Your address will show here +12 34 56 78
Blog, Dataset Creation

A recent study released by development consulting firm Banyan Global sheds light on Microwork and Impact Sourcing highlighting the different sides of the industry by looking at what clients want out of service providers and how to ensure that workers are being offered steady work with future opportunity. Microwork is a series of small tasks which together constitute a larger project. Impact Sourcing, also known as socially responsible outsourcing, refers […]

[Research] Big Data Drives Boom For Microwork and Impact Sourcing

A recent study released by development consulting firm Banyan Global sheds light on Microwork and Impact Sourcing highlighting the different sides of the industry by looking at what clients want out of service providers and how to ensure that workers are being offered steady work with future opportunity.

Microwork is a series of small tasks which together constitute a larger project. Impact Sourcing, also known as socially responsible outsourcing, refers to the creation of employment for high potential but disadvantaged people in the services sector via contract work.

Key findings in the study include:

  • Microwork industry is expecting 5x growth by 2020.
  • Data science, algorithm-based IT approaches and technology advances have expanded the range of work performed by microwork service providers.
  • Microwork service providers are structured in three different models offering varied benefits and drawbacks.
  • Clients selecting outsourcing partners look to business factors such as cost, quality, and timeliness as central decision factors.
  • Impact sourcing initiatives must be well structured and well-managed to produce cost-effective, high-quality products on time.
  • Concerns around microwork include security, implementation complexity, and potentially low-quality products when workers are not sufficiently skilled or managed properly.

Big Data + Data Science Drives Boom for Microwork

In today’s fast-paced digital world, change is the only guarantee. Organizations are struggling to keep up with innovation, having to spend the majority of their budgets and human resources maintaining their current offerings. This creates a gap between current offering and innovation. Over time, this gap threatens to open up as lean startups jump ahead and the competitive landscape evolves.

Technology breakthroughs and innovations have opened new opportunities for business. Today, advancements are commonly driven by leveraging the ever-increasing abundance of available data. The need to remain as lean as possible while extracting insights and innovation from data is the key driver in the evolution and growth of microwork and impact sourcing. This increase in data work has given rise to the microwork industry, changing the type of work available from very basic data work to work that requires domain-specific skilling, including image and video annotation to power machine learning algorithms or UGC content moderation to enhance user safety and experience. According to the study, it is projected that the microwork industry will grow from a $400 million industry today to $25 billion by 2020.

To remain competitive, companies need to be using data to their advantage; to better target customers, to provide personalized insights, and to enhance the customer experience. While everyone has access to data, the challenge is in gaining useful insights. To do this, the data needs to be in a structured format. Algorithms that are used in artificial intelligence, machine learning and computer vision rely on accurate data. The most advanced digital companies are heavily powered by human data services in the background. Cleansing data is a crucial task that needs to be done with extremely high accuracy to minimize false outputs and increase accuracy. Structuring data typically requires highly repetitive tasks completed accurately. High-growth companies are looking outside of their human resource pool to complete data tasks while their core team remains focused on core business objectives.

Technology innovations, such as cloud computing, increased bandwidth, and expanded access to reliable internet, are fueling employment opportunity for people all over the world. As the microwork industry grows, so does the opportunity for individuals in developing countries to join the “digitized economy,” offering skilled employment where there previously wasn’t any stable options, increasing their purchasing power.

The type of work that microwork providers can handle varies greatly but is centered in dataset skills. The study highlights work case studies from Ancestry.comGetty Images, and eBay. As an example, Getty Images, the world’s largest provider of digital media content, processes over 40,000 still images per day. To increase search accuracy for their customers, they outsourced image categorization to microwork service providers, including iMerit. Adding high-quality metadata to each image enables customers to find what they are looking for, providing a better customer experience.

Different Types of Impact Sourcing Models

The study has classified microwork service providers in three different categories, each one varying in advantages and disadvantages to both the client and the workers.

The Micro Distribution Model















This model is commonly referred to as ‘crowdsourcing’ – a company creates a platform that acts as an intermediary between client and workers. This model is highly scalable and low cost due to the lack of infrastructure as workers are self-employed and dispersed (working from their home or local cafes). This structure also has the capability for broad impact as it’s accessible to anyone with reliable Internet and basic literacy and numeracy skills.

The micro distribution model can cause challenges for workers due to fluctuating demand for services. Because of the dispersed nature of the structure, there is less opportunity for skill development and can create quality control difficulties due to lack of direct management.

The Direct Model



In the Direct Model, service providers build and operate delivery centers and employ and train local workers to complete work in those centers. Services providers will usually have a United States-based headquarters with delivery centers in developing and emerging countries.

In this model, workers are offered education, up-skilling opportunities, and a management team to offer guidance. While this model represents the highest level of investment, fixed capacity, and operational complexity for the service provider due to infrastructure and training, according to the study, it also has the highest potential for performing high volumes of work at a high level of quality.

