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Build-a-Button (in Figma) Workshop, by FoF Irvine

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Join us for a LIVE event with Karen Rencurrel of Slate

Marlene Puffer has been named chief investment officer at AIMCo. (Courtesy AIMCo) Alberta Investment Management Corporation (AIMCo) has appointed Marlene Puffer as its chief investment officer, effective Jan. 30. Puffer is an accomplished investor and ...

PeopleSpace: Puffer joins AIMCo, Murray moves to Ontario Teachers

Dream Residential REIT has announced Brian Pauls will become CEO effective June 6, replacing Jane Gaven who will remain on the REIT's board of trustees. We also report other executive moves at Colliers, CLC, Oxford and more...

The People Space

PeopleSpace

peoplespace

How do people like us, who started with $0 in web3 over a few years make a small fortune? That is the question, and this article will give you the answers. My name is Splashy, and welcome to the 1%.” Almost every project will cook if you can enter the top 3 on the leaderboard. BACK STORY I bought my first piece of crypto in 2013 and sold it a few days later for 2x profit. That was my introduction to crypto, I didn’t understand it, but it was something that could catch on. My first taste of crypto money was exciting, I was hooked, I started researching crypto to understand it more, and I learned about altcoins, and their incredible potential to moon hard [do 100x plus]. Eventually, at the top around 1300, I bought plenty of Bitcoin Cash with money I couldn’t afford to lose. Bitcoin Cash never reached that all-time high again. Five years later, I sold BTC Cash at a loss. I lost interest in crypto for a while and decided to seek my fortune elsewhere. I got a job, worked hard at it, and saved up a bit, but quit cold turkey because I was losing my mind. The hours were bad, and we worked based on a roster so I couldn’t define my time or hang out with friends… While searching for an alternative to this lifestyle, I settled again on crypto and started learning how to trade, trading was fun and quite profitable for me, but the profit was little because I didn’t have much capital to trade with. If it’s so easy to make money trading, why the fuck am I working so hard for it? I set out to build my trading capital. ALPHA 1:- CAPITAL IS THE TRUTH To make decent money from anything, you need money to start with or plenty of time, you can’t escape this …call it the iron rule…you either spend money or time. In 2023, I went all in on crypto, trading, farming airdrops, NFT free mints, and degen trading. I tried every single area I heard about (still doing that). I made a decent amount of money and moved to a cheaper country to reduce my living expenses. I’m not there yet, but damn, I feel close. Enough of the backup story I know you’re dying to know how to make 100x from crypto and earn consistent income from crypto, but here it is, straight from my heart with no filters. BUILDING YOUR CAPITAL IN CRYPTO FROM 0$ Firstly, you need to pick a niche, airdrop farmer, investor, creator, free mint hunter, or degen trader, choose one. Secondly, understand your place in your niche, in this space everybody needs everybody. Projects need people, and they incentivize them by organizing airdrops. Understand your unique position and start where you are, some methods of making money are harder than others, but you can start from where you are right now. Stage 0: you have zero capital: start farming airdrops or free mints or get a mod job: focus mf, don’t dilly dally -> your goal here is to raise capital and move to stage 1. Stage 1: you have 10k capital: start trading full-time or content creation full-time, in my case, I do both. Stage 2: 500k+ plus, become a micro investor, keep trading, keep creating content, and add value to the community that made you and crypto at large. STAGE 0 to 1 If you’re at stage 0 looking for that 10k…it’s easy but, it’s going to take time. Find an airdrop or free mint that can give you a potential 100 USD, and do it 100 times. Alternatively, find an airdrop or free mint that can give you 1000 USD, and do it 10 times. Easy right? EASY AND HARD….because nobody fucking knows which airdrop is going to cook hard, and doing everything you see on your X (Twitter) timeline is a recipe for burnout. ALPHA 2:- RESIST THE URGE TO DO ALL Every airdrop cooks hard, but not for everybody, you want to participate in airdrops only when you can cook hard, getting to the top 100 in 2 airdrops campaigns is better than being top 10k in 10 airdrops. After starting, if you sense that you can’t make it to the top 100, ditch it asap, and keep searching for the one. When you are in the top 10 of any project, fade everything else and focus hard till you get your goal. I tried everything, at one point I was farming 170+ airdrops at once, my daily task alone across all accounts took the whole day, and when the projects I was farming released a new task It took me days to catch up… tough times. Doing everything just doesn’t work. I get a little 100 USD, some 300 USD, a few 1k, and plenty 10–50 USD… after farming for months…not good. Save yourself the trouble, and resist the urge to do all. Conclusion: I’m going to help you move from stage 0 to 1. Finding Alpha is a full-time job. Reading and understanding tokenomics and whitepaper is a skill newbies learn over time, before you learn to do your research (DYOR), I’ll help you with your homework. This is my promise to you, expect cooks and alpha from me, follow me on x @splashy_effort, send me a dm, and drop your thoughts below. Your’s in crypto, splashy🧩 SUMMARY:- steps to 100x find your edge [automation, writing, speaking, design, etc]
pick a hustle [FREE MINTS, TESTNET AIRDROPS, PLAY 2 AIRDROPS, etc.]
only pick projects where you can top the leaderboard
