The evolution of data platforms across the superannuation and investment management industry

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Sean Turner

Sean Turner

Founder | CEO | Fintech Recruitment Leader
September 25, 2024

 

Lets take a decade by decade look…

Data evolution has been driven by technological advancements, regulatory demands and the need for improved fact paced decision-making and real time member engagement.

There are so many systems nowadays like NeoXam, Goldensource, Fencore, Finbourne, ICS, Eagle/BNY, Matrix/Rimes, MarkitEDM, State Street Alpha and Factset all of which have unique offerings and all vying for your business – but how did we get to this point of evolution with such sophisticated product platforms in our industry?

As the industry has grown, data platforms have evolved from basic systems handling static data to complex, real-time, and cloud-based platforms capable of processing vast amounts of information.

This transformation has enabled superannuation funds and investment managers to make more informed decisions, optimise operations and enhance member services.

Let’s jump in and take a look at the journey through the ages……

 

1. Early Data Platforms (Pre-2000s): Basic Record-Keeping and Compliance

Data platforms in the superannuation and investment industry in the early days were relatively simple. They were primarily designed to meet regulatory compliance needs, such as tracking contributions and maintaining member account balances. These systems were limited in scope and functionality and the data was often siloed with little integration across different functions and different systems.

They were basic database systems for tracking member accounts, contributions and withdrawals. They were simple reporting tools and required manual data input and processing and limited ability to provide  real-time insights or analytics.

 

2. Introduction of ERP and Financial Software (2000s-2010): Integration and Automation

As superannuation funds grew larger and the investment landscape became more complex, the industry began to adopt enterprise resource planning (ERP) systems and specialised financial software. These platforms introduced greater levels of integration across team functions, helping to automate back-office operations and provide more accurate financial reporting.

These systems allowed better integration of member data, investments, and accounting and data warehouses began to emerge, enabling the storage of large volumes of historical data for more comprehensive analysis. The start of automating routine tasks (payroll, fund administration and regulatory reporting).

Challenge was that data remained largely batch-processed with limited real-time capabilities however integration improved

 

3. Shift to Data Analytics and BI (2010-2015): Data-Driven Decision-Making

With increased industry competition and an increased focus on investment performance and member engagement, superannuation funds began to adopt more advanced data analytics and business intelligence tools. The ability to generate actionable insights from data became a strategic priority.

This era saw the introduction of data analytics and business intelligence (BI) platforms for portfolio management, risk assessment, and performance analysis. Data visualisation tools emerged and advancements in data reporting occurred for reg compliance, risk management and member comms.

Issue is that platforms were still predominantly on-prem making scalability and flexibility difficult.

 

4. Advent of Cloud-Based Platforms and Big Data (2015-2020): Scalability and Flexibility

The adoption of cloud-based platforms and the ability to process big data marked a significant turning point in the superannuation and investment industry. Advancements in cloud technology allowed funds to scale their data storage and processing capabilities, while also providing flexibility in managing both structured and unstructured data.

Cloud allowed the reduction of on-prem data centre costs and big data technologies enabled funds to process vast amounts of information quickly.

Data integration became more seamless and we saw the growth of advanced analytics, machine learning and AI to automate portfolio management and optimise investment decisions.

There were still issues around data security and privacy and the migration of legacy systems to cloud platforms required significant investment

 

5. Real-Time Data and AI-Driven Platforms (2020-2024): Innovation and Predictive Insights

The most recent phase of data platform evolution has been driven by AI, machine learning, and real-time data processing. These technologies are enabling superannuation funds and investment managers to make faster more informed decisions and offer personalised services to members.

With the reduction in many superfunds and investment firms due to either acquisitions or mergers, and also the increased use of SMSF, means that funds are required to produce more significant returns for members.

AI and machine learning algorithms are used to predict market trends, optimise portfolios and automate risk, which as an SMSF member, you probably don’t have access to.

Real-time data platforms provide instant insights into portfolio performance, market conditions and member behaviour.

Personalisation at scale: Funds can now offer tailored advice and investment options to members based on their unique circumstances, powered by data analytics and AI.

ESG integration: Data platforms are also being used to assess environmental, social, and governance (ESG) factors, allowing funds to meet growing demand for sustainable investment options.

