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Tidying Up your Data With The Marie Kondo Method

For most of us, everything in our lives could benefit from a little tidying up. From our houses, cars, and closets to our business systems, procedures, and data. In this post, we apply Marie Kondo's KonMari methodology to tidying up business data.
Tidying Up your Data With The Marie Kondo Method

Cleaning mogul, Marie Kondo’s rise to popularity may seem as if it occurred overnight when her show, Tidying up with Marie Kondo was released on Netflix, New Year’s Day. However, unbeknownst to many, Marie Kondo had made a name for herself within the ‘cleaning world’ long before the hit show’s premiere. In 2011, she released her first book The Life-changing Magic of Tidying Up which introduced many cleaning fanatics to the now famous ‘KonMari’ method. The KonMari method is a guideline for tidying.

The philosophy behind this guide boils down to one being able to do the following 6 things:
  1. Commit yourself to tidying up
  2. Imagine your ideal life
  3. Finish letting go first
  4. Tidy by category, not location
  5. Follow the right order
  6. Ask yourself if it sparks joy.

So - How does this relate to business?

How does this cleaning phenomena relate to business? For most of us, everything in our lives could benefit from a little tidying up. From our houses, cars, and closets to our business systems, procedures, and data. With data, it can be easy to become unaware of expired or inaccurate information which could be draining the company wallet and preventing new opportunities. If data is not accurate, up to date, well organized, and easily understood, the value of data analytics drops drastically. Before you know it, bad data could be seeping into your reports and leading you to make poor decisions based on invalid data. Taking inspiration from Marie, we can utilize her tips and tricks to tidy up our organizations so hopefully we can better manage and use our data efficiently to ultimately have a positive impact on our bottom line.

Marie’s 6 Steps:

Lets look at Marie’s 6 steps and how they can be used to tidy your data.
1. Commit yourself to tidying up: Make sure you have the time and motivation to tidy up. If you are going to start tidying up your data without finishing you may make things worse and messier.
2. Imagine your ideal life: What is your ideal way to house your data? What is your ideal way to validate your data? Questions to keep in mind when organizing.
3. Finish letting go first: Make sure to get rid of ‘bad data’ first. Decluttering without actually getting rid of anything, lessens the positive results of tidying.
4. Tidy by category first, not location: Tidying a specific category lets you take inventory of everything you have, possibly uncovering data sources you have forgotten about and/or lost.
5. Follow the right order (clothes, books, papers, miscellaneous items and finally, sentimental items): Although data doesn’t usually take a physical form, we can use the overall idea of sorting from things we do not have much of a connection with (clothes & books) to things that we do have a stronger connection with (sentimental items). Looking at data that we can pinpoint quickly as being unused & unneeded, unreliable or just old and unusable is easiest to rid of because we have little to no need or connection with this data. This serves as the clothes/books in the KonMari method. Data that may be harder to go through and is webbed and interconnected through the business, requires more effort to appraise its quality and value. This type of data serves as the sentimental items in Marie’s method.
6. Ask yourself if it sparks joy: Data - sparking joy? Data may not give you personal joy, but having good data to back up critical decisions will definitely give your board members and/or shareholders joy when they see company financial statements. Data that is accurate and unbiased can increase the value of your data analytics systems fueling you to make better decisions for your organization.

Tips & Tricks to Tidy Up Your Business Data

Keep things in boxes: Throughout season 1, Marie consistently shares her love for storing things in boxes because of how they keep smaller objects easy to find while looking streamlined and visually appealing from the outside. When looking at data storage - dashboards are the equivalent of these boxes. Like boxes, data dashboards are a great way to store smaller data reports without being too overwhelming to the eye, which can lead to important information being missed or overlooked. Data dashboards highlight and neatly display the KPIs of your choosing while also allowing you to dig down into the ‘nitty-gritty’ behind them. For more information on the psychological benefits of using data dashboards check out our past blog post here.

Establish a system: Although this may seem like a given, establishing a universal tidying system for your company is important in long term organizing success. Having a predetermined method for how things will be filed and categorized (i.e: by company name, state, industry, etc.) can eliminate unnecessary stress when searching for something specific and being unable to find it. Dedicating time to checking the accuracy of your data also helps to ensure ‘bad data’ isn’t coming in. Choosing a system makes it easier to store new data because everyone would be on the same page to how it is being stored. Setting time aside whether it be on a weekly, monthly, or quarterly basis to refresh and check in on the success of the determined organizational system can help to eliminate bad data from coming unnoticed and being used in important decision making.

Marie Kondo your Business Data
Having accurate data and a great data analytics system is incredibly important to ensure your company isn’t unknowingly losing profit from the bottom line. Loyalty and Rewards programs are a successful way to retain customers, however, fraudsters have cracked the code to gaming these programs.

View our on-demand webinar recording with our customer, Shoe Carnival to learn how they leveraged data analytics stop reward points fraud & abuse.

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