Economic growth: inclusive, green, no-cost.

POEMs at home

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It’s Monday afternoon. Yvonne is in pursuit of diverse economic opportunity. But it must fit within ever-changing commitments in her life.

 

 

 

Working it

Yvonne is ex-military, discharged with back problems. She now combines work largely as a security guard (which pays well for veterans), beautician (which she enjoys) and care worker (first steps towards the nursing career she craves). With her new husband, she cares part time for a disabled grandson.

Yvonne lives within a cluster of US states that initiated POEMs (Public Official E-Markets) and saw it quickly adopted by residents used to social media. Yvonne found the system daunting at first and she adopted it conservatively, choosing to have an intermediary as her legal employer for work through the system. She could have opted for a commercial agency but selected a local co-operative that takes a small cut of her earnings across the system in return for its support. This charge is on top of POEMs’ 2% markup on each transaction.

A supermarket chain offers Guaranteed Work to new veterans. If she listed minimum 16 hours availability a week they would buy at least 6 whenever stores were busy. Realizing the value of a good POEMs’ track record, she worked diligently; quickly qualifying for their certification. It came with a code allowing her to validate the new credential and add it to her list of achievements in POEMs verified by intermediary.

Knowing she likes beauty work, POEMs then matched her with a salon wanting to grow their pool of top-up receptionists. Her proven reliability in retail merited their investment in her induction. Data showing local shortages of beauticians soon triggered external investment for her certification in return for a percentage of her enhanced earnings for six months.

Other enthusiasms and skills are constantly being exploited as POEMs works to enhance her opportunities and earnings. One example: Military and retail experience, plus a self-certified love of dogs, ensured she was found by POEMs algorithms working for Rent-A-Pet Inc. The company sought local delivery drivers for their rental of comfort dogs through POEMs. They have told POEMs to arrange one of their approved drivers, and a delivery vehicle, within each dog rental.

Yvonne has now turned off her old retail worktypes. They don’t pay enough and weren’t taking her where she wants to go. If the market turns against her, she can of course switch them back on.

 

Being available

Yvonne trades many assets on POEMs. She rents a barbecue set, the grandson’s paddling pool, curling tongs and a formal evening gown when they’re not needed. All the work is done for her by a nearby “holder” who dispatches items for rentals and checks them back in with POEMs constructing each contractual chain and deducting the holder’s mark-up.

But the key asset is hours she is available for work. She has a recurring pattern of availability in POEMs, but updates it as daily life unfolds. And her calendar is partly filled with recurring bookings; slots where a business or household wants her at regular times each week. POEMs constantly incentivizes these steps towards an employer/employee relationship.

POEMs produces many trendlines. A key one is Utilization: what percentage of hours offered are booked? Utilization can be shown across types of work, geographies, worker attributes, timeframes or combinations of factors like this. Yvonne’s figure is personal, covering her last four weeks.

Yvonne has told the system how far she will travel from home, her minimum period of notice and minimum length of bookings. Where she hasn’t accepted a fixed pay rate offer, she can tell POEMs to dynamically construct her rate for each booking for which she’s eligible. The further she has to travel the more compensation she needs. And she will only do short-notice assignments for an extra $2 for each hour less than four hours’ notice. This is a wide market with competing buyers. She charges what she’s worth.

POEMs doesn’t broadcast out potential bookings with sellers scrabbling to respond. It treats Yvonne’s hours as an asset to be sold at maximized value, within her parameters, and to be constantly developed. Whenever she gets a booking it will be within all her rules, at times she wants to work, helping her along her chosen pathway. The system expects her to complete these bookings. Her valuable track record of reliability is on the line if she confirms an assignment then fails to show up without triggering a replacement by POEMs.

Videos showing a version of the markets Yvonne is using can be seen here.

 

Data day

Many POEMs users are passive. They define an ambition, a career in marine engineering for example, then let system algorithms plot personalized stepping-stones of bookings, upskilling and investment or other interventions to get them there. But Yvonne is more hands-on. She watches POEMs’ information outputs in the way amateur investors scrutinize stock tickers. Today’s potential strategy: should she add babysitting to her portfolio of work-types? She tells Alexa to put the relevant POEMs data on her TV.

Currently there are no offers to finance her certification for childcare. That suggests a market that’s already over-supplied. Does she believe she could attract buyers in an obviously crowded sector? If so, POEMs can align her with trainers and certifying authorities instantly. It will construct learning sessions at times that fit around her. But she will have to self-fund accreditation.

So where is there funding if she wants to further broaden her openings? POEMs offers her an Opportunity Feed, curated through her filters, refreshed as often as she likes. She flicks it up on her phone. Today it is offering her:

  • Investment in her development: Arondique Inc. have put $50,000 into POEMs and told it to identify qualified beauticians with strong reliability records and medical experience or aspirations. They must be spread around the system’s catchment area. The corporate will fund individualized training in how to administer cosmetic facial injections in customers’ homes. POEMs is flagging the catch in the offer; she must agree to only injecting Arondique products for a year after training. POEMs would enforce this when she is booked for injection sessions. The current pay rate is acceptable for her but Utilization for their agents is only 48%.

