Waste

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Eliminate DevOps waste with Japanese management practices

Liran Haimovitch
Contributor

Co-founder and CTO of Rookout, Liran is an award-winning cybersecurity practitioner and writer who advocates for modern software methodologies.

Across the board, industries need to embrace modern workflows to keep up with the speed of startups. And out of all the various methodologies, I find the “lean methodology” to be the most intriguing of them all. It’s a unique combination of pragmatism and a higher purpose.

Lean methodology descends directly from the Toyota Production Systems (TPS), which is based on a philosophy of eliminating waste to achieve efficiency in processes. It relies heavily on the mindset of “just-in-time,” making only “what is needed when needed, and in the amount needed.” In software development, this means only developing the features your clients need, and only when they need them.

To emphasize the point and stir some creative juices, let’s look at the Japanese concepts of muda, mura and muri, and how this applies to being lean when we are building and shipping software.

Muda, mura and muri

Muda is the “waste” we are working to remove that is directly hurting efficiency. Waste is any activity that doesn’t create value, in the form of the products and services we offer. As every engineer knows, spending half the day in meetings is a painful waste of time.

Mura is “unevenness,” referring to any variance in the process itself or the output generated. In software development, “mura” causes unpredictability that makes it impossible to embrace a “just-in-time” mindset. If the quality of a new upcoming feature is uncertain, then additional time and resources will have to be reserved for quality assurance and bug-fixing efforts. It’s better to know upfront what you are going to get, how long it will take and what the cost will be.

Muri is “overburden,” which happens when we demand the unreasonable from our team, tools and processes. If we want to deliver a specific feature just-in-time, then we must allocate the appropriate time and resources. Giving our engineering teams too many simultaneous tasks, or failing to give them the tools necessary to succeed, will only lead to disappointment in time, quantity, quality or cost.

Forms of waste

Diving deeper into muda — what I consider the cardinal sin of lean methodology — here are the forms of waste we should always be on the lookout for:

  1. Overproduction – Producing more than is needed, or before it is required. Besides unneeded features, we often over-allocate computing resources, especially in non-cloud environments.

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Greyparrot bags $2.2M seed to scale its AI for waste management

London-based Greyparrot, which uses computer vision AI to scale efficient processing of recycling, has bagged £1.825 million (~$2.2M) in seed funding, topping up the $1.2M in pre-seed funding it had raised previously. The latest round is led by early stage European industrial tech investor Speedinvest, with participation from UK-based early stage b2b investor, Force Over Mass.

The 2019 founded startup — and TechCrunch Disrupt SF battlefield alum — has trained a series of machine learning models to recognize different types of waste, such as glass, paper, cardboard, newspapers, cans and different types of plastics, in order to make sorting recycling more efficient, applying digitization and automation to the waste management industry.

Greyparrot points out that some 60% of the 2BN tonnes of solid waste produced globally each year ends up in open dumps and landfill, causing major environmental impact. While global recycling rates are just 14% — a consequence of inefficient recycling systems, rising labour costs, and strict quality requirements imposed on recycled material. Hence the major opportunity the team has lit on for applying waste recognition software to boost recycling efficiency, reduce impurities and support scalability.

By embedding their hardware agnostic software into industrial recycling processes Greyparrot says it can offer real-time analysis on all waste flows, thereby increasing efficiency while enabling a facility to provide quality guarantee to buyers, mitigating against risk.

Currently less than 1% of waste is monitored and audited, per the startup, given the expensive involved in doing those tasks manually. So this is an application of AI that’s not so much taking over a human job as doing something humans essentially don’t bother with, to the detriment of the environment and its resources.

Greyparrot’s first product is an Automated Waste Monitoring System which is currently deployed on moving conveyor belts in sorting facilities to measure large waste flows — automating the identification of different types of waste, as well as providing composition information and analytics to help facilities increase recycling rates.

It partnered with ACI, the largest recycling system integrator in South Korea, to work on early product-market fit. It says the new funding will be used to further develop its product and scale across global markets. It’s also collaborating with suppliers of next-gen systems such as smart bins and sorting robots to integrate its software.

“One of the key problems we are solving is the lack of data,” said Mikela Druckman, co-founder & CEO of Greyparrot in a statement. “We see increasing demand from consumers, brands, governments and waste managers for better insights to transition to a more circular economy. There is an urgent opportunity to optimise waste management with further digitisation and automation using deep learning.”

