See how leaders, including Sapia’s CEO Barbara Hyman, reacted to the Treasurer’s 2020 Federal Budget, and their comments on how it will impact Australian businesses.
Featured in Business Daily Media | Wed 7th October 2020
“The R&D incentives initiative is a game changer for us because it provides the very thing that all start up businesses want – certainty. These changes are strongly supported because it means we can, as a business, confidently invest in more people to deliver innovative solutions and provide material outcomes for economic growth.”
“ACS is delighted to see the recognition of the importance of technology professionals in Australia’s recovery from the COVID-19 downturn with the emphasis on IT and cybersecurity in this year’s budget.
The 50,000 new higher education short courses which include IT subjects is an important part of addressing skill shortages across the Australian economy.
Coupled with this, the announcement of $240m to support female cadetships and apprenticeships in science, technology, engineering and mathematics will go some way to address the under-representation of women in the ICT sector.
Along with the measures announced in last week’s advanced manufacturing and Digital Business plans, the budget lays firm foundations for a tech led recovery.”
“I welcome the Treasurer’s announcement that the government will provide $231m over four years to support economic recovery by employing more women in the workforce. The funding to increase the number of co-funded grants to women-founded start-ups, and to establish the women in STEM industry cadetship program is a fantastic step in the right direction.
As a female tech founder of an emerging RegTech provider of a digital product governance platform, these initiatives are refreshing and will certainly drive growth in our digital economy.
Australia has over 80 emerging RegTech providers supported by the RegTech Association, and if each of them plans to create around ten new jobs in next 12 months, we are well on the way to not only supporting modern manufacturing and the broad range of Australian industries (clean energy, MedTech, IoT, retail) but also to building a global RegTech export sector.
There is a substantial opportunity for high export potential of RegTech right at the time when our country needs it most. Global RegTech spending is predicted to exceed USD $127 billion.
I would however encourage the government to go harder on looking at initiatives to promote commercialisation. In Australia, a gap exists in commercialisation – after R&D when a start-up needs to find product-market fit and scale-up. Australia needs more effective incentives for this ‘cliff’ to ensure commercialisation and that jobs of the future stay in Australia.”
“I highly commend the government’s decision to double the number of Medicare funded psychological services through the Better Access Initiative. We’ve seen a huge spike in mental health related problems since the outbreak of COVID-19, and this is projected to get worse. Better Access funds telehealth mental health consultations, and thus enables equitable access for all Australians.
But there are more challenges than just mental health. I would have liked to have seen a broader approach to the digitalisation of healthcare. The global pandemic has accelerated digital transformation in healthcare. However, the Federal Budget was missing any concrete indication from the government to properly see this through; the digitalisation of our system starts with a long-term pledge to the reimbursement of telehealth items.
Healthcare businesses aren’t going to invest in the necessary training, hardware and infrastructure setup for digital transformation if there is no long-term government commitment.
We all want to live in a country where quality healthcare is accessible to all. However, it’s going to take more support from the government to get there. I’m hopeful that it won’t take us another pandemic to realise this.”
“While the JobMaker Hiring Credit and the $1.2bn investment to support apprenticeships and trainees are strong initiatives to boost employment, neither of these measures holistically address employment with thousands of Australian white collar workers looking for work who could be utilised more effectively now to help further stimulate the economy. The JobMaker Hiring Credit will be paid at a rate too low to seriously help any business pay the wage of a skilled worker, of which there is high demand for amongst small to medium businesses and this ranges from everything from tech engineers, accountants, marketeers, IT and business professionals.
“To get Australians back to work we need to get more creative in how we view people’s skill sets. The JobTrainer package announced earlier this year is a step in the right direction for helping upskill Australians, but we need more investment in the learning and development space for programs to help job seekers transfer their skills into new industries. The job market is down, but the reality is that there’s still a lot of businesses operating. When they are hiring, they need to be able to screen applications for transferable skill set. All this while making the right hires quickly.”
“It is positive to see reinforced support for mental health initiatives, but this focus needs to be on preventative measures that can help support the wellbeing of Australians before it reaches crisis level. While support for organisations like Beyond Blue is necessary, we also need long term investment for mental health in the learning and development space to create initiatives that can be delivered at a workplace level to support the wellbeing and resilience of Australians as an ongoing priority.”
