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Asher Umerie

Asher Umerie

3 years ago

What is Bionic Reading?

Senses help us navigate a complicated world. They shape our worldview - how we hear, smell, feel, and taste. People claim a sixth sense, an intuitive capacity that extends perception.

Our brain is a half-pool of grey and white matter that stores data from our senses. Brains provide us context, so zombies' obsession makes sense.

Bionic reading uses the brain's visual information and context to simplify text comprehension.

Stay with me.

What is Bionic Reading?

Bionic reading is a software application established by Swiss typographic designer Renato Casutt. The term honors the brain (bio) and technology's collaboration to better text comprehension.

The image above shows two similar paragraphs with bionic reading.

Notice anything yet?

This Twitter user did.

I did too...

Image text describes bionic reading-

New method to aid reading by using artificial fixation points. The reader focuses on the highlighted starting letters, and the brain completes the word. 

How is Bionic Reading possible?

Do you remember seeing social media posts asking you to stare at a black dot for 30 seconds (or more)? You blink and see an after-image on your wall.

Our brains are skilled at identifying patterns and'seeing' familiar objects, therefore optical illusions are conceivable.

Brain and sight collaborate well. Text comprehension proves it.

Considering evolutionary patterns, humans' understanding skills may be cosmic luck.
Scientists don't know why people can read and write, but they do know what reading does to the brain.

One portion of your brain recognizes words, while another analyzes their meaning. Fixation, saccade, and linguistic transparency/opacity aid.

Let's explain some terms.

The Bionic reading website compares these tools.

Text highlights lead the eye. Fixation, saccade, and opacity can transfer visual stimuli to text, changing typeface.

## Final Thoughts on Bionic Reading

I'm excited about how this could influence my long-term assimilation and productivity.

This technology is still in development, with prototypes working on only a few apps. Like any new tech, it will be criticized.

I'll be watching Bionic Reading closely. Comment on it!

More on Productivity

Pen Magnet

Pen Magnet

3 years ago

Why Google Staff Doesn't Work

Photo by Rajeshwar Bachu on Unsplash

Sundar Pichai unveiled Simplicity Sprint at Google's latest all-hands conference.

To boost employee efficiency.

Not surprising. Few envisioned Google declaring a productivity drive.

Sunder Pichai's speech:

“There are real concerns that our productivity as a whole is not where it needs to be for the head count we have. Help me create a culture that is more mission-focused, more focused on our products, more customer focused. We should think about how we can minimize distractions and really raise the bar on both product excellence and productivity.”

The primary driver driving Google's efficiency push is:

Google's efficiency push follows 13% quarterly revenue increase. Last year in the same quarter, it was 62%.

Market newcomers may argue that the previous year's figure was fuelled by post-Covid reopening and growing consumer spending. Investors aren't convinced. A promising company like Google can't afford to drop so quickly.

Google’s quarterly revenue growth stood at 13%, against 62% in last year same quarter.

Google isn't alone. In my recent essay regarding 2025 programmers, I warned about the economic downturn's effects on FAAMG's workforce. Facebook had suspended hiring, and Microsoft had promised hefty bonuses for loyal staff.

In the same article, I predicted Google's troubles. Online advertising, especially the way Google and Facebook sell it using user data, is over.

FAAMG and 2nd rung IT companies could be the first to fall without Post-COVID revival and uncertain global geopolitics.

Google has hardly ever discussed effectiveness:

Apparently openly.

Amazon treats its employees like robots, even in software positions. It has significant turnover and a terrible reputation as a result. Because of this, it rarely loses money due to staff productivity.

Amazon trumps Google. In reality, it treats its employees poorly.

Google was the founding father of the modern-day open culture.

Larry and Sergey Google founded the IT industry's Open Culture. Silicon Valley called Google's internal democracy and transparency near anarchy. Management rarely slammed decisions on employees. Surveys and internal polls ensured everyone knew the company's direction and had a vote.

20% project allotment (weekly free time to build own project) was Google's open-secret innovation component.