The Indirect Model



This model adds a layer to the direct model between the client and the workers in the form of delivery partner, service intermediaries, or subcontractors, who find contracts to bring to their partners. While this is a very scalable model, quality control can be very complex and is affected by all collaborating firms.

iMerit is an example of the Direct Model with a headquarters in California and delivery centers in India. Employees are offered stable employment with continuous on-the-job training and advancement opportunities enabling them to join the digitized economy. A stable work environment, skills and opportunity advancement, and a management team on site leads to below 3% attrition rates and projects that are completed with above 95% accuracy on time, and on budget.  Knowing that the team you partner with today is the team that will be here tomorrow creates a sense that the iMerit workforce is truly a part of the client’s workforce. This helps build valuable long-term client relationships, encourages investment in knowledge transfer and technology, and adds to the quality of work.

Microwork increases production, scalability, and lowers costs without risk

With direct and indirect models offering the skilling required to complete more advanced tasks, more and more companies are looking to outsource their data work saving them money through lower salaries for workers, lower training costs, and lower attrition rates. According to the study, impact sourcing can lower client costs by up to 40% and replace the need for staff augmentation, saving addition costs, as service providers take on the responsibility of acting as the employer, or that workers are hired as freelancers.

Not only does enlisting dataset service providers reduce costs, but it can also help clients scale their work at a reduced risk. According to the study, the “large-scale digitization of service production and the unbundling of service value chains have enabled firms to view individuals and locations as calculable, marginal and substitutable in the performance of this work.” As an example, companies who are launching a new product will utilize outsourced workforces to help manage increasing amounts of data and to refine their product before launch. The study mentions that Microsoft did this when testing the algorithms used in its search engine, Bing.

Challenges and Concerns

There are concerns or challenges that arise when hiring an outside team to complete important work. According to the study, clients interviewed are concerned about security, implementation complexity, and potentially low-quality output. To reduce these concerns, initiatives must be well structured and well-managed to produce cost-effective, high-quality products on time.

In the case of the Direct Model, teams are managed in delivery centers. This creates an opportunity for high security as data is not leaving the centers. Through project managers, upskilling, and low attrition rates, teams can take on more complex projects. Because management is right there with them, quality control is a key component, ensuring the client receives high-quality work.

While I have focused mainly on the client-related aspects and opportunities that microwork and impact sourcing provide, the study details the incredible opportunity that it offers marginalized individuals all over the world. For more information and to read the entire study, you can check it out here.

For more information on the on-demand data services iMerit provides, get in touch today!

0

Blog

In our previous blog post about working with external teams, we talked about the importance of knowledge transfer when creating, enhancing, and cleaning datasets. Take a look here. This week, we’re talking about communication. When we work on projects with co-workers, we do a great deal of communicating: meetings, calls, stand-ups, check-ins, you know the drill. When work with external teams – from consultants to BPOs to crowds – it’s […]

In our previous blog post about working with external teams, we talked about the importance of knowledge transfer when creating, enhancing, and cleaning datasets. Take a look here. This week, we’re talking about communication.

When we work on projects with co-workers, we do a great deal of communicating: meetings, calls, stand-ups, check-ins, you know the drill. When work with external teams – from consultants to BPOs to crowds – it’s important to remember that though there may be fewer in-house team members, communication is still key.

In practice, this first means establishing good knowledge transfer, as we talked about in our last segment. However, that one-way channel is not enough.

It’s important to create feedback channels from your external teams to in-house teams.

When working with a managed team – whether it’s a group of consultants or an iMerit team – this can be straightforward. Between email, phone calls, Slack, Skype – the list goes on – channels are established and it’s just a matter of making and sticking to a schedule.

When working with an anonymous crowd, however, you need to get creative.

The “team” you’re working with could be ever-shifting, making it hard (but not impossible) to gather unified feedback.

One method to try is adding a “task” in your process that asks for the workers’ feedback. You can gather feedback on the task structure, the task documentation, and see if there is anything you can change to make the task more straightforward for them, and more useful for you.

Encourage honesty, and then you can iterate your tasks based on the feedback you get. Over time, your tasks will be clearer and easier for the crowd to complete, ensuring even more accuracy for you!

What does this look like in reality?

Perhaps you have an online clothing store, and are entering new items into your retail site’s taxonomy. As you go through the data coming from your crowd, you notice that there is an item with markedly low inner-agreement rates. Different crowd members keep placing it in different categories, there is no agreement on where it should belong.

hoodie_blog_imgTake a look at it on the left.

Your crowd is baffled.

Some call it a “hoodie” – it does have a hood, after all – while others are placing it in the “sleeveless top” category. If they were sitting in-house, they could ask you which of these categories is more important to your categorization, or they could suggest placing it in two categories. But, they’re not in your office, so you need to anticipate their thoughts.