do 10x or 100x of the above projects Want more good stuff like this? Follow me on x @splashy_effort PS: I pinned this post on my x account to remind myself to work only on things where I have an edge, you should do the same. How do people like us, who started with $0 in web3 over a few years make a small fortune? That is the question, and this article will give you the answers. My name is Splashy, and welcome to the 1%.” Almost every project will cook if you can enter the top 3 on the leaderboard. BACK STORY BACK STORY I bought my first piece of crypto in 2013 and sold it a few days later for 2x profit. That was my introduction to crypto, I didn’t understand it, but it was something that could catch on. My first taste of crypto money was exciting, I was hooked, I started researching crypto to understand it more, and I learned about altcoins, and their incredible potential to moon hard [do 100x plus]. Eventually, at the top around 1300, I bought plenty of Bitcoin Cash with money I couldn’t afford to lose. Bitcoin Cash never reached that all-time high again. Five years later, I sold BTC Cash at a loss. I lost interest in crypto for a while and decided to seek my fortune elsewhere. I got a job, worked hard at it, and saved up a bit, but quit cold turkey because I was losing my mind. The hours were bad, and we worked based on a roster so I couldn’t define my time or hang out with friends… While searching for an alternative to this lifestyle, I settled again on crypto and started learning how to trade, trading was fun and quite profitable for me, but the profit was little because I didn’t have much capital to trade with. If it’s so easy to make money trading, why the fuck am I working so hard for it? I set out to build my trading capital. ALPHA 1:- CAPITAL IS THE TRUTH ALPHA 1:- CAPITAL IS THE TRUTH To make decent money from anything, you need money to start with or plenty of time, you can’t escape this …call it the iron rule…you either spend money or time. In 2023, I went all in on crypto, trading, farming airdrops, NFT free mints, and degen trading. I tried every single area I heard about (still doing that). I made a decent amount of money and moved to a cheaper country to reduce my living expenses. I’m not there yet, but damn, I feel close. Enough of the backup story I know you’re dying to know how to make 100x from crypto and earn consistent income from crypto, but here it is, straight from my heart with no filters. BUILDING YOUR CAPITAL IN CRYPTO FROM 0$ BUILDING YOUR CAPITAL IN CRYPTO FROM 0$ Firstly, you need to pick a niche, airdrop farmer, investor, creator, free mint hunter, or degen trader, choose one. Secondly, understand your place in your niche, in this space everybody needs everybody. Projects need people, and they incentivize them by organizing airdrops. Understand your unique position and start where you are, some methods of making money are harder than others, but you can start from where you are right now. Stage 0: you have zero capital: start farming airdrops or free mints or get a mod job: focus mf, don’t dilly dally -> your goal here is to raise capital and move to stage 1. Stage 1: you have 10k capital: start trading full-time or content creation full-time, in my case, I do both. Stage 2: 500k+ plus, become a micro investor, keep trading, keep creating content, and add value to the community that made you and crypto at large. STAGE 0 to 1 STAGE 0 to 1 If you’re at stage 0 looking for that 10k…it’s easy but, it’s going to take time. Find an airdrop or free mint that can give you a potential 100 USD, and do it 100 times. Alternatively, find an airdrop or free mint that can give you 1000 USD, and do it 10 times. Easy right? EASY AND HARD….because nobody fucking knows which airdrop is going to cook hard, and doing everything you see on your X (Twitter) timeline is a recipe for burnout. ALPHA 2:- RESIST THE URGE TO DO ALL ALPHA 2:- RESIST THE URGE TO DO ALL Every airdrop cooks hard, but not for everybody, you want to participate in airdrops only when you can cook hard, getting to the top 100 in 2 airdrops campaigns is better than being top 10k in 10 airdrops. After starting, if you sense that you can’t make it to the top 100, ditch it asap, and keep searching for the one. When you are in the top 10 of any project, fade everything else and focus hard till you get your goal. I tried everything, at one point I was farming 170+ airdrops at once, my daily task alone across all accounts took the whole day, and when the projects I was farming released a new task It took me days to catch up… tough times. Doing everything just doesn’t work. I get a little 100 USD, some 300 USD, a few 1k, and plenty 10–50 USD… after farming for months…not good. Save yourself the trouble, and resist the urge to do all. Conclusion: I’m going to help you move from stage 0 to 1. Finding Alpha is a full-time job. Reading and understanding tokenomics and whitepaper is a skill newbies learn over time, before you learn to do your research (DYOR), I’ll help you with your homework. This is my promise to you, expect cooks and alpha from me, follow me on x @splashy_effort, send me a dm, and drop your thoughts below. Your’s in crypto, splashy🧩 SUMMARY:- steps to 100x SUMMARY:- find your edge [automation, writing, speaking, design, etc] pick a hustle [FREE MINTS, TESTNET AIRDROPS, PLAY 2 AIRDROPS, etc.] only pick projects where you can top the leaderboard do 10x or 100x of the above projects find your edge [automation, writing, speaking, design, etc] pick a hustle [FREE MINTS, TESTNET AIRDROPS, PLAY 2 AIRDROPS, etc.] only pick projects where you can top the leaderboard do 10x or 100x of the above projects Want more good stuff like this? Follow me on x @splashy_effort PS: I pinned this post on my x account to remind myself to work only on things where I have an edge, you should do the same.