After Larry and Sergey's exit in 2019, this is Google's first profitability hurdle. Only Google insiders can answer these questions.

  • Would Google's investors compel the company's management to adopt an Amazon-style culture where the developers are treated like circus performers?

  • If so, would Google follow suit?

  • If so, how does Google go about doing it?

Before discussing Google's likely plan, let's examine programming productivity.

What determines a programmer's productivity is simple:

How would we answer Google's questions?

As a programmer, I'm more concerned about Simplicity Sprint's aftermath than its economic catalysts.

Large organizations don't care much about quarterly and annual productivity metrics. They have 10-year product-launch plans. If something seems horrible today, it's likely due to someone's lousy judgment 5 years ago who is no longer in the blame game.

Deconstruct our main question.

  • How exactly do you change the culture of the firm so that productivity increases?

  • How can you accomplish that without affecting your capacity to profit? There are countless ways to increase output without decreasing profit.

  • How can you accomplish this with little to no effect on employee motivation? (While not all employers care about it, in this case we are discussing the father of the open company culture.)

  • How do you do it for a 10-developer IT firm that is losing money versus a 1,70,000-developer organization with a trillion-dollar valuation?

When implementing a large-scale organizational change, success must be carefully measured.

The fastest way to do something is to do it right, no matter how long it takes.

You require clearly-defined group/team/role segregation and solid pass/fail matrices to:

  • You can give performers rewards.

  • Ones that are average can be inspired to improve

  • Underachievers may receive assistance or, in the worst-case scenario, rehabilitation

As a 20-year programmer, I associate productivity with greatness.

Doing something well, no matter how long it takes, is the fastest way to do it.

Let's discuss a programmer's productivity.

Why productivity is a strange term in programming:

Productivity is work per unit of time.

Money=time This is an economic proverb. More hours worked, more pay. Longer projects cost more.

As a buyer, you desire a quick supply. As a business owner, you want employees who perform at full capacity, creating more products to transport and boosting your profits.

All economic matrices encourage production because of our obsession with it. Productivity is the only organic way a nation may increase its GDP.

Time is money — is not just a proverb, but an economical fact.

Applying the same productivity theory to programming gets problematic. An automating computer. Its capacity depends on the software its master writes.

Today, a sophisticated program can process a billion records in a few hours. Creating one takes a competent coder and the necessary infrastructure. Learning, designing, coding, testing, and iterations take time.

Programming productivity isn't linear, unlike manufacturing and maintenance.

Average programmers produce code every day yet miss deadlines. Expert programmers go days without coding. End of sprint, they often surprise themselves by delivering fully working solutions.

Reversing the programming duties has no effect. Experts aren't needed for productivity.

These patterns remind me of an XKCD comic.

Source: XKCD

Programming productivity depends on two factors:

  • The capacity of the programmer and his or her command of the principles of computer science

  • His or her productive bursts, how often they occur, and how long they last as they engineer the answer

At some point, productivity measurement becomes Schrödinger’s cat.

Product companies measure productivity using use cases, classes, functions, or LOCs (lines of code). In days of data-rich source control systems, programmers' merge requests and/or commits are the most preferred yardstick. Companies assess productivity by tickets closed.

Every organization eventually has trouble measuring productivity. Finer measurements create more chaos. Every measure compares apples to oranges (or worse, apples with aircraft.) On top of the measuring overhead, the endeavor causes tremendous and unnecessary stress on teams, lowering their productivity and defeating its purpose.

Macro productivity measurements make sense. Amazon's factory-era management has done it, but at great cost.

Google can pull it off if it wants to.

What Google meant in reality when it said that employee productivity has decreased:

When Google considers its employees unproductive, it doesn't mean they don't complete enough work in the allotted period.

They can't multiply their work's influence over time.

  • Programmers who produce excellent modules or products are unsure on how to use them.

  • The best data scientists are unable to add the proper parameters in their models.

  • Despite having a great product backlog, managers struggle to recruit resources with the necessary skills.

