How mobile body measuring software solves the biggest challenges of uniform manufacturing
Everyday uniforms that people wear for their jobs — be it a pair of vintage checkered chef’s pants or a protective utility jumpsuit — are now being reimagined and made both more comfortable and fashionable.
Well-fitted workwear is one of the most important assets for a company that requires its employees to wear uniforms. It’s a visible way to convey a brand’s image, values, goals, and at the same time it represents an indispensable utility and means of protection for its people.
While there’s been a lot of debate around the feasibility of uniforms in some sectors, for others – like public service or military service – workwear is a necessity beyond debate. It is both a vitally protective garment and also represents a great source of pride for the serviceman who wears it.
A well-fitted uniform also goes a long way to convey trust, quality, and experience. And as companies have come to reconceptualize workwear for people who need not only practical but also stylish and perfect fit clothing for actual work, it is no wonder more and more uniform manufacturers and distributors are turning to technology to satisfy these needs.
The current manual process for manufacturers and distributors of uniforms involves people and measuring tapes. For those who have leaned into technology, large and expensive scanning hardware is also an option. Either option drains resources and is time-consuming. Further, we as humans lose and gain weight which means that data is hard and expensive to update (assuming someone has even created a database of body measurements for their employees).
And the bigger the company, the bigger the collateral damage.
As brands and businesses grow, so does the distance tailors need to travel to measure employees, or vice versa, which puts a financial strain on the company in both travel expenses and lost productivity due to travel time.
The average manual body measuring procedure takes approximately 5-20 minutes. Meanwhile ordering uniforms in bulk – when an in-person measurement is required – automatically necessitates a one-by-one approach all destined to be time-consuming and wasteful.
And if to speed up the process, with long travel times, pressure to arrive quickly, and an overwhelming number of people to measure, tailors are stressed, tired, and prone to making mistakes. While ill-fitting, uncomfortable, too-tight uniforms may seem inconsequential to a layperson, professionals know that it does have serious implications and may pose safety hazards.
Besides, if the workwear or protective clothing appears to be ill-fitting because of the poorly taken measurements or a change of size – gaining or losing weight – it is usually up to the employee to bare the financial burden to have the item tailored to fit properly.
Another issue is the sheer number of people that large companies have to measure. Depending on the number of workers to be measured, manufacturers have to supply their own trained employees to take the measurements. So, imagine measuring 18,000 pilots for American Airlines, 70,000 annually-recruited soldiers, or 1,900,000 employees of the largest fast-food chain all over the world. The number of specialists needed to manually serve all these people is immense.
While it’s obvious that measuring for a uniform with a tape measure is an expensive in-person task draining tons of time, finance, and human resources, advances in technology have created an opportunity to digitize this process with mobile body scanning.
Recent advances in AI-powered technologies such as computer vision and deep learning have enabled next-gen mobile body measuring solutions which focus on bringing significant efficiency to the uniform manufacturing supply chain. They revolutionize traditional practices by optimizing three interconnected aspects of the measuring process: people, time and money.
For manufacturers or suppliers, sending staff long distances to manually measure customer’s employees is costly. The travel itself – plane tickets, lodging, and food – adds up. Mobile body scanning software allows anyone to measure themselves anywhere, alleviating the need to complicate schedules and move people around. The implications to global workforces are obvious.
The benefits of digitizing the measuring process have implications beyond saving time and resources. The data that this software computes allows manufacturers and distributors to focus on a body-centered design approach to use this data to optimize the product development, pattern making and grading process. The significance of understanding body data towards inventory forecasting, management, and planning is massive.
The global workwear market is huge – it was valued at $28.3 billion in 2018 – and for good reason. According to the Labor Department, there are about 3 million nurses and 2.5 million cooks, in the US alone. And a lot of them are young people who are used to buying everything online.
Following the transformation occurring in fashion apparel, the uniform segment is following suite and disruptive millennial founded uniform companies catering directly to the consumer are tapped to lead the next wave of disruption. Sellers Commerce predicts that even though uniform manufacturing will continue to be carried out on a contract basis, in the next couple of years the industry will be focused on e-commerce and new delivery methods.
The reason for this is pretty simple. From the consumer’s perspective, the idea of spending time traveling to a police, postal or fire gear store to be fitted and tailored is a huge waste of personal time. People want to buy their uniforms the same way they buy everything else – by pointing and clicking and having the items in their sizes delivered directly to their homes. Many hospitals are already allowing employees to buy scrubs from online uniform providers such as Lands’ End or Figs.
And as mobile devices have long come to play a major role in shopping – with more consumers completing their purchases via smartphones than computers – it is crucial for uniform suppliers to adapt their business model to get ahead. This is where mobile body scanning software comes in particularly handy as it puts the measuring device right into employee’s hand thus providing convenience, portability, and lower costs for both the business and the wearer.
At the end of the day, the measurement methods of yesterday carry more obstacles and expenses than are necessary to bear. Whether it is time, money, or human assets, manual one-by-one measuring drains company resources. Providing employees with an accurate and remote method of measurement will help uniform manufacturers and suppliers save time, eliminate human error, reduce costs, and expand the reach of their businesses.
At 3DLOOK we have built a body data platform that enables a simple exchange of measurement and shape data between your business and your customers.