100x Secrets for Crypto Newbies: How I Went From 0$ to 100k

This is the second part of a series of articles on how GenAI is revolutionizing Rev-Ops functions in enterprise technology businesses. In the first part, we saw some broad applications of Gen AI in Rev Ops. In this article, we will explore how GenAI use cases are being developed and deployed in the first of the  four core Rev Ops pillars - business strategy and planning. A little bit about myself : I am a GTM veteran & Sr. Director of RevOps at Cisco. Business Planning - what is it, how is it done, and what is changing? Business Planning is the primary cross-functional performance in the corporate ballroom. Lead actors from Product, Engineering, Finance and Sales participate in this song-and-dance routine with Rev Ops called upon to choreograph the arrangement as tightly as possible. The perennial challenge in these situations is that everybody performs to their own sheets of music with not-so pleasant outcomes for the company or stakeholders. A single source of truth for business planning has historically been the holy grail of corp-strategy and execution if ever there was one. Enter language models with context awareness and generative capabilities. Generative AI enhances data-driven decision-making in business planning by providing advanced tools and capabilities that improve the efficiency, accuracy, and depth of insights. Here are some ways it contributes to this process: Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language. By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making.


Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights. This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making.


Dynamic Scenario Planning and Modeling: Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation.


Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. In the following articles, we will continue these discussions across Marketing, Sales, and Customer Success. This is the second part of a series of articles on how GenAI is revolutionizing Rev-Ops functions in enterprise technology businesses. In the first part , we saw some broad applications of Gen AI in Rev Ops. In this article, we will explore how GenAI use cases are being developed and deployed in the first of the  four core Rev Ops pillars - business strategy and planning. In the first part In the first part A little bit about myself : I am a GTM veteran & Sr. Director of RevOps at Cisco. Business Planning - what is it, how is it done, and what is changing? Business Planning - what is it, how is it done, and what is changing? Business Planning is the primary cross-functional performance in the corporate ballroom. Lead actors from Product, Engineering, Finance and Sales participate in this song-and-dance routine with Rev Ops called upon to choreograph the arrangement as tightly as possible. The perennial challenge in these situations is that everybody performs to their own sheets of music with not-so pleasant outcomes for the company or stakeholders. A single source of truth for business planning has historically been the holy grail of corp-strategy and execution if ever there was one. Enter language models with context awareness and generative capabilities. not-so pleasant outcomes for the company or stakeholders. not-so pleasant outcomes for the company or stakeholders. Generative AI enhances data-driven decision-making in business planning by providing advanced tools and capabilities that improve the efficiency, accuracy, and depth of insights. Here are some ways it contributes to this process: Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language. By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making. Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights. This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making. Dynamic Scenario Planning and Modeling: Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation. Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language. By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making. Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language . By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making. average user the ability to query and understand data in natural language average user the ability to query and understand data in natural language Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights. This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making. Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights . This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making. real-time, actionable insights real-time, actionable insights Dynamic Scenario Planning and Modeling: Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation. Dynamic Scenario Planning and Modeling : Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation. Dynamic Scenario Planning and Modeling Dynamic Scenario Planning and Modeling Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. In the following articles, we will continue these discussions across Marketing, Sales, and Customer Success.

Reimagining Rev-Ops with Gen AI: Always-On Strategy and Planning 

The Sun and the Ether: Why Ethereum Has Already Won

সূর্য এবং ইথার: কেন ইথেরিয়াম ইতিমধ্যে জিতেছে

Die Sonne und der Äther: Warum Ethereum bereits gewonnen hat

El sol y el éter: por qué Ethereum ya ganó

Le soleil et l'éther : pourquoi Ethereum a déjà gagné

सूर्य और ईथर: क्यों एथेरियम पहले ही जीत चुका है

太陽とエーテル：イーサリアムがすでに勝利した理由

태양과 에테르: 이더리움이 이미 승리한 이유

O Sol e o Éter: Por que Ethereum já venceu

Солнце и эфир: почему Ethereum уже победил

Güneş ve Eter: Ethereum Neden Zaten Kazandı?