  • Product designers who frequently develop and A/B test newer designs are unaware of why measures are inaccurate or whether they have already reached the saturation point.

  • Most ignorant: All of the aforementioned positions are aware of what to do with their deliverables, but neither their supervisors nor Google itself have given them sufficient authority.

So, Google employees aren't productive.

How to fix it?

  • Business analysis: White suits introducing novel items can interact with customers from all regions. Track analytics events proactively, especially the infrequent ones.

  • SOLID, DRY, TEST, and AUTOMATION: Do less + reuse. Use boilerplate code creation. If something already exists, don't implement it yourself.

  • Build features-building capabilities: N features are created by average programmers in N hours. An endless number of features can be built by average programmers thanks to the fact that expert programmers can produce 1 capability in N hours.

  • Work on projects that will have a positive impact: Use the same algorithm to search for images on YouTube rather than the Mars surface.

  • Avoid tasks that can only be measured in terms of time linearity at all costs (if a task can be completed in N minutes, then M copies of the same task would cost M*N minutes).

In conclusion:

Software development isn't linear. Why should the makers be measured?

Notation for The Big O

I'm discussing a new way to quantify programmer productivity. (It applies to other professions, but that's another subject)

The Big O notation expresses the paradigm (the algorithmic performance concept programmers rot to ace their Google interview)

Google (or any large corporation) can do this.

  1. Sort organizational roles into categories and specify their impact vs. time objectives. A CXO role's time vs. effect function, for instance, has a complexity of O(log N), meaning that if a CEO raises his or her work time by 8x, the result only increases by 3x.

  2. Plot the influence of each employee over time using the X and Y axes, respectively.

  3. Add a multiplier for Y-axis values to the productivity equation to make business objectives matter. (Example values: Support = 5, Utility = 7, and Innovation = 10).

  4. Compare employee scores in comparable categories (developers vs. devs, CXOs vs. CXOs, etc.) and reward or help employees based on whether they are ahead of or behind the pack.

After measuring every employee's inventiveness, it's straightforward to help underachievers and praise achievers.

Example of a Big(O) Category:

If I ran Google (God forbid, its worst days are far off), here's how I'd classify it. You can categorize Google employees whichever you choose.

The Google interview truth:

O(1) < O(log n) < O(n) < O(n log n) < O(n^x) where all logarithmic bases are < n.

O(1): Customer service workers' hours have no impact on firm profitability or customer pleasure.

CXOs Most of their time is spent on travel, strategic meetings, parties, and/or meetings with minimal floor-level influence. They're good at launching new products but bad at pivoting without disaster. Their directions are being followed.

Devops, UX designers, testers Agile projects revolve around deployment. DevOps controls the levers. Their automation secures results in subsequent cycles.

UX/UI Designers must still prototype UI elements despite improved design tools.

All test cases are proportional to use cases/functional units, hence testers' work is O(N).

Architects Their effort improves code quality. Their right/wrong interference affects product quality and rollout decisions even after the design is set.

Core Developers Only core developers can write code and own requirements. When people understand and own their labor, the output improves dramatically. A single character error can spread undetected throughout the SDLC and cost millions.

Core devs introduce/eliminate 1000x bugs, refactoring attempts, and regression. Following our earlier hypothesis.

The fastest way to do something is to do it right, no matter how long it takes.

Conclusion:

Google is at the liberal extreme of the employee-handling spectrum

Microsoft faced an existential crisis after 2000. It didn't choose Amazon's data-driven people management to revitalize itself.

Instead, it entrusted developers. It welcomed emerging technologies and opened up to open source, something it previously opposed.

Google is too lax in its employee-handling practices. With that foundation, it can only follow Amazon, no matter how carefully.

Any attempt to redefine people's measurements will affect the organization emotionally.

The more Google compares apples to apples, the higher its chances for future rebirth.

Jari Roomer

Jari Roomer

3 years ago

5 ways to never run out of article ideas

Perfectionism is the enemy of the idea muscle. " — James Altucher

Photo by Paige Cody on Unsplash

Writer's block is a typical explanation for low output. Success requires productivity.