Regulatory compliance still remains a challenge as funds must ensure they adhere to evolving rules on data privacy and financial transparency. Business also need to ensuring that AI and machine learning models remain ethical.

 

What the future Trends in Data Platforms will look like: Decentralisation, Blockchain, and Enhanced Automation

Looking ahead, the superannuation and investment industry is likely to see further evolution in data platforms, driven by emerging technologies such as blockchain, decentralised finance (DeFi), and enhanced automation.

 

Technology advancements and the adoption of funds to utilise the best platforms fit for member purpose, transparency, reg compliance and security are going to be an interesting road ahead.

Kapital Consulting is a niche Fintech Recruitment Business specialising in Technology, Project Services and Data Recruitment across Australia. For more information connect with us on www.kapitalconsulting.com.au and follow us on www.linkedin.com/company/kapital-consulting

Fintech Recruitment Newsletter August 2022

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Technology-driven trends

The following trends will likely drive demand for skilled talent over the coming years. In a post-pandemic world defined by production challenges and political unrest, people continue to focus on digital solutions capable of shifting traditional models of distribution. These emerging trends lie at the intersection of data and employment:

Lifestyle and skills reappraisal

The great attrition of 2021 saw employees resigning in record numbers. While this trend continues in many markets, it has shifted its focus somewhat towards reappraisal and renegotiation. Employment numbers are healthy, with a fundamental mismatch between the demand for talent and the people supplying it.

41% of Australian workers and 40% of global workers say they might leave their jobs in the near future.

Technology has a huge role to play in this brave new world, as data skills and remote work arrangements enable fluid movements between locations and industry sectors.

Digital demand and distribution

The redistribution of banking continues to divorce traditional financial channels. Digital solutions remain resilient in the face of change, and emerging digital-physical hybrids offer a viable alternative solution. The global pandemic has accelerated a permanent channel shift, making data skills more in demand than ever.

In 2021, over 40% of core retail banking sales originated in the digital sphere, in an environment where total sales dropped by 10%, and digital sales rose 4%. This highlights the resilient nature of digital resources in tough economic climates.

As digital banking grows and data-led solutions overflow into other financial services, professionals with data skills will likely remain in high demand.

Alternative investment models

The wealth management industry faces altered priorities, with new delivery methods, offerings, and economic models requiring a new skills base. While the traditional longing for capital efficiency and recurring revenue is even more pronounced, technology plays a bigger role in achieving these things.

Customer demand for wealth management is expected to surge by $254 billion by 2030, which is double the revenue from 2021.

With ESG (environmental, social, and governance), private, and digital investments increasingly desired by new and existing customers, data expertise will retain its immense value in the years ahead.

Safety and security

As technology evolves to meet the demands of the brave new world, security remains a key concern. Moreover, the current global political landscape is accelerating existing trends, with the invasion of Ukraine and tensions with China increasing challenges and driving cybersecurity investment.

Cybercrime is expected to cost the world an estimated USD$10.5 trillion by 2025, a number that has grown from just USD$3 trillion in 2015. This highlights a growing need for digital security employment, which is relevant to fintech and most other industry sectors.

Cybercrime is a huge concern for banks and financial services organisations trying to protect customer data. The rate of demand has increased and so has the expectation on candidates skillsets.

We have seen huge demand across our Australian client base in all of the above areas and have further research to provide. Should you wish to find out more, please message us at info@kapital.com.au or team@kapital.com.au

 

Recruitment Readiness: Fund and Asset Managers Expanding their Footprint with Intelligent Data

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There is no shortage of articles published relating to AI and Big Data and much of that is predicated on the idea that AI will replace the jobs of many professionals (recruiters seem to have a target on their back here too).  It does seem a fully viable and end to end AI solution is far away.  Fund and asset managers are however looking to ways that intelligent use of Data and Analytics can add value to the business, empowering firms to better deploy their resources.

Applications of data and decision science has been a feature of many fund and asset managers for building quantitative investment and risk models and the scope of its application is now changing beyond these departments.  A growing number of firms have sought to invest in their data teams, working to enhance the capability of distribution teams by applying data science and advanced analytics to their distribution models.  This has seen organizations shift to a more targeted engagement model for working with clients and coordinating sales visits.  This has freed up much of the sales force to engage with higher priority and often more profitable opportunities.