No more pages to load
BLACK
FRIDAY Deal
ENJOY 20% OFF
FOR 3 MONTHS
The offer is valid if you sign up before November 30.
Applicable to all plans, excluding the ‘Individual’.
Cookie | Duration | Description |
---|---|---|
__hstc | 1 year 24 days | This cookie is set by Hubspot and is used for tracking visitors. It contains the domain, utk, initial timestamp (first visit), last timestamp (last visit), current timestamp (this visit), and session number (increments for each subsequent session). |
_ga | 2 years | This cookie is installed by Google Analytics. The cookie is used to calculate visitor, session, campaign data and keep track of site usage for the site's analytics report. The cookies store information anonymously and assign a randomly generated number to identify unique visitors. |
_gat_UA-92309701-1 | 1 minute | This is a pattern type cookie set by Google Analytics, where the pattern element on the name contains the unique identity number of the account or website it relates to. It appears to be a variation of the _gat cookie which is used to limit the amount of data recorded by Google on high traffic volume websites. |
_gcl_au | 3 months | This cookie is used by Google Analytics to understand user interaction with the website. |
_gid | 1 day | This cookie is installed by Google Analytics. The cookie is used to store information of how visitors use a website and helps in creating an analytics report of how the website is doing. The data collected including the number visitors, the source where they have come from, and the pages visted in an anonymous form. |
_hjFirstSeen | 30 minutes | This is set by Hotjar to identify a new user’s first session. It stores a true/false value, indicating whether this was the first time Hotjar saw this user. It is used by Recording filters to identify new user sessions. |
hubspotutk | 1 year 24 days | This cookie is used by HubSpot to keep track of the visitors to the website. This cookie is passed to Hubspot on form submission and used when deduplicating contacts. |
Cookie | Duration | Description |
---|---|---|
__hssrc | session | This cookie is set by Hubspot. According to their documentation, whenever HubSpot changes the session cookie, this cookie is also set to determine if the visitor has restarted their browser. If this cookie does not exist when HubSpot manages cookies, it is considered a new session. |
cookielawinfo-checbox-analytics | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics". |
cookielawinfo-checbox-functional | 11 months | The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". |
cookielawinfo-checbox-others | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other. |
cookielawinfo-checkbox-advertisement | 1 year | The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Advertisement". |
cookielawinfo-checkbox-necessary | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary". |
cookielawinfo-checkbox-performance | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance". |
JSESSIONID | session | Used by sites written in JSP. General purpose platform session cookies that are used to maintain users' state across page requests. |
viewed_cookie_policy | 11 months | The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data. |
Cookie | Duration | Description |
---|---|---|
__hssc | 30 minutes | This cookie is set by HubSpot. The purpose of the cookie is to keep track of sessions. This is used to determine if HubSpot should increment the session number and timestamps in the __hstc cookie. It contains the domain, viewCount (increments each pageView in a session), and session start timestamp. |
bcookie | 2 years | This cookie is set by linkedIn. The purpose of the cookie is to enable LinkedIn functionalities on the page. |
lang | session | This cookie is used to store the language preferences of a user to serve up content in that stored language the next time user visit the website. |
lidc | 1 day | This cookie is set by LinkedIn and used for routing. |
Cookie | Duration | Description |
---|---|---|
_fbp | 3 months | This cookie is set by Facebook to deliver advertisement when they are on Facebook or a digital platform powered by Facebook advertising after visiting this website. |
bscookie | 2 years | This cookie is a browser ID cookie set by Linked share Buttons and ad tags. |
fr | 3 months | The cookie is set by Facebook to show relevant advertisments to the users and measure and improve the advertisements. The cookie also tracks the behavior of the user across the web on sites that have Facebook pixel or Facebook social plugin. |
IDE | 1 year 24 days | Used by Google DoubleClick and stores information about how the user uses the website and any other advertisement before visiting the website. This is used to present users with ads that are relevant to them according to the user profile. |
personalization_id | 2 years | This cookie is set by twitter.com. It is used integrate the sharing features of this social media. It also stores information about how the user uses the website for tracking and targeting. |
test_cookie | 15 minutes | This cookie is set by doubleclick.net. The purpose of the cookie is to determine if the user's browser supports cookies. |
Cookie | Duration | Description |
---|---|---|
_ga_NXNB16WGX6 | 2 years | No description |
_hjAbsoluteSessionInProgress | 30 minutes | No description |
_hjid | 1 year | This cookie is set by Hotjar. This cookie is set when the customer first lands on a page with the Hotjar script. It is used to persist the random user ID, unique to that site on the browser. This ensures that behavior in subsequent visits to the same site will be attributed to the same user ID. |
_hjIncludedInPageviewSample | 2 minutes | No description |
_lfa | 2 years | This cookie is set by the provider Leadfeeder. This cookie is used for identifying the IP address of devices visiting the website. The cookie collects information such as IP addresses, time spent on website and page requests for the visits.This collected information is used for retargeting of multiple users routing from the same IP address. |
_pin_unauth | 1 year | No description |
_pinterest_ct_ua | 1 year | No description |
AnalyticsSyncHistory | 1 month | No description |
RUL | 1 year | No description |
UserMatchHistory | 1 month | Linkedin - Used to track visitors on multiple websites, in order to present relevant advertisement based on the visitor's preferences. |