The expanded First Home Loan Deposit Scheme is a fantastic step in the right direction – too many people living in expensive cities have been missing out for for too long. Increasing the caps on the price of homes that can be purchased to as much as $950,000 will go a long way towards helping to kick start the building boom which is absolutely critical to our economy.
However, it is a shame the HomeBuilder scheme was not extended. This would have been a fantastic way to rejuvenate the property market.
“The Federal Budget is rightly looking to stimulate the economy. It is pleasing to see that more funding for medicines is being injected into the Modern Manufacturing plan. Unfortunately, the breakthroughs we need to overcome the current pandemic will, and are coming from, the smaller companies like Aegros.
To date, we have not seen any targeted support for Australian innovation sectors. This plus the cut in innovation company grants has really cut into Australia’s innovation engine. It may well explain the decrease we have seen in Australia’s productivity over the last 10 years.
Despite this, the Government still hasn’t considered reactivating the SME company R&D commercial project grants,. Those grants provided up to 50% funding to cover the cost of bridging the death valley between prototypes and a commercial product. There’s still much to learn for the Australian government, particularly from Israel, whereby this model of funding has been used to have successful companies repay sales grants. The beauty of this approach is the funds have to be spent first before the Government co-funds. Ensuring only worthwhile projects are supported and ensuring the funds are spent and not used to pay down debts.”
“It is comforting and critical that the government has recognised the important need to invest in thIs younger generation. They are both the worst-affected as a group by COVID in the short term. They are also likely to beat a larger cost of the impact of COVID on the economy and employment opportunities for the next 5 to 10 years.
Despite this, the investment in training only pays off if the individual has a good idea of what jobs they are best suited to. And we all know that career counselling from school and beyond is pretty much non-existent.
The more understanding for the kind of role and environment that brings out the best in an 18 or 25-year-old and the deeper self-awareness they have about their strengths, the more ROI both the government and the individual will get from this massive investment. Scaleable career discovery should really be a part of this and the R&D backing in this year’s budget should be used. This technology is here now through AI-led personalised scaleable career coaching. Perfect for the scale of the challenge we face in a world where face-to-face contact is becoming less necessary.”
“While any increase in funding is welcomed for the aged care sector in crisis, it seems the Government’s 2020-21 budget comes without fundamental structural changes.
The government mentioned an increase in-home care packages alone – and when we already have an average of nearly $8,000 per person unspent, and over 100,000 on the waiting list (almost as many as the 136,000 receiving a package), it does feel a bit like putting a bandaid on a shark bite.
Care providers are already overworked and understaffed, and Australia needs to be spending the money more effectively and efficiently. The aged care sector is clearly in crisis. Thus, instead of adding more funding or policies to what we are already doing, we need to stop the bleeding at the source and become preventative rather than reactive. The government should be enabling families to take charge of their own care to relieve the over-stressing and this could be achieved through technology.
The first contact is via general practitioners and the existing healthcare network. We need to make assistive technology MBS approved and put the power back into the hands of the individual, and save on higher cost services that are, simply put, too little too late.”
“It’s encouraging to see $2 billion injection in R&D incentives. The mortgage broking and the mortgage sector overall is rapidly digitising and this program will only help support its disruption and drive efficiency in the mortgage market. However, there’s still no support for software-based R&D activities which is going to drive the next phase of growth for Australia. AI will be the key for driving productivity of Australians and companies like Effi will be investing heavily in R&D to develop right AI solutions and compete at a global level – but this is only possible if companies like Effi can access R&D incentives easily.
On the other hand, tax support for businesses and incentives for hiring are also good, as they are also needed to help businesses sustain growth.”
“The federal government’s move to invest $28.5 million in expanding Australia’s world-leading Consumer Data Right is an excellent move forward that will help Australia move closer towards realising its open banking transition. The Consumer Data Right and Open Banking is an important initiative that serves up plenty of advantages for Australian customers. It will allow fintech entrants to provide new and improved products by offering data-driven insights and more compelling, tailored and personalised offerings for Australians, all of which will drive economic growth and improved customer outcomes.