“Waste is not only a massive market — it builds up to a global crisis. With an increase in both world population and per capita consumption, waste management is critical to sustaining our way of living. Greyparrot’s solution has proven to bring down recycling costs and help plants recover more waste. Ultimately it unlocks the value of waste and creates a measurable impact for the environment,” added Marie-Hélène Ametsreiter, lead partner at Speedinvest Industry, in another statement.

Greyparrot is sitting pretty in another aspect — aligning with several strategic areas of focus for the European Union, which has made digitization of legacy industries, industrial data sharing, investment in AI, plus a green transition to a circular economy core planks of its policy plan for the next five+ years. Just yesterday the Commission announced a €750BN pan-EU support proposal to feed such transitions as part of a wider coronavirus recovery plan for the trading bloc. 

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Image recognition, mini apps, QR codes: how China uses tech to sort its waste

China’s war on garbage is as digitally savvy as the country itself. Think QR codes attached to trash bags that allow a municipal government to trace exactly where its trash comes from.

On July 1, the world’s most populated city (Shanghai) began a compulsory garbage-sorting program. Under the new regulations (in Chinese), households and companies must classify their wastes into four categories and dump them in designated places at certain times. Noncompliance can lead to fines. Companies and properties that don’t comply risk having their credit rating lowered.

The strict regime became the talk of the city’s more than 24 million residents, who criticized the program’s inflexibility and confusing waste categorization. Gratefully, China’s tech startups are here to help.

For instance, China’s biggest internet companies responded with new search features that help people identify which wastes are “wet” (compostable), “dry,, “toxic,” or “recyclable.” Not even the most environmentally conscious person can get all the answers right. Like, which bin does the newspaper you just used to pick up dog poop belong to? Simply pull up a mini app on WeChat, Baidu or Alipay and enter the keyword. The tech firms will give you the answer and why.

wechat garbage sorting

A WeChat mini program that lets users learn the category of cash

Alipay, Alibaba’s electronics payment affiliate, claims its garbage-sorting mini app added one million users in just three days. The lite app, which is available without download inside the e-wallet with one billion users, has so far indexed more than 4,000 types of rubbish. Its database is still growing, and soon it will save people from typing by using image recognition to classify trash when they snap a photo of it. Alibaba’s answer to Alexa Tmall Genie can already answer (in Chinese) the question “what kind of trash is a wet wipe?” and more.

If people are too busy or lazy to hit the collection schedule, well, startups are offering valet trash service at the doorstep. A third-party developer helped Alipay build a recycling mini app (“垃圾分类回收平台”) and is now collecting garbage from 8,000 apartment complexes across 11 cities. To date, two million people have sold recyclable material through its platform.

Ele.me, Alibaba’s food delivery arm, added trash pickup to its list of valet services its fleets offer on top of “apologize to the girlfriend” and dog walking.

Alibaba’s food delivery & local service platform https://t.co/Yh95Bt0DPG just rolled out a “throw out the trash” service for $2. The delivery guy can also “apologize to the girlfriend” on your behalf among other things #DigitalEconomyinChina $BABA pic.twitter.com/C2ey1ePDvJ

— Krystal Hu (@readkrystalhu) June 24, 2019

Besides helping households, companies are also building software to make property managers’ lives easier. Some residential complexes in Shanghai began using QR codes to trace the origin of garbage, state-owned media outlet Xinhua reported. Each household is asked to attach a unique QR code to their trash bags, which will be scanned for sources and classification when they arrive at the waste management station.

shanghai garbage

Workers at a waste management station in Shanghai scan codes on trash bags to check their source (Screenshot from Xinhua feature)

This way, regulators in the region know exactly which family has produced the trash — although the city’s current garbage regulations do not require real-name tracking — and those who correctly categorized receive a small reward of 0.1 yuan, or 1.45 cents, per day, according to another report (in Chinese) from Xinhua.

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This tech startup is trying to tackle waste in Africa

Kenya has a waste management problem, especially in the country’s capital of Nairobi. As of 2016, Nairobi was producing around 2,400 tons of waste every day but only 38 percent of that trash was collected and less than 10 percent was recycled. That resulted in the remaining 62 percent being left on illegal dumpsites or getting burned. Read More

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Santa Fe enlists Rubicon Global to curb waste and ramp up recycling

 Humans, especially Americans, are kind of slobs. We mess up the Earth by throwing out about 4.5 pounds of garbage per person on average every day. Two-thirds of that waste could be composted, but isn’t. And half of the rest of it could be recycled, according to research from the Duke Nicholas School of the Environment, corroborated by studies from the Global Footprint Network and… Read More

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