng, co-founder and CTO of Aloft, an actual property expertise startup primarily based in Seattle, WA.

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As a enterprise chief, you’re typically anticipated to make use of knowledge to make an knowledgeable choice, no matter whether or not your job title incorporates the phrase “knowledge.” All the pieces from how a lot finances to allocate to a advertising marketing campaign, to what number of headcounts to approve, to what the gross sales projection must be. Nevertheless, making data-driven selections isn’t just a slogan, it’s a instrument that has finest practices to observe. Listed here are three frequent errors enterprise leaders make whereas utilizing knowledge to make selections.

Skipping Information Validation

When introduced with a decent timeline (as we frequently are) and an information set, it’s tempting to right away begin analyzing the information set. Nevertheless, your findings can solely be as helpful and informative as the standard of the underlying knowledge, so it’s essential that you simply spend adequate time and power validating the accuracy of your knowledge set.

On the subject of knowledge validation, begin with a skeptical eye towards the information. Put your detective hat on and attempt to discover the failings within the knowledge. Use your present enterprise information to finish the next sentence: If the information is correct, then ______. Then, use SQL or Excel to validate these assumptions earlier than continuing with the precise evaluation.

Underestimating The Impression Of Low-Likelihood Occasions

Occasions which are much less prone to occur can typically have an outsized affect on the objectives you are attempting to realize. For instance, whereas pandemics occur hardly ever, few companies around the globe haven’t been meaningfully impacted by Covid-19 prior to now few years. As a enterprise chief, it’s not possible so that you can foresee all of the low-probability occasions that might occur, and but you’re typically having to decide in any case. What do you do?

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One method is by explicitly asking your self: Given the length of the information out there, what may the information not have “seen?” For instance, in case you have two years’ value of gross sales knowledge, then you may assume any uncommon occasions that occur yearly have in all probability been included in your knowledge. As such, the occasions don’t want particular consideration to be accounted for in your evaluation. However, in case you have solely six months of gross sales knowledge, then you must work together with your crew to suppose by means of conditions that may solely occur yearly (seasonality involves thoughts) and use your enterprise judgment to supplant your knowledge findings. Presenting an inventory of low-probability, high-impact occasions alongside your evaluation can typically assist your stakeholders make a lot better selections.

Overlooking The Energy-Person Impact In Your Evaluation

Let’s say you’re a fitness center proprietor, and you are attempting to estimate on common how typically your members train at your fitness center. One “simple” method to do that: Stand on the entrance desk, ask the following 20 members who stroll by what number of occasions they’ve visited the fitness center prior to now month, and take a mean of these 20 solutions. Beware—the common you derived this manner won’t signify your whole membership inhabitants. Why? As a result of a frequent fitness center goer is more likely to be surveyed by you than a member who solely visits the fitness center as soon as a month.

When conducting an evaluation on product utilization, you could rigorously study whether or not the methodology you employ ends in findings biased towards your energy customers. This isn’t to say that you could disregard the outcomes you discover this manner, however this does imply that you must proceed with warning.

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It’s not an exaggeration to say that a lot of our work lives now revolve round knowledge. As enterprise decision-makers, we should deal with knowledge evaluation as a strong instrument that additionally has traps and errors and critical methods to trigger harm. By combining knowledge with our personal instinct, and continually difficult our personal methodologies, we are able to maximize the utility of knowledge evaluation.

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