At Seed Space, we believe that collaboration is a key driver of success and the $9.6 million proposed by the government to expand the Fintech Bridge program is a welcome initiative that builds on the government’s ongoing multilateral fintech expansion initiatives that are all aimed at helping Australian fintechs grow and scale into key offshore markets such as Europe and the UK, as well as learning from international counterparts to ensure our home grown fintechs are at the operating in line with global best practice.
We also strongly believe the $11.4 million for Australian regtech companies to help ease regulatory burdens is an important initiative. The government is also making available $6.9 million in funding for two blockchain pilots to test how the technology could be used to reduce regulatory compliance burden for businesses. These pilots will complement the National Blockchain Roadmap and will allow the development of successful use cases in how blockchain can help reduce frictions and pain points right across industry verticals.”
“The federal government has stepped up to the plate and provided critical funding support that would allow local manufacturers to continue to innovate, particularly in critical export sectors like retail and health and wellness.
The R&D initiatives will be most welcome to Australian emerging companies seeking to grow and realise their export potential. With regards to this, EVE are currently working on new product development with our honey and tea tree and the development of strains of probiotic that work synergistically to maximise the gut health benefit to consumers. R&D assistance from the government in this process would enable innovation by bringing these products to market much quicker and into the hands of everyday Australians.
Support will also be given to manufacturers to upgrade and improve manufacturing equipment to expand production. At EVE, we are firmly focused on identifying new opportunities for scale, and dovetails nicely with our expansion plans for new export markets and the need to increase our manufacturing capacity. It also is a critical step in providing new employment opportunities for Australian businesses in manufacturing.”
“The budget saw the federal government go much further in recognising what is going to be leading the engine room of the Australian economy both now and in the months ahead: small business.
Many SME businesses across Australia have been left ill-equipped to respond to COVID-19 and we must provide these businesses with a clear path for recovery and getting back to operating very quickly. With over 2 million SMBs across the country, accounting for more than 97 per cent of all Australian businesses by employee size, this business segment is the beating heart of this country.
What we would have liked to see more is additional consideration for helping businesses in regional areas, particularly those looking to adjust to operating in a new normal and supporting their digital footprints. The message is clear: if you’re in any business, you’ve got to be investing in digital resilience.”
“I’m happy to see that this year’s budget includes a number of great outcomes for the startup community. In particular, we welcome the $2bn boost for R&D as this is the lifeline of the tech sector and will provide greater certainty for investment and help support the development of novel technologies within Australia.
The investment in the 5G network and infrastructure is another win for us as better internet means improved connectivity for startups with their employees, customers, partners and networks, ultimately speeding up growth capability.
The $9.6M investment for fintechs will enhance support for businesses to expand internationally and encourage foreign investment and job creation in Australia. The investment in blockchain technology will also help support the fintech community through encouraging broader uptake of blockchain by these businesses which can help improve transparency and rescue regulatory compliance costs.
We welcome news of the personal income tax cuts which will be of great support to many founders who are working full time to support their side hustles. Tax relief will lower the cost of living and allow founders longer runways.
Investment in measures to improve STEM gender equity in Australia is another positive outcome for startups as this will see startups have access to larger talent pools and new perspectives which previously impacted startups having ‘male blinkers’.”
Source: Staff Writer at Business Daily Media, October 7 2020
Predictive Talent Analytics turns the imaginary into reality, presenting a variety of businesses, including contact centres, with the opportunity to improve hiring outcomes and raise the performance bar. With only a minor tweak to existing business processes, predictive talent analytics addresses challenge faced by many contact centres.
Recruitment typically involves face-to-face or telephone interviews and psychometric or situational awareness tests. However, there’s an opportunity to make better hires and to achieve better outcomes through the use of Predictive Talent Analytics.
Many organisations are already using analytics to help with their talent processes. Crucially, these are descriptive analytical tools. They’re reporting the past and present. They aren’t looking forward to tomorrow and that’s key. If the business is moving forward your talent tools should also be pointing in the same direction.
Consider a call-waiting display board showing missed and waiting calls. This is reporting.
Alternatively, consider a board that does the same but also accurately predicts significant increases in call volumes, providing you with enough time to increase staffing levels appropriately. That’s predictive.