In four years of writing, I've never had writer's block. And you shouldn't care.

You'll never run out of content ideas if you follow a few tactics. No, I'm not overpromising.


Take Note of Ideas

Brains are strange machines. Blank when it's time to write. Idiot. Nothing. We get the best article ideas when we're away from our workstation.

  • In the shower

  • Driving

  • In our dreams

  • Walking

  • During dull chats

  • Meditating

  • In the gym

No accident. The best ideas come in the shower, in nature, or while exercising.

(Your workstation is the worst place for creativity.)

The brain has time and space to link 'dots' of information during rest. It's eureka! New idea.

If you're serious about writing, capture thoughts as they come.

Immediately write down a new thought. Capture it. Don't miss it. Your future self will thank you.

As a writer, entrepreneur, or creative, letting ideas slide is bad.

I recommend using Evernote, Notion, or your device's basic note-taking tool to capture article ideas.

It doesn't matter whatever app you use as long as you collect article ideas.

When you practice 'idea-capturing' enough, you'll have an unending list of article ideas when writer's block hits.


High-Quality Content

More books, films, Medium pieces, and Youtube videos I consume, the more I'm inspired to write.

What you eat shapes who you are.

Celebrity gossip and fear-mongering news won't help your writing. It won't help you write regularly.

Instead, read expert-written books. Watch documentaries to improve your worldview. Follow amazing people online.

Develop your 'idea muscle' Daily creativity takes practice. The more you exercise your 'idea muscles,' the easier it is to generate article ideas.

I've trained my 'concept muscle' using James Altucher's exercise.


Write 10 ideas daily.

Write ten book ideas every day if you're an author. Write down 10 business ideas per day if you're an entrepreneur. Write down 10 investing ideas per day.

Write 10 article ideas per day. You become a content machine.

It doesn't state you need ten amazing ideas. You don't need 10 ideas. Ten ideas, regardless of quality.

Like at the gym, reps are what matter. With each article idea, you gain creativity. Writer's block is no match for this workout.


Quit Perfectionism

Perfectionism is bad for writers. You'll have bad articles. You'll have bad ideas. OK. It's creative.

Writing success requires prolificacy. You can't have 'perfect' articles.

Perfectionism is the enemy of the idea muscle. Perfectionism is your brain trying to protect you from harm.” — James Altucher

Vincent van Gogh painted 900 pieces. The Starry Night is the most famous.

Thomas Edison invented 1093 things, but not all were as important as the lightbulb or the first movie camera.

Mozart composed nearly 600 compositions, but only Serenade No13 became popular.

Always do your best. Perfectionism shouldn't stop you from working. Write! Publicize. Make. Even if imperfect.


Write Your Story

Living an interesting life gives you plenty to write about. If you travel a lot, share your stories or lessons learned.

Describe your business's successes and shortcomings.

Share your experiences with difficulties or addictions.

More experiences equal more writing material.

If you stay indoors, perusing social media, you won't be inspired to write.

Have fun. Travel. Strive. Build a business. Be bold. Live a life worth writing about, and you won't run out of material.

Jon Brosio

Jon Brosio

3 years ago

Every time I use this 6-part email sequence, I almost always make four figures.

(And you can have it for free)

Photo by Gustavo Fring from Pexels

Master email to sell anything.

Most novice creators don't know how to begin.

Many use online templates. These are usually fluff-filled and niche-specific.

They're robotic and "salesy."

I've attended 3 courses, read 10 books, and sent 600,000 emails in the past five years.

Outcome?

This *proven* email sequence assures me a month's salary every time I send it.

What you will discover in this article is that:

  • A full 6-part email sales cycle

  • The essential elements you must incorporate

  • placeholders and text-filled images

  • (Applies to any niche)

This can be a product introduction, holiday, or welcome sequence. This works for email-saleable products.

Let's start

Email 1: Describe your issue

This email is crucial.

How to? We introduce a subscriber or prospect's problem. Later, we'll frame our offer as the solution.