Implementing Data

After seeing real results from implementing data driven changes, demand for data skilled talent is growing along with its adoption.  To roll out any such changes, companies need to review and enhance their Data Architecture, Data Governance and Data Quality Management processes.  The last 12 months has seen considerable growth in opportunities and wages for Data Architects, Data Scientists, Data Engineers, Data Governance Managers as well as project services candidates with strong data migration and management backgrounds.

Beyond the distribution teams, data is being used to make enhancements to middle and back office operations, allowing some of our clients to reduce costs through the increased process automation, better administration efficiency and automated systems for monitoring of crime and trade surveillance.  Accessing data and information has elevated in importance, as many legacy products do not provide the required capability to do advanced modelling.

Migration to new systems such as BlackRock’s Aladdin platform or SimCorp Dimension has been a feature over the last 12 months, with a number of other firms looking to make the transition over the next due to the better access to data and information. For a clearer indication on how we see the market salaries for Data skills, Data Science, Business Analysts, please contact shane.nash@kapital.com.au.

Market salaries

Overall, the market is offering rates for candidates with certain skills in systems or product knowledge.  Programs such as the CHESS Replacement program have attracted many Project Services BA’s and PM’s with knowledge of the equities trade life cycle.  Systems migrations to Aladdin or Dimension have provided attractive rates for BA’s and PM’s with legacy or incumbent platform knowledge.

Beyond this area we are also seeing investment going into Data Product Creation, with firms looking to make the most of incoming data or historical data.  Organizations with large amounts of unpublished data such as Stock Exchanges are rolling out data platforms known as a “Data Sandbox” allowing organizations to capture value in big data, and providing the opportunities for other organizations to run proprietary data into platforms to gather further insights.

All things considered, Fund and Asset Managers are ready to embark on the next stage of their journeys, with Data Driven changes enabling firms to realise efficiencies, savings and growing revenue, demand for data driven talent with knowledge of the buy side industry still valuable, however, relevant market knowledge may not be as mandatory to some other areas of the business such as sales, marketing and distribution.

For more information on current market and trends, please reach out to shane.nash@kapital.com.au or follow Shane on LinkedIn at https://www.linkedin.com/in/shane-nash-9b2231a0/

Recruitment Ready: A snapshot of the forces driving demand for data talent

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Technology is becoming a mandatory feature of regulation and changes, that is to say that data is empowering organizations to make better decisions, and at the same time it is being regulated and protected. While the use of Data is said to be one of the key drivers of an organisation’s success, using data incorrectly is not only expensive in opportunity costs, but also in potential fines for regulators when breaches are discovered.  It is mandatory that firms meet regulatory requirements and respond to changes. The effective use of data can empower an organisation to properly monitor, detect and respond to potential risk.  We’ve seen this impacting the wider technology recruitment market.

There has never been a better time for organisations to deploy technology and data to solve regulatory challenges.  Intelligent use of data is being deployed in many ways across organisations to garner results, with artificial intelligence, machine learning and data science a critical feature of many organizations decision process.  Data driven solutions are having a profound impact on how an organisation monitor activity, detect breaches and manage potential crime and regulatory risk to avoid loss and costly fines.  Not only can data assist in avoiding such costs, it can also make processes more efficient to better prioritise innovation and prioritise more transparency.  

Data Scientists are an integral piece to insurers, consulting firms and banks, with roles of actuaries, data analysts, pricing analysts and risk analyst changing.  As data savvy talent are providing more and more value to the organization where they ply their trade, it is understandable that the cost of attracting such talent is increasing.  For example, the cost of demanding the best Data Scientists to gleam new insights for a business is not only in the form of salary, it comes also in the form of benefits provided by the firm.  

The real cost comes in organisations having appropriate strategies to ensure that the data is captured, structured and shared appropriately.  A data transformation can require substantial investment in new systems, processes and implementation.  Changes to Data Governance, Data Pipelines, Data Quality and Master Data Management necessitate data focused Architects, Project Managers, Engineers