To avoid this confusion, design tasks in a way that makes it easy for workers to voice their thoughts.

Going forward, there are many interventions you could take:

  • Add a checkbox workers can tick to mark that they are “unsure of the category”
  • Include a free-text field that workers can fill in with any questions they have about the categorization of each particular item
  • Place a question at the end of the tasks asking your workers if they faced any confusion at an overall level
  • Require a final question where workers can offer suggestions for tasks or instructions

Get creative with the questions you ask your external teams, and remember they’re team members just like those you see in your office everyday!

Stay tuned for more tips on using external teams.

0

Blog

The path to the relevant, clean and complete dataset you need can be a long one, made up of many small, often time-consuming tasks. Maybe it’s tagging hand gestures in a video in order to build an algorithm training dataset. It could be […]

The Foundation to Creating Datasets with External Teams

The path to the relevant, clean and complete dataset you need can be a long one, made up of many small, often time-consuming tasks. Maybe it’s tagging hand gestures in a video in order to build an algorithm training dataset. It could be reading individual user comments to keep your site clean and relevant. Or perhaps it’s conducting complex web research on financial entities.

These tasks take time and focus away from other core tasks, and the option of passing them along to an external team can be quite appealing. However, using external teams – from consultants to crowds – is not straightforward. Communication can be time consuming, and results may not match what you needed. To address these challenges, we pulled together tips we’ve learned along the way of our data journeys.

The first tip? Document, document, document.

No matter how you look at it, your external teams are like new hires. They don’t have the company knowledge or familiarity you do. That means it’s best to do all you can to start them off with a good infusion of knowledge.

To ensure good knowledge hand-off, start with a process document. Chances are this isn’t the first time you have gathered or enhanced the particular dataset in question, so walk through the process as you’ve found it to be working best and document that. Make notes of what teams can expect to see as they create and/or enhance the dataset, and include step-wise instructions as appropriate. Don’t stop there, though! Remember, these are just like new team members. That means…

Adopt the persona of a complete newcomer and revisit your instructions.

Make sure there’s no insider jargon, preconceived notions or assumptions that might derail your external workforce. Remember, nothing is obvious. Double-check your language for clarity, and imagine how it would read to someone entirely unfamiliar with the process and the context.

If you can find common ways to break your instruction design, then you can make it more robust out of the gate.

To find bugs, and weak spots in our instruction design, we have found it incredibly useful to discuss edge-cases and outliers. It’s hard (perhaps impossible) to account for all possible variants of edge-cases, but it’s critical to include even a few. Talk through how your teams – or other external teams – have handled edge-cases and outliers in the past. Do your best to explain the logic and assumptions behind decisions made that perhaps fall outside of the typical cases. This insight into your internal processes and priorities is invaluable to your external teams, and will help them even more than discussion of “typical” cases.

For one ecommerce client, we were asked to develop a set of tasks that would help them spot marketplace listings of counterfeit items. Though some items were quite obviously counterfeit, not all were as easily identifiable.

pear_smartphone

The less-well-known Pear brand smartphone

In addition to the clearer cases, we were able to identify some trends that marked the more difficult edge cases of counterfeit products. These included things like suspiciously low prices, or account names that seemed to suggest something suspicious was afoot (names like **CHEEP**REPROS** might be a give-away). By incorporating these special cases into documentation, we were able to ensure quicker identification of tough-to-spot products.

tip for process documentation

DOWNLOAD TIP SHEET

Keep this tip sheet handy for next time you need to document your data process, and stay tuned for more tips on using external teams.

0

Blog

Last week, we introduced four of iMerit Metiabruz’s data experts. This week, we delve deeper into their stories, and get a glimpse of iMerit from their eyes. How did you first become interested in iMerit? Rukhsar: I would always notice how happy my cousin was after a shift working at iMerit, so I thought to myself, “Why don’t I give it a try?” Hearing about her experience with her friendly […]

Last week, we introduced four of iMerit Metiabruz’s data experts. This week, we delve deeper in to their stories, and get a glimpse of iMerit from their eyes.

How did you first become interested in iMerit?

Rukhsar: I would always notice how happy my cousin was after a shift working at iMerit, so I thought to myself, “Why don’t I give it a try?” Hearing about her experience with her friendly colleagues there got me really interested in joining iMerit. It seemed like a fantastic opportunity.

Arfana: I heard about so many different work centers, but when I heard about iMerit it sounded different. I learned that this organization is working for human development through the support of rural communities and their livelihoods, and it made me happy and very interested to work with iMerit.