Label the:

  • Problem

  • Why it still hasn't been fixed

  • Resulting implications for the customer

This puts our new subscriber in solve mode and queues our offer:

Courtesy | author

Email 2: Amplify the consequences

We're still causing problems.

We've created the problem, but now we must employ emotion and storytelling to make it real. We also want to forecast life if nothing changes.

Let's feel:

  • What occurs if it is not resolved?

  • Why is it crucial to fix it immediately?

  • Tell a tale of a person who was in their position. To emphasize the effects, use a true account of another person (or of yourself):

Courtesy | author

Email 3: Share a transformation story

Selling stories.

Whether in an email, landing page, article, or video. Humanize stories. They give information meaning.

This is where "issue" becomes "solution."

Let's reveal:

  • A tale of success

  • A new existence and result

  • tools and tactics employed

Start by transforming yourself.

Courtesy | author

Email 4: Prove with testimonials

No one buys what you say.

Emotionally stirred people buy and act. They believe in the product. They feel that if they buy, it will work.

Social proof shows prospects that your solution will help them.

Add:

  • Earlier and Later

  • Testimonials

  • Reviews

Proof this deal works:

Courtesy | author

Email 5: Reveal your offer

It's showtime.

This is it. Until now, describing the offer and offering links to a landing page have been sparse in the email pictures.

We've been tense. Gaining steam. Building suspense. Email 5 reveals all.

In this email:

  • a description of the deal

  • A word about a promise

  • recapitulation of the transformation

  • and make a reference to the urgency Everything should be spelled out clearly:

Courtesy | author

Email no. 6: Instill urgency

When there are stakes, humans act.

Creating and marketing with haste raises the stakes. Urgency makes a prospect act because they'll miss out or gain immensely.

Urgency converts. Use:

  • short time

  • Screening

  • Scarcity

Urgency and conversions. Limited-time offers are easy.

Courtesy | author

TL;DR

Use this proven 6-part email sequence (that turns subscribers into profit):

  • Introduce a problem

  • Amplify it with emotions

  • Share transformation story

  • Prove it works with testimonials

  • Value-stack and present your offer

  • Drive urgency and entice the purchase

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Frederick M. Hess

Frederick M. Hess

2 years ago

The Lessons of the Last Two Decades for Education Reform

My colleague Ilana Ovental and I examined pandemic media coverage of education at the end of last year. That analysis examined coverage changes. We tracked K-12 topic attention over the previous two decades using Lexis Nexis. See the results here.

I was struck by how cleanly the past two decades can be divided up into three (or three and a half) eras of school reform—a framing that can help us comprehend where we are and how we got here. In a time when epidemic, political unrest, frenetic news cycles, and culture war can make six months seem like a lifetime, it's worth pausing for context.

If you look at the peaks in the above graph, the 21st century looks to be divided into periods. The decade-long rise and fall of No Child Left Behind began during the Bush administration. In a few years, NCLB became the dominant K-12 framework. Advocates and financiers discussed achievement gaps and measured success with AYP.

NCLB collapsed under the weight of rigorous testing, high-stakes accountability, and a race to the bottom by the Obama years. Obama's Race to the Top garnered attention, but its most controversial component, the Common Core State Standards, rose quickly.

Academic standards replaced assessment and accountability. New math, fiction, and standards were hotly debated. Reformers and funders chanted worldwide benchmarking and systems interoperability.

We went from federally driven testing and accountability to government encouraged/subsidized/mandated (pick your verb) reading and math standardization. Last year, Checker Finn and I wrote The End of School Reform? The 2010s populist wave thwarted these objectives. The Tea Party, Occupy Wall Street, Black Lives Matter, and Trump/MAGA all attacked established institutions.

Consequently, once the Common Core fell, no alternative program emerged. Instead, school choice—the policy most aligned with populist suspicion of institutional power—reached a half-peak. This was less a case of choice erupting to prominence than of continuous growth in a vacuum. Even with Betsy DeVos' determined, controversial efforts, school choice received only half the media attention that NCLB and Common Core did at their heights.