Descriptive analytical tools showing the path to achievement taken by good performers within the business can add value. But does that mean that every candidate within a bracketed level of academic achievement, from a particular socio-economic background, from a certain area of town or from a particular job board is right for your business? It’s unlikely! Psychometric tests add value but does that mean that everyone within a pre-set number of personality types will be a good fit for your business? That’s also unlikely.
The simple truth is that, even with psychometric testing and rigorous interviews, people are still cycling out of contact centres and the same business challenges remain.
With only a minor tweak to talent processes, predictive talent analytics presents an opportunity to harness existing data and drive the business forward by making hiring recommendations based on somebody’s future capability.
But wait, it gets better!
Pick the right predictive talent analytics tool and this can be done in an interesting, innovative and intriguing way taking approximately five minutes.
Once the tool’s algorithm knows what good looks like, crucially within your business (because every company is different!), your talent acquisition team can approach the wider talent market armed with a new tool that will drive up efficiency and performance.
Picking the right hires, first time.
Consider this. Candidate A has solid, recent, relevant experience and good academic grades, ticking all the right hiring boxes but post-hire subsequently cycles out of the business in a few months.
Candidate B is a recent school-leaver with poor grades, no work history but receives a high-performance prediction and, once trained, becomes an excellent employee for many years to come.
On paper candidate A is the better prospect but with the fullness of time, candidate B, identified using predictive talent analytics, is the better hire.
Instead of using generic personality bandings to make hiring decisions, use a different solution.
Use predictive talent analytics to rapidly identify people who will generate more sales or any other measured output. Find those who will be absent less or those who will help the business achieve a higher NPS. Bring applicants into the recruitment pipeline knowing the data is showing they will be a capable, or excellent, performer for your business.
Now that’s an opportunity worth grasping!
Steven John worked within contact centres whilst studying at university, was a recruiter for 13 years and is now Business Development Manager at Sapia, a leading workforce science business providing a data-driven prediction with every hire. This article was originally written for the UK Contact Centre Forum
The value is greatest when companies harness the differences between employees from multiple demographic backgrounds to understand and appeal to a broad customer base. But true diversity relies on social mobility and therein lies the problem: the rate of social mobility in the UK is the worst in the developed world.
The root cause of the UK’s lack of social mobility can be found in the very place that it can bring the most value – the workplace. Employers’ recruiting processes often suffer from unconscious human bias that results in involuntary discrimination. As a result, the correlation between what an employee in the UK earns today and what his or her father earned is more apparent than in any other major economy.
This article explores the barriers to occupational mobility in the UK and the growing use of predictive analytics or algorithmic hiring to neutralise unintentional prejudice against age, academic background, class, ethnicity, colour, gender, disability, sexual orientation and religion.
The UK government has highlighted the fact that ‘patterns of inequality are imprinted from one generation to the next’ and has pledged to make their vision of a socially mobile country a reality. At the recent Conservative party conference in Manchester, David Cameron condemned the country’s lack of social mobility as unacceptable for ‘the party of aspiration’. Some of the eye-opening statistics quoted by Cameron include:
The OECD claims that income inequality cost the UK 9% in GDP growth between 1990 and 2010. Fewer educational opportunities for disadvantaged individuals had the effect of lowering social mobility and hampering skills development. Those from poor socio economic backgrounds may be just as talented as their privately educated contemporaries and perhaps the missing link in bridging the skills gap in the UK. Various industry sectors have hit out at the government’s immigration policy, claiming this widens the country’s skills gap still further.
Besides immigration, there are other barriers to social mobility within the UK that need to be lifted. Research by Deloitte has shown that 35% of jobs over the next 20 years will be automated. These are mainly unskilled roles that will impact people from low incomes. Rather than relying too heavily on skilled immigrants, the country needs to invest in training and development to upskill young people and provide home-grown talent to meet the future needs of the UK economy. Countries that promote equal opportunity for everyone from an early age are those that will grow and prosper.