She swipes left on this one.

 

  • Buyers of her time: Countless organizations tell POEMs to find workers with specific combinations of geography, skills, reliability ranking and aspirations. A local residential care facility maintains a pool of approved workers on the platform. Each worker in the pool has agreed to the facility’s fixed pay rate and been inducted by their staff. Yvonne is already in over a dozen pools like this for employers wanting pre-trained top-up workers on-tap. She likes working where they know her. She swipes right. That tells POEMs to schedule an induction session within hours she makes herself available.

 

  • The job interview is an instant swipe left. It lacks the prefix “Paid”. Given Yvonne’s track record she expects any serious employer trying to tempt her out of POEMs to pay for her time at an interview. She isn’t in supplicant mode.

 

  • Benefits: POEMs offered Yvonne a range of models – and providers – for health, holiday, retirement and other benefits each pro-rated and deducted from payment for each hour worked. Her system settings tell POEMs to alert her when more favorable options emerge from a new provider joining the system. She could have better pay if sick, it only takes a right swipe.

 

  • Social opportunities: Working in a post-jobs world can be isolating. POEMs has a range of social network tools. That’s tools for actual relevant local networking. POEMs’ operators have no algorithms aimed at keeping users glued to their screens, consuming adverts. Their priority is finding each user as much well-paid work as possible, they get – perhaps – 2% of earnings with no other source of revenue. Real networks help. A group of local beauticians wants to formalize a network; they’ve told POEMs to reach out to potential members within their parameters. She taps to open up more details then tells the system to push the opportunity back to her next month, she can’t decide about joining at present.

 

Money ways

Yvonne manages household finances through POEMs. She “auto-balances” income, automatically lending out anything over $50 above weekly spends each day, sometimes borrowing to make the target figure another week. This market for small loans between POEMs users is solid. POEMs isn’t allowed to speculate or create money by re-lending deposits. It just lets lenders choose one of its funds based on the risk parameters of users allowed to borrow that money. Market forces set interest rates for each pot of digital cash with the system securely facilitating everything for its standard 2% cut.

Yvonne is cautious, her spare income goes to a fund only lending to people who have reached at least level 5 (of 6) in POEMs’ reliability ranking. Borrowers accept they will go down two ranks across all POEMs’ markets if they fail to repay. Anyone likely to default in POEMs’ market for high-reliability individuals can of course re-borrow from another fund for less proven users. But rates will be higher to attract lenders willing to take more risk.

Yvonne started in POEMs with few assets in life. Her track record of reliable trading has become collateral even for the wider world. Unable to afford a deposit for a rented apartment, she could instantly get a bond to email to her landlord. Competing insurers inside the system allow a POEMs track record to be pledged for a cash sum. If she stops paying rent without cause the insurers pay the landlord, but she loses her track record and has to start again on the first rung.

POEMs never forces her to do anything, it just monitors whether she does what she says she will (by confirming, then completing bookings) and allows her to exploit the resulting record. Outside POEMs, credit ratings rank individuals by ability to consume. Yvonne is judged on ability to deliver.

 

Embedded

Within 6 months, POEMs has become a taken-for-granted enabler for Yvonne and her family. Her teenage stepson is in a school that operates a “Ringfenced Market”. Teachers have identified 50 local households and businesses deemed fit to hire 16 year olds for a few hours at a time. On Saturday daytimes, when they wish, he and classmates are deployed in stocktaking, gardening, bike repair, cleaning, bagging at a food market, teaching younger kids soccer, car valeting, data entry, counter service and other low risk activities.

Monthly review of each student’s experience with a Business Studies teacher helps them expand skills, services and confidence. All activity is limited to the school’s approved buyers, within times and parameters set by the Principal. On graduation, the boy will transition from this protective sub-market to mainstream POEMs with hundreds of hours earning from possibly dozens of buyers. That will kick-start his track record in the wider world. He aspires to life as a hotel manager. Once enrolled in community college, he will tell POEMs to find him paid work in banqueting, front-desk, kitchen portering and other related functions at times that fit round his studies.

POEMs facilitates volunteering, training, social meet-ups and similar activities as secondary to paid work. Yvonne is available for work today from 2PM-7.30PM. But she has told the platform if she’s not booked for one of her diverse worktypes by 4PM, it is to release her hours to her church’s project. They maintain a list of isolated older people; using their criteria, POEMs will assign Yvonne someone to visit, likely someone she has dropped in on before. She caps volunteering through POEMs at four hours a week.

On her way out to today’s first booking, Yvonne calls her sister, living in a neighboring state that didn’t initiate POEMs. She endures a predictable lament; daily scrabbling for survival work, low wages, payday loans, listless children with few prospects and a lack of decent men for dating.

Yvonne is past even the last point. She met her husband in an app that allows users to pledge their POEMs trading record. She would only meet potential partners whose photo, life story and reliability in making arrangements to meet was backed by pledging their POEMs’ grades. If she found a guy lying or letting her down without excuse on a first date, she could refer it into POEMs’ dispute resolution tools where he could end up back down the ladder of grades. She would have done it to protect other women.

 

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