Recently, culture clash-fueled attention to race-based curriculum and pedagogy has exploded (all playing out under the banner of critical race theory). This third, culture war-driven wave may not last as long as the other waves.

Even though I don't understand it, the move from slow-building policy debate to fast cultural confrontation over two decades is notable. I don't know if it's cyclical or permanent, or if it's about schooling, media, public discourse, or all three.

One final thought: After doing this work for decades, I've noticed how smoothly advocacy groups, associations, and other activists adapt to the zeitgeist. In 2007, mission statements focused on accomplishment disparities. Five years later, they promoted standardization. Language has changed again.

Part of this is unavoidable and healthy. Chasing currents can also make companies look unprincipled, promote scepticism, and keep them spinning the wheel. Bearing in mind that these tides ebb and flow may give educators, leaders, and activists more confidence to hold onto their values and pause when they feel compelled to follow the crowd.

Sam Hickmann

Sam Hickmann

3 years ago

Improving collaboration with the Six Thinking Hats

Six Thinking Hats was written by Dr. Edward de Bono. "Six Thinking Hats" and parallel thinking allow groups to plan thinking processes in a detailed and cohesive way, improving collaboration.

Fundamental ideas

In order to develop strategies for thinking about specific issues, the method assumes that the human brain thinks in a variety of ways that can be intentionally challenged. De Bono identifies six brain-challenging directions. In each direction, the brain brings certain issues into conscious thought (e.g. gut instinct, pessimistic judgement, neutral facts). Some may find wearing hats unnatural, uncomfortable, or counterproductive.

The example of "mismatch" sensitivity is compelling. In the natural world, something out of the ordinary may be dangerous. This mode causes negative judgment and critical thinking.

Colored hats represent each direction. Putting on a colored hat symbolizes changing direction, either literally or metaphorically. De Bono first used this metaphor in his 1971 book "Lateral Thinking for Management" to describe a brainstorming framework. These metaphors allow more complete and elaborate thought separation. Six thinking hats indicate ideas' problems and solutions.

Similarly, his CoRT Thinking Programme introduced "The Five Stages of Thinking" method in 1973.

HATOVERVIEWTECHNIQUE
BLUE"The Big Picture" & ManagingCAF (Consider All Factors); FIP (First Important Priorities)
WHITE"Facts & Information"Information
RED"Feelings & Emotions"Emotions and Ego
BLACK"Negative"PMI (Plus, Minus, Interesting); Evaluation
YELLOW"Positive"PMI
GREEN"New Ideas"Concept Challenge; Yes, No, Po

Strategies and programs

After identifying the six thinking modes, programs can be created. These are groups of hats that encompass and structure the thinking process. Several of these are included in the materials for franchised six hats training, but they must often be adapted. Programs are often "emergent," meaning the group plans the first few hats and the facilitator decides what to do next.

The group agrees on how to think, then thinks, then evaluates the results and decides what to do next. Individuals or groups can use sequences (and indeed hats). Each hat is typically used for 2 minutes at a time, although an extended white hat session is common at the start of a process to get everyone on the same page. The red hat is recommended to be used for a very short period to get a visceral gut reaction – about 30 seconds, and in practice often takes the form of dot-voting.

ACTIVITYHAT SEQUENCE
Initial IdeasBlue, White, Green, Blue
Choosing between alternativesBlue, White, (Green), Yellow, Black, Red, Blue
Identifying SolutionsBlue, White, Black, Green, Blue
Quick FeedbackBlue, Black, Green, Blue
Strategic PlanningBlue, Yellow, Black, White, Blue, Green, Blue
Process ImprovementBlue, White, White (Other People's Views), Yellow, Black, Green, Red, Blue
Solving ProblemsBlue, White, Green, Red, Yellow, Black, Green, Blue
Performance ReviewBlue, Red, White, Yellow, Black, Green, Blue

Use

Speedo's swimsuit designers reportedly used the six thinking hats. "They used the "Six Thinking Hats" method to brainstorm, with a green hat for creative ideas and a black one for feasibility.