Zaheda: There are lots of things that attracted me to working with iMerit, but the first of these would be my curiosity in learning about the IT sector and my desire to learn more about the professional world. I’ve always had a passion for technology and a desire to see myself as a more independent individual. Before joining iMerit I had spent my life as a student, but I had always wanted to have a profession of my own, one where I could see myself as an independent person. I’ve always loved learning about technology, and here at iMerit I learn about technology every day. I’ve added to my skill set, too. Now I’m a professional person and I have an identity that I can call my own.

How have you grown personally or professionally as an individual?

Mushtari: iMerit has given me the opportunity to really enhance myself. When I first joined, I had very little knowledge about computers and the IT world, but because of iMerit, I’ve had the platform to learn so many different things – networking security assembly, for example. It is in thanks to the iMerit community that I have had this opportunity to learn and grow as I have.

Rukhsar: Personally speaking, I was a very shy girl in my school days, but since joining iMerit I have developed the habit of interacting more with people. This has turned me from an introvert to an extrovert, and it has also brought immense confidence in me. Not only that – it’s also helped me to speak frequently in English. All these factors have definitely allowed me to grow as a person. Professionally speaking, after having observed my managers and fellow team leaders, I’ve noticed how hard they work and the way they speak and behave with others. I’ve tried very hard to embody similar leadership qualities that they have set as an example. This has helped me to get promoted as a Team Leader here at iMerit Metiabruz. It feels good to be recognized as a leader in this office.

What are some of the skills that you have learned while here at iMerit?

Arfana: I have learned so many things here at iMerit – it’s hard to put them all into words. I’ve been working with iMerit for around five years now, and in that time I’ve definitely developed and advanced my leadership skills. For example, I’ve learned how to motivate others, like the members of the team I lead. I’ve improved my communication skills and also learned how to learn from past failures and shortcomings. I have learned that leadership can play a large role in our career development.

Mushtari: I have learned so many things during my time here at iMerit: IT skills, management, and workplace etiquette, for example. I’ve also had the opportunity to improve my English communication skills here, too. All of these things relate to one another, so the skills I’ve

learned here get practiced again and again.

What is your favorite thing about working at iMerit?

Mushtari: My favorite thing about iMerit is that here we can learn and work

simultaneously. This is the only center in this area where girls can work; so many

girls love to join our office.

Arfana: My favorite thing is the Communication Training by Anita, the Annual Functions, and that we can learn and work simultaneously.

What would you tell someone who is interested in working with iMerit?

Rukhsar: I always talk about my office work environment to my relatives and friends. I tell them about how much I enjoy working in iMerit, as this is a center where mainly girls work. We work as a family together. iMerit gives a great opportunity to all educated girls of Metiabruz to work and earn a livelihood and become self-dependent. Not only that, several girls also help to run their family by working in this office. Lots of girls I’ve met in my community have been inspired by my experience here. After listening to my story, some have also joined iMerit.

What has been one of your most memorable experiences here at iMerit so far?

Mushtari: At the 2016 iMerit Picnic, my name was announced as the recipient of the Ownership Award. I was so shocked – I really can’t express my feelings in words now, thinking about that moment when Radha Didi (iMerit CEO, Radha Basu) presented me with the award. It was really one of the sweetest memories of my life.

Rukhsar: In the last iMerit Picnic in February, I sang a song in front of a huge, appreciative audience – it felt very good to do that. It also gave me a lot of confidence and courage to face similarly daunting challenges in the future.

Zaheda: In the beginning when I first joined, we were working a lot and faced many issues. We didn’t have very reliable internet then, but all of us were driven by our ambition. We had the curiosity to do this kind of work to the best of our ability, and we were also a symbol of women’s empowerment from our locality. All those people who thought that girls are not able to work in offices were proved wrong. We showed them that we have the power to do these things. Now, many people love to see their daughters working here in Metiabruz. Working with iMerit has been one of the most memorable experiences of my life.

0

Blog

iMerit is thrilled to announce a new partnership with CrowdFlower. In response to the growing need for secure, confidential data enrichment, iMerit and CrowdFlower will team up to provide clients with a secure platform and a secure workforce to tackle many data enhancement needs. Until now, data science teams needing huge human-curated datasets were faced with a tough trade-off: use scarce internal resources, which can be expensive and […]

iMerit is thrilled to announce a new partnership with CrowdFlower. In response to the growing need for secure, confidential data enrichment, iMerit and CrowdFlower will team up to provide clients with a secure platform and a secure workforce to tackle many data enhancement needs.

Until now, data science teams needing huge human-curated datasets were faced with a tough trade-off: use scarce internal resources, which can be expensive and come at a high cost, or use the external crowd, which may not always satisfy confidentiality needs. Now, this new partnership enables CrowdFlower customers to work with iMerit teams trained in data confidentiality standards and committed to non-disclosure, working in secure environments. Businesses will benefit from the speed and flexibility of the crowd, but can rest assured knowing that their secure information is in good hands.

[Read More]

0