Mặt trời và Ether: Tại sao Ethereum đã chiến thắng

太阳和以太：为什么以太坊已经获胜

MODERN PROPHECIES

107 Stories To Learn About Search Engine

No strategy can help an organization thrive if the people in the organization aren’t resilient to change and chaos. Setbacks and challenging situations - a missed deadline, a lost deal, a failed project, a bad strategy - are everyday affairs at work, and only those who learn to get past them can grow professionally and personally. A resilient mindset is essential to bounce back from challenging situations at work. At an individual level, different people have different expectations and different levels of resilience to deal with challenges and setbacks. While one person may be devastated when their idea doesn’t work out, another may simply move on to try a new strategy. A lost deal can make someone wallow in their misery while another person in the same situation may be up and about already trying to get a new client. Unlike popular belief, people aren’t born to be this way. It isn’t part of their DNA. It’s not an inborn quality that only a few possess. Anyone can learn to be resilient. “Fail fast, be agile, be resilient.” We have all heard this at work. But simply telling people to be resilient doesn’t work. Irrespective of how much we tell our teams to move past failures and learn from mistakes, we know that it isn’t easy to accept a failure. The expectation to do well at work makes people believe that failure isn’t an option. Putting in the effort and not achieving the outcome is always disappointing. Fear, anger and confusion can cause people to feel helpless after a setback and paralyze them from moving forward. The tendency to assign blame to an external factor beyond their control can also leave them feeling hopeless. But there’s a huge difference between feelings of disappointment and letting those emotions turn into feelings of devastation. Being resilient is all about knowing that difference. It’s knowing that failure is a part of life and not an excuse to stop trying, avoid risk or ignore challenging circumstances. It’s not displaying toxic positivity, but rather having a sense of realistic optimism. It’s staying flexible and adapting to the change around us and not being rigid about our beliefs and expectations. Resilience is building a sense of coherence, both physically and mentally by observing, adjusting and adapting to the world around us. Victor Frankl, a neurologist and a holocaust survivor, writes in Man’s Search for Meaning: When we are no longer able to change a situation, we are challenged to change ourselves. In other words, we can’t control our circumstances, but we can control our attitude to those circumstances. Resilience is all about that attitude. 4 methods to help your team fail fast and be resilient at work By adopting these 4 techniques, you can improve your team’s ability to succeed in difficult situations by bouncing back from failure: 1. Don’t try to flip the switch. Resilience = Ability to deal with emotions I was part of a five-member team tasked with the project to reduce the processing time of one of our products by more than 80%. Large processing time was impacting business and making our clients super unhappy about our product. We were thrilled as a team to take on this challenge. After months of working on the product and getting it to close to our initial target, we hit a major roadblock. We learnt that one of our core assumptions about deploying the solution was faulty and our original strategy may not work. It was a major disappointment for the entire team. We had already spent so much time trying to make it work. This was on a late Tuesday evening. The next morning when we told our manager about the problem, he simply said “Let’s move on. What’s the next step?” What’s the next step? Aren’t you even slightly disappointed about all the effort that has been wasted? Do you even care that we put in so much time and energy in trying to make it work? Even with right intentions at heart, his message didn’t land very well with the entire team. He wanted to move forward with another solution instead of wasting time in discussing what clearly doesn’t work. And I don’t blame him for thinking forward. His only mistake was expecting people to flip from one emotional state to another in a moment, just like that. When dealing with failures and setbacks, building resilience isn’t about ignoring emotions and trying to be rational. It requires accepting those emotions while staying rational. It requires giving people space and time to process, reconcile and come to terms with what just happened. An essential step to “move on” and build resilience is to process and analyze the failure or the mistake and use that as an opportunity to do better next time. As a manager, you may think that talking about failure will make your team feel worse about their situation, but it has quite an opposite effect. To build resilience as a team, give your team time to deal with their failure and then help them see past it and into the future. Don’t try to do both at the same time. Give them time to ponder over their mistakes, then regroup to discuss the changes you can make as a team or the practices you can adopt to avoid them in the future. Summary: 2. Don't try to motivate them. Resilience = Learning to face reality A mistake I made later as a manager myself was trying to save my people from “feeling bad” about their failures. I would try to shift their mood by toning down the failure or the mistake. I thought it would be a good motivation technique to keep them productive. But I was wrong. Don’t say things like these - “No one could have guessed the market shift. We are doing better than so many others who couldn’t survive the change.” “Losing this client is no big deal. We weren’t going to generate a lot of revenue through them.” Being resilient requires raising the bar and emerging stronger, not lowering down your expectations. By comparing yourself to those who are doing worse off than you are, you don’t convey a strong desire to work hard and rise above the challenge. Building resilience requires facing the uncomfortable truth. It requires letting your team face the reality of their situation. Don’t sugar coat the message. Don’t try to avoid disappointments. Don’t try to be nice or kind. Describe the situation and share feedback as they need to hear. Convey the importance of achieving outcomes while not tying those outcomes to their identity. You can be caring and still hold them accountable at the same time. Most importantly, make them see that they are in control of their situation and then help them identify the next steps to move forward. When you learn to let go of the details you can’t control, the amount of time and energy you’ll be able to devote to the things you can control will give you the ability to accomplish incredible feats - Amy Morin You don’t need to increase your team’s motivation when they fail. Build their resilience by helping them feel in control of their situation. Make them believe that come what may, they will have the courage and strength to get past it and come out on the other side stronger than they started. Summary: 3. Inculcate a fail fast mindset. Resilience = Feeling comfortable with taking bigger risks Small wins and failures are much better than massive setbacks and large accomplishments. Yes, big project victories are celebrated much more, but they are really a gamble. When you go all in, the outcome can go either way. Irrespective of whether you succeed or fail, there’s less opportunity to learn from the process. However, when you encourage your team to take small steps in the direction of their goals, they don’t lose sight of the big picture, and yet they get both a sense of progress and an opportunity to tweak as they move along. They not only learn what works, but also what does not work. Once your team feels comfortable with small steps, they will be much more willing to take bigger risks because they now have a recipe to bounce back from difficult situations. They know that at any point in time they can go back and rework on a specific step without feeling overwhelmed by the overall scope of the project. The ability to break down a large problem into a series of tiny experiments encourages a fail-fast mentality. It’s a great strategy to build resilience in your team. Summary: 4. Shift from problem to solution. Resilience = Forward thinking with a solution mindset All the things that individuals fall prey to — misattribution and rationalization — are compounded on a team and add exponential complexity to the process - Ben Dattner When a group fails, some people may be more hurt by the failure than others as they may have a different stake in the project. Depending on how they view the situation, some level of finger pointing and blame games is common in such situations. Spending time regretting past decisions or identifying who to blame can only lead to inaction. As a manager, it’s your responsibility to help the entire team take responsibility for the outcome and move on. It’s important to know the cause, but far more important is to determine what to do with that information. How to react and act once you know better. Ask these questions to help your team problem solve together: What do you think happened? What can we learn from this situation? What would you do differently next time? As a team, what was your biggest learning from the project? Building resilience requires shifting from blame games to shouldering responsibility as a group. When team members engage in constructive problem solving with a focus on the future, they emerge stronger as a team. Summary: Summary Resilience isn’t about not feeling disappointed about your failures. It’s about not letting those emotions prevent you from moving forward. Building resilience is essential to deal with challenges and setbacks at work. It’s a key component in professional growth. As a manager, you can help your team use failures as learning opportunities thereby making them more resilient to setbacks and be more willing to embrace difficult situations. When your team is feeling emotional about something that didn’t go necessarily well, acknowledge their emotions first. You can try to fix the situation later. Building resilience isn’t about ignoring feelings. Don’t try to be nice or say things to make them feel good. State facts. Share feedback as they need to hear. Building resilience requires facing reality, not denying it. People need to feel in control of their situation. Encourage a fail fast mindset by helping your team see the value in taking small steps and using that to build the courage to take bigger risks. Don’t let finger pointing and blame games get in the way of finding solutions. Hold your entire team responsible for failures and help them find solutions to move forward as a group. Previously published here .