Typically, a project begins with extensive white hat research. Each hat is used for a few minutes at a time, except the red hat, which is limited to 30 seconds to ensure an instinctive gut reaction, not judgement. According to Malcolm Gladwell's "blink" theory, this pace improves thinking.

De Bono believed that the key to a successful Six Thinking Hats session was focusing the discussion on a particular approach. A meeting may be called to review and solve a problem. The Six Thinking Hats method can be used in sequence to explore the problem, develop a set of solutions, and choose a solution through critical examination.

Everyone may don the Blue hat to discuss the meeting's goals and objectives. The discussion may then shift to Red hat thinking to gather opinions and reactions. This phase may also be used to determine who will be affected by the problem and/or solutions. The discussion may then shift to the (Yellow then) Green hat to generate solutions and ideas. The discussion may move from White hat thinking to Black hat thinking to develop solution set criticisms.

Because everyone is focused on one approach at a time, the group is more collaborative than if one person is reacting emotionally (Red hat), another is trying to be objective (White hat), and another is critical of the points which emerge from the discussion (Black hat). The hats help people approach problems from different angles and highlight problem-solving flaws.

The woman

The woman

3 years ago

Why Google's Hiring Process is Brilliant for Top Tech Talent

Without a degree and experience, you can get a high-paying tech job.

Photo by Mitchell Luo on Unsplash

Most organizations follow this hiring rule: you chat with HR, interview with your future boss and other senior managers, and they make the final hiring choice.

If you've ever applied for a job, you know how arduous it can be. A newly snapped photo and a glossy resume template can wear you out. Applying to Google can change this experience.

According to an Universum report, Google is one of the world's most coveted employers. It's not simply the search giant's name and reputation that attract candidates, but its role requirements or lack thereof.

Candidates no longer need a beautiful resume, cover letter, Ivy League laurels, or years of direct experience. The company requires no degree or experience.

Elon Musk started it. He employed the two-hands test to uncover talented non-graduates. The billionaire eliminated the requirement for experience.

Google is deconstructing traditional employment with programs like the Google Project Management Degree, a free online and self-paced professional credential course.

Google's hiring is interesting. After its certification course, applicants can work in project management. Instead of academic degrees and experience, the company analyzes coursework.

Google finds the best project managers and technical staff in exchange. Google uses three strategies to find top talent.

Chase down the innovators

Google eliminates restrictions like education, experience, and others to find the polar bear amid the snowfall. Google's free project management education makes project manager responsibilities accessible to everyone.

Many jobs don't require a degree. Overlooking individuals without a degree can make it difficult to locate a candidate who can provide value to a firm.

Firsthand knowledge follows the same rule. A lack of past information might be an employer's benefit. This is true for creative teams or businesses that prefer to innovate.

Or when corporations conduct differently from the competition. No-experience candidates can offer fresh perspectives. Fast Company reports that people with no sales experience beat those with 10 to 15 years of experience.

Give the aptitude test first priority.

Google wants the best candidates. Google wouldn't be able to receive more applications if it couldn't screen them for fit. Its well-organized online training program can be utilized as a portfolio.

Google learns a lot about an applicant through completed assignments. It reveals their ability, leadership style, communication capability, etc. The course mimics the job to assess candidates' suitability.

Basic screening questions might provide information to compare candidates. Any size small business can use screening questions and test projects to evaluate prospective employees.

Effective training for employees

Businesses must train employees regardless of their hiring purpose. Formal education and prior experience don't guarantee success. Maintaining your employees' professional knowledge gaps is key to their productivity and happiness. Top-notch training can do that. Learning and development are key to employee engagement, says Bob Nelson, author of 1,001 Ways to Engage Employees.

Google's online certification program isn't available everywhere. Improving the recruiting process means emphasizing aptitude over experience and a degree. Instead of employing new personnel and having them work the way their former firm trained them, train them how you want them to function.

If you want to know more about Google’s recruiting process, we recommend you watch the movie “Internship.”