The UK government’s proposal to tackle the issue of social mobility, both in education and in the workplace, has to be greatly welcomed. Cameron cited evidence that people with white-sounding names are more likely to get job interviews than equally qualified people with ethnic names, a trend that he described as ‘disgraceful’. He also referred to employers discriminating against gay people and the need to close the pay gap between men and women. Some major employers – including Deloitte, HSBC, the BBC and the NHS – are combatting this issue by introducing blind-name CVs, where the candidate’s name is blocked out on the CV and the initial screening process. UCAS has also adopted this approach in light of the fact that 36% of ethnic minority applicants from 2010-2012 received places at Russell Group universities, compared with 55% of white applicants.
Although blind-name CVs avoid initial discriminatory biases in an attempt to improve diversity in the workforce, recruiters may still be subject to similar or other biases later in the hiring process. Some law firms, for example, still insist on recruiting Oxbridge graduates, when in fact their skillset may not correlate positively with the job or company culture. While conscious human bias can only be changed through education, lobbying and a shift in attitude, a great deal can be done to eliminate unconscious human bias through predictive analytics or algorithmic hiring.
Bias in the hiring process not only thwarts social mobility but is detrimental to productivity, profitability and brand value. The best way to remove such bias is to shift reliance from humans to data science and algorithms. Human subjectivity relies on gut feel and is liable to passive bias or, at worst, active discrimination. If an employer genuinely wants to ignore a candidate’s schooling, racial background or social class, these variables can be hidden. Algorithms can have a non-discriminatory output as long as the data used to build them is also of a non-discriminatory nature.
Predictive analytics is an objective way of analysing relevant variables – such as biodata, pre-hire attitudes and personality traits – to determine which candidates are likely to perform best in their roles. By blocking out social background data, informed hiring decisions can be made that have a positive impact on company performance. The primary aim of predictive analytics is to improve organisational profitability, while a positive impact on social mobility is a healthy by-product.
A recent study in the USA revealed that the dropout rate at university will lead to a shortage of qualified graduates in the market (3 million deficit in the short term, rising to 16 million by 2025). Predictive analytics was trialled to anticipate early signs of struggle among students and to reach out with additional coaching and support. As a result, within the state of Georgia student retention rates increased by 5% and the time needed to earn a degree decreased by almost half a semester. The programme ascertained that students from high-income families were ten times more likely to complete their course than those from low-income households, enabling preventative measures to be put in place to help students from socially deprived backgrounds to succeed.
Bias and stereotyping are in-built physiological behaviours that help humans identify kinship and avoid dangerous circumstances. Such behaviours, however, cloud our judgement when it comes to recruitment decisions. More companies are shifting from a subjective recruitment process to a more objective process, which leads to decision making based on factual evidence. According to the CIPD, on average one-third of companies use assessment centres as a method to select an employee from their candidate pool. This no doubt helps to reduce subjectivity but does not eradicate it completely, as peer group bias can still be brought to bear on the outcome.
Two of the main biases which may be detrimental to hiring decisions are ‘Affinity bias’ and ‘Status Quo bias’. ‘Affinity bias’ leads to people recruiting those who are similar to themselves, while ‘Status Quo bias’ leads to recruitment decisions based on the likeness candidates have with previous hires. Recruiting on this basis may fail to match the selected person’s attributes with the requirements of the job.
Undoubtedly it is important to get along with those who will be joining the company. The key is to use data-driven modelling to narrow down the search in an objective manner before selecting based on compatibility. Predictive analytics can project how a person will fare by comparing candidate data with that of existing employees deemed to be h3 performers and relying on metrics that are devoid of the type of questioning that could lead to the discriminatory biases that inhibit social mobility.
“When it comes to making final decisions, the more data-driven recruiting managers can be, the better.”
‘Heuristic bias’ is another example of normal human behaviour that influences hiring decisions. Also known as ‘Confirmation bias’, it allows us to quickly make sense of a complex environment by drawing upon relevant known information to substantiate our reasoning. Since it is anchored on personal experience, it is by default arbitrary and can give rise to an incorrect assessment.
Other forms of bias include ‘Contrast bias’, when a candidate is compared with the previous one instead of comparing his or her individual skills and attributes to those required for the job. ‘Halo bias’ is when a recruiter sees one great thing about a candidate and allows that to sway opinion on everything else about that candidate. The opposite is ‘Horns bias’, where the recruiter sees one bad thing about a candidate and lets it cloud opinion on all their other attributes. Again, predictive analytics precludes all these forms of bias by sticking to the facts.