The Fail Fast Mindset: How to Help Your Team Fail and Be Resilient at Work

Meet the Winners of Startups in North and Central America

How To Create An Effective Instagram Story Ad

Computer algorithms that scan everything from terror watch lists to eviction records spit out flawed tenant screening reports. And almost nobody is watching Burglary and domestic assault in Minnesota. Selling meth and jumping bail in Kentucky. Driving without insurance in Arkansas. Disorderly conduct. Theft. Lying to a police officer. Unspecified “crimes.” Too many narcotics charges to count. Samantha Johnson said she's been wrongly labeled a criminal by tenant screening companies. ThomasPatterson That’s what the landlord for an apartment in St. Helens, Ore., saw when he ran a background check for Samantha Johnson, a prospective tenant, in 2018. But none of the charges were hers. The growing data economy and the since the 2008 financial crisis have fueled a rapid expansion of the tenant screening industry, . The companies produce cheap and fast—but not necessarily accurate—reports for across the country. rise of American rentership now valued at $1 billion an estimated nine out of 10 landlords The automated background check for Johnson cast a wide net, looking for negative information from criminal databases even in states where she had never lived and pulling in records for women whose middle names, races, and dates of birth didn’t match her own. It combined criminal records from five other women: four Samantha Johnsons, and a woman who had used the name as an alias—even though the screening report said she was an “active inmate” in a Kentucky jail at the time. “You can totally tell we’re not the same person at all,” said Johnson, who eventually got the apartment after she convinced the landlord she wasn’t a criminal. It was not the first time she had been the victim of incorrect automated screening reports. It wouldn’t be the last, either. “You Just Have to Give a Crap” The reports can be created in a few seconds, using searches based on partial names or incomplete dates of birth. Tenants generally have no choice but to submit to the screenings and typically pay an application fee for the privilege. Automated reports are usually delivered to landlords without a human ever glancing at the results to see if they contain obvious mistakes, according to court records and interviews. A review of hundreds of federal lawsuits filed against screening companies over the past 10 years shows how hasty, sloppy matches can lead to reports that wrongly label people deadbeats, criminals or sex offenders. Among those who say they were wrongly maligned: Davone Jackson, who was denied low-income housing in Tennessee after the screening company RealPage reported that he had twice been convicted of trafficking in heroin in Kentucky and was on Wisconsin’s sex offender registry. In fact, those records belonged to an Eric Jackson and a James Jackson. After the denial, Davone Jackson said, he and his 9-year-old daughter were forced to live in a small motel room for nearly a year. Glenn Patrick Thompson Sr. and Glenn Patrick Thompson Jr., who said they had been left homeless near Seattle after a tenant screening company called On-Site, which is now part of RealPage, told two different landlords that the father and son had been previously evicted. In fact, the eviction was for a Patricia Thompson, who was not related to them. William Hall Jr., who lost out on a duplex in his small town in Georgia after TransUnion Rental Screening Solutions said he had sexually abused a minor. The criminal record belonged to a William Hall who was 30 years older and possibly dead. Hall said the landlord had stopped returning his telephone calls after receiving the incorrect report. Hall’s suit is pending; the others were settled for undisclosed sums. The screening process happens so quickly and the competition for apartments can be so fierce that prospective renters don’t always know why they were turned down, much less whether an incorrect background report was the cause. Some screening companies don’t even provide the underlying records to landlords, instead producing a color-coded “risk” score or a thumbs-up or thumbs-down lease recommendation. An example of a screening report that makes a judgment—in this case, a recommendation to reject the applicant, who sued the background company claiming the report was incorrect.Source: U.S. District Courts, Texas Western District, case 5:14-CV-01072 Screening company employees have stated in lawsuits that they err on the side of including any possible match, rather than excluding possible errors. The owner of one screening company criticized his industry, saying his peers can do better. “We can figure out how to match a record,” said Matt Visser, chief executive of Victig Screening Solutions, whose Utah company sells 10,000 to 20,000 tenant and employment screening reports a month. He said his company verifies negative findings. “It requires a human element.” “When we are performing any of these reports, it is a fairly monumental moment in someone’s life,” he added. “You just have to give a crap.” Large background firms, including RealPage, CoreLogic, TransUnion, and RentGrow, declined interview requests for this article. They referred specific questions to a trade group, the Consumer Data Industry Association. Noting the millions of tenant background reports produced each year, the group denied that any systemic problems existed and accused consumer lawyers of being myopic. “If I sat in a cardiologist’s office all day, all I would see is people with heart problems,” said Eric Ellman, the association’s senior vice president for public policy and legal affairs. He acknowledged that it hadn’t developed any standards for screening accuracy but said the companies had their own policies. In responses to lawsuits, tenant screening companies say renters