Age is firmly on the agenda in the world of recruitment, yet it has been reported that over 50% of recruiters who record age in the hiring process do not employ people older than themselves. Disabled candidates are often discriminated against because recruiters cannot see past the disability. Even these fundamental stereotypes and biases can be avoided through data-driven analytics that cut to the core in matching attitudes, skills and personality to job requirements.
Once objective decisions have been made, companies need to have the confidence not to overturn them and revert to reliance on one-to-one interviews, which have low predictive power. The CIPD cautions against this and advocates a pure, data-driven approach: ‘When it comes to making final decisions, the more data-driven recruiting managers can be, the better’.
The government’s strategy for social mobility states that ‘tackling the opportunity deficit – creating an open, socially mobile society – is our guiding purpose’ but that ‘by definition, this is a long-term undertaking. There is no magic wand we can wave to see immediate effects.’ Being aware of bias is just the first step in minimising its negative effect in the hiring process. Algorithmic hiring is not the only solution but, if supported by the government and key trade bodies, it can go a long way towards remedying the inherent weakness in current recruitment practice. Once the UK’s leading businesses begin to witness the benefits of a genuinely diverse workforce in terms of increased productivity and profitability, predictive hiring will become a self-fulfilling prophecy.
During this seasonal holiday a great many of us will start to create plans for the forthcoming New Year. We’ll think about events, occurrences and happenings of the year gone by and many will commit to doing things better next year.
Even though studies have shown that only 8% of people keep their New Year’s resolutions , we still make (and subsequently break) them. But the intention was there, so good work!
Have you ever stopped to think about the processes your brain undertakes to enable you to set your goals for the New Year? No? Well, luckily I’ve done that bit for you. To make that resolution you combined your current and historical personal data and produced a future outcome, factoring in the probability of success, based on your analysis. A form of predictive analytics, if you like!
Thinking about those things you did (and didn’t do) this year and predicting/projecting for next year.
So now you know what it involves and we are (loosely) agreed that you’re on board with predictive analytics, when better than to tell you now that 2016 is going to be the year when we really start to see the benefits of predictive analytics within our jobs and people functions at work.
I think it’s now universally accepted that when technology is used in the right way it can enhance and improve our lives across every sector and industry. Most fields have seen significant developments over the last 20-30 years as technology is increasingly used to further our understanding of the way things work, enabling us to make better decisions in areas such as medicine, sport, communication and, arguably, even dating (predictive analytics is used in all of those sectors by the way!) so why not use it to help us find the right people for the right organisations?
Did you know you no longer need a top-class honours degree to work at Google?
Every employee is put through their analytics process allowing the business to match the right person with the right team, giving each individual the best environment to allow their talent to flourish.
Companies such as E&Y and Deloitte are using different methods to tackle the same problem – removing conscious and subconscious bias attached to the name and/or perceived quality of the university where applicants studied.
Airlines, retail, BPOs, recruitment firms a growing number of businesses within these sectors are using or on-boarding predictive analytics to achieve upturns in profits, productivity and achieving a more diverse and happier workforce.
Predictive analytics helps us make people and talent decisions to positively influence tomorrow’s business performance without bias, so I guess the question is this – if it’s already a proven science to achieve results, why isn’t everyone doing it? How long until everyone starts to use, and see the benefits, of predictive analytics?
Data can be big and it can be daunting, but it can also be invaluable if you ask and frame the right questions and combine the answers with human knowledge and experience. You will be surprised by the insights, knowledge and benefits that your business can obtain from even the smallest amounts of data. Data you probably already collect, even if it’s unknowingly or unwittingly!
So as you start rummaging through your brain trying to remember where you filed your finest seasonal outfit(s) (that might just be me!), start prepping for the new year budgets, or start writing your list of resolutions let me help you frame a few questions:
Statistically, your personal New Year’s resolution is unlikely to be on course in 12-months time so instead, why not make a resolution to bring predictive analytics into your talent processes in the upcoming year?
You’ll see the benefits for years to come, and that’s a promise we can both keep.