dispute fewer than 1 percent of reports. But it’s impossible to know the actual error rate because tenants may not always know to complain. of landlords say they run background checks on all applicants 90% Source: TransUnion survey With about half of the nation’s 43 million rentals , even an error rate of 1 percent could upend the lives of hundreds of thousands of people. turning over every year Regulators have taken action against a few companies for slipshod tenant screenings; the Fair Credit Reporting Act requires background screeners to “follow reasonable procedures to assure maximum possible accuracy.” But rejected tenants continue to complain about the same careless practices by companies that regulators had called out, interviews and federal lawsuits show. Johnson has lost count of the times she has been turned down for housing or work because of incorrect background reports. Since 2016, she has sued six tenant screening companies for incorrect reports. All of them have settled. When she moved out of the apartment in St. Helens and applied to rent a house, the background report was 112 pages long. By then Johnson knew the drill: Find out where the report came from, call the screening company, fax in a copy of her ID, and start the dispute process. “I’ve tried to figure out if there’s something I can do, to stop that from happening,” she said. “But I don’t think that there really is, because there’s just so many background companies out there—and they’re not doing their jobs.” Lax Rules and Wild Cards Tenant screening was once confined to a simple credit check with the three major credit bureaus and a few phone calls to references, but it was revolutionized by the advent of cheap or even free, easily available electronic court records. These include criminal records from across the country, sex-offender registries, terrorism watch lists, and housing court records. Easy access to the troves of data has also made it possible for anyone with a computer to become a background screener: About 2,000 companies offer the service, but . Tenant screeners don’t have to register with any government agency. that’s only an estimate People can complain about faulty background reports to the Federal Trade Commission or the Consumer Financial Protection Bureau—or sue. But regulators have not limited tenant screening as much as other kinds of background checks. Regulators forced credit bureaus to follow standards for matching records to a person, and the kinds of records the bureaus can legally report are limited. Rules for employment screening, which some of the tenant screening firms provide, require employers to share the negative report with a rejected applicant. None of those restrictions applies to tenant screening. Federal law requires landlords only to tell tenants if they were turned down because of a negative report and who produced it. Under the Fair Credit Reporting Act, screening companies have 30 days to respond to tenants’ requests for corrections. By then, a landlord may have given the apartment away. “It’s just crazy that you can’t get immediate results,” said Andrew Guzzo, a consumer lawyer who has filed more than 100 federal lawsuits against background screeners and other consumer reporting agencies. “There’s not many worse imaginable consumer-financial-services-related impacts that you could have, more than an inaccurate tenant screening that costs you the ability to rent an apartment.” Tenants can’t get ahead of the problem by checking their background reports in advance because too many companies provide the service. “You can’t just go to one place and request your free annual report,” said Ariel Nelson, author of a 52-page National Consumer Law Center on screening errors. report A handful of cities have begun to regulate tenant screening by limiting a landlord’s ability to reject an applicant for old criminal convictions or evictions. Courts have also begun to take notice; a panel of federal judges recently consolidated seven lawsuits about errors in TransUnion’s tenant screening reports. Screening companies put the onus for accuracy on landlords, telling them right in the reports that they should double-check them. Steven Schachtman, a longtime Minneapolis landlord and property manager who oversees about 10,000 rentals and uses screening firms, said it’s difficult for a landlord to check the reports to ensure they matched their applicants. “That is why we are hiring them,” he said. “I assume they have matched everything up.” One CoreLogic employee said during a deposition for a federal lawsuit that she considered a background report “accurate” if it correctly reported what was in public records. A common method that screening companies use to increase hits, court records show, is a so-called wild-card search, which gathers different names that start with the same few letters. Terrence Enright’s experience, described in his federal lawsuit against National Tenant Network, shows how it works. When he applied for an apartment in Chicago in 2014, the company searched for and . But the company also searched for misspelled versions, including *, and found a match: an eviction for a Teri Enwright in California, one of what Enright said were three evictions mistakenly attributed to him, which resulted in his being denied the apartment. His lawsuit was settled out of court. Enright, Ter* Terrence, Enr* Enwright, Ter Screening companies could use more careful methods to reduce incorrect reports, such as excluding eviction records for addresses that don’t appear on a person’s credit report. Or reporting only records that match full names and other data, such as complete dates of birth. But they often don’t, tenants and consumer attorneys say, and the errors can have an outsize effect on people with common names—particularly members of minority groups, which . For example, more than 12 million Latinos nationwide share just 26 surnames, according to the census. tend to have fewer unique last names Marco Fernandez is suing RentGrow, another screening firm, after it included information in his report about another person, Mario Fernandez Santana. Fernandez lives in Maryland, works for an elite military cybercommand strike force and has a top-secret security clearance. The other man is on a federal watch list for suspected terrorists or drug traffickers, lives in Mexico, and has a different date of birth, according to the lawsuit. “These matching algorithms treat Hispanic names just like a mix-and-match,” said Fernandez’s attorney, E. Michelle Drake. RentGrow declined to explain why the company included the other man’s record in Fernandez’s report, but said in a statement that it had “promptly resolved all concerns in his favor.” Fernandez was able to get into the apartment he wanted. While disputing the report, however, Fernandez said he discovered that RentGrow had incorrectly reported the same federal watch list information to a landlord four years earlier, according to the lawsuit. He said he was not informed at the time. Hector Hernandez took CoreLogic to court after the company mixed him up with an accused drug smuggler, Hector Hernandez-Garcia, causing him, his wife and their newborn son to be temporarily homeless in the Washington, D.C., suburbs. “I kept telling them: ‘You got the wrong guy. I’m telling you, that’s not me,’” Mr. Hernandez, who works for a pest control company, said in an interview. CoreLogic settled the lawsuit. In a deposition for another federal lawsuit, a CoreLogic employee said independently verifying reports like these before sending them out “would be an overwhelming task.” It’s certainly more expensive: Court filings in a federal lawsuit show that RealPage pays one data broker 22 cents for each criminal record by buying data in bulk. The company typically charges landlords $12 per report. If there’s a dispute, the data broker would charge RealPage $7 to hand-check a record, according to the contract, shrinking RealPage’s profits—but not eliminating them. That lawsuit claims RealPage produced 11,000 inaccurate renter background reports between 2014 and 2019 using “abbreviated” criminal records, which are cheaper than a full record check, bought from an affiliate of . The records don’t include details of the resolution or complete dates of birth so are more likely to lead to incorrect reports. Backgroundchecks.com In a statement, RealPage said that “the screening that gave rise to this case occurred years ago” and that the company “has long since made changes to its criminal matching logic that would prevent this record from returning for the plaintiff in that case.” It would not elaborate on those changes. Federal regulators have fined both RealPage and Backgroundchecks.com. Backgroundchecks.com and an affiliated company were fined by the Consumer Financial Protection Bureau in 2015 over employment screenings. Among other things, the had failed to look for patterns in customer disputes that would identify root causes of inaccuracies, such as court jurisdictions with unreliable data, error-prone procedures, or employees who are particularly sloppy. agency said the company In 2018, the Federal Trade Commission for using wild-card searches; the company did not have to admit wrongdoing. The company brings in about $48 million annually from tenant background screenings, according to court filings. fined RealPage $3 million Despite the federal action, RealPage continues to employ a name-matching program that tolerates a significant amount of imprecision, according to federal lawsuits. For instance, according to a lawsuit by Leon Howard, RealPage included criminal records for a Lonnie Howard and eviction records for a Linnea Howard in his background report when he applied for a rental in Georgia in 2019. Lonnie Howard’s date of birth was different than Leon Howard’s, and the report included a photo of the offender, according to the lawsuit, which RealPage settled for an undisclosed sum. Still Waiting Most hurt are people living on the edge, especially those who made it to the top of long wait lists for a housing voucher or a public housing unit only to lose out because of faulty background checks. Sandra Smith was denied public housing because a tenant screening report pulled in a different Sandra Smith's eviction. Jon M. Fletcher Sandra Smith waited more than a year for a spot in public housing in her hometown, Jacksonville, Fla. After a divorce, she had been staying with friends and her mother. Unemployed while recovering from health problems, Smith was relieved she’d finally be able to move back out of her teenage bedroom. “I’m 55,” she said. “Having my own space is something I haven’t had in a long time, and I felt like I was ready for that.” But the housing authority turned her down after a background check reported a 2013 eviction for a different Sandra Smith. “Everything was a runaround,” she said. “No one had any more anything to show me—why they were so convinced that this was me.” Agency officials said she had been denied because of the screening, which is their policy. “It would’ve taken them two to three minutes to investigate this,” said Adam Thoresen, a Jacksonville Area Legal Aid lawyer whom Smith turned to for help. The signature on the lease agreement, which was attached to the online eviction records, wasn’t the same as his client’s, he said. The lease listed multiple children—but his client has only one child, an adult in his 30s, and the names didn’t match. “This is really simple stuff,” Thoresen said. It took Smith a year and a half to get her denial overturned. She is still dealing with the paperwork and hasn’t gotten an apartment. Credits Originally published as " " with the Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license. Access Denied: Faulty Automated Background Checks Freeze Out Renters

How Automated Background Checks Can Freeze Out the Wrong Renters

Hi there! My name is , I’m a Product Manager. In this essay of the series I will share with you . Previous parts of the series you can find here: , . Vitalii Berdichevskyi 2020 HR Tech trends research Part 1 Part 2 What you will find in the essay: HR Tech trends Hypothesis about future of distributed work after COVID-19 A collection of handpicked links I used in the research HR Tech trends 1. Specialization For example, Job boards (marketplaces) - despite the existence of “whales” like LinkedIn, Indeed, Careerbuilder, and Monster, there is a growing industry of niche Job boards that focus on job types, geos, skills, and industries. 2. Distributed work The number of employees who work remotely in the USA (remotely = work from home more than 2 days a week) is 4.7 million people or 3.6% of the total number of employees (Source: ) Flex jobs REmote job statistics The hypothesis is that after COVID-19, the number of distributed workforces will grow. The longer employees work remotely, the more a habit is developed, the more of them will remain to work remotely after quarantine. Figures confirming hypotheses: 42% of remote workers plan to work remotely more often than they currently do over the next 5 years. 80% of employees want to work from home at least part of the time (Source: ) OWLLabs State of Remote Work 2019 The growth forecast for employees working more than 2 days a week outside the office after the end of the information noise around Coronovirus is 25-30% of the total number of working people in the USA (39-46 million people) in the next 2 years (source: ) Global Workplace Analytics 56% of the workforce in the United States has work that is compatible (at least partially) with remote work Gallup data show that the percentage of workers who worked remotely for some time in 2016 was 43% (4% more than in 2012) Reduced fear among supervisors of remote employees. One reason is that managers themselves work remotely. Research data says that 56% of companies already allow remote work (16% completely remotely, 40% hybrid; (source: ) OWLLabs: Global State of remote work 2018 Unemployment continues to reach generational lows with every Jobs Report from the U.S. Department of Labor, and from every international reporting agency. So offering employees hybrid or completely remote job could help employers to attract talents The ability of enterprises to reduce costs by reducing the cost of offices and the transfer of employees to remote work. The survey data say that more than a third of workers are ready to reduce wages by up to 5% in exchange for the opportunity to work remotely for at least some time; a quarter is ready to cut wages by 10%; 20% ready for even greater reduction in return for schedule flexibility (Source: ) OWLLabs State of Remote Work 2019 3. Conversational HR technology Technologies like chatbots and messaging interfaces have led to rudimentary process improvements like automating repetitive and administrative tasks. The result is a creep in the number of applications used to interface with employees. These technologies will tie into core HR platforms, reducing the burden of repetitive employee relations transactions and streamlining data collection and analytics 4. Running into skills-based everything With global unemployment continuously setting new record-lows, the cost of replacing existing talent is far greater than "re-skilling" them. Retention has always been an action-driver for HR, but when a visible employer like Amazon commits to retrain a third of its workforce with an investment of approximately USD $700 Million, CEOs everywhere take note. Taking inventory of a company’s existing skills, mapping that to the jobs internally, then matching based on an algorithm, sprinkling in some machine learning or AI… factoring in data from a workforce planning initiative – using the same data to then look at candidates externally. Integration: demonstrable integrations to the internal systems that feed the matching engines AND the talent management processes and systems in place that guide the employee on their newly defined path. Learning: Matching without learning is a direction without a GPS. If we're going to point the employee in a direction based on their interest, skills, cognitive abilities, and more we need to connect the employee into the learning path to reach the destination. In this case we mean the "royal" learning - skills and compliance certification, casual learning, micro-learning, mentor-based learning, self-learning, external learning. All of whatever is available, via integration or natively. 5. Job boards and marketplaces which add bigger value Temp/Contract to Hire Model: as work is becoming more distributed and more contingent, job board marketplaces have the ability to offer projects that lead to full time employment. There's an emerging opportunity  for employers to offer project work to universities, community colleges, skills certification programs, veteran-focused jobs initiatives, state government run job training programs, second chance career  organizations, and more. Certified Talent:  Skills can be tested and cognitive abilities can be assessed with validity.  Backgrounds can be checked. Certifications can be validated. Initial screening can be completed. All before the candidate is presented to the employer, or at any point along the way. Marketplaces with the right resources and  tech can begin to look like automated  recruitment process outsourcing (RPO) firms in the near future, delivering a better candidate experience with potentially one process for multiple employers, and a more turnkey solution for employers. A collection of handpicked links I used in the research Below is the link to handpicked resources I have used in Google Sheet format. What’s inside: Articles Industry reports List of top HR tech influencers and many more. To use filters you can easily make a copy of the file and save it to your Google Drive. A collection of handpicked resources Summing it up Specialization - even though there are alot of wales in each subcategory there are still a lot of room for niche players COVID19 may boost the total number of working people in the USA remotely to (39-46 million people) in the next 2 years Skill based solutions requires integration and learning Job boards-marketplaces can begin to look like automated recruitment process outsourcing firms in the nearest future P.S. This essay was previously published at . If you have any questions about the research or are in love with creating products - please feel free to ping me on or . Lampovoeit.space Facebook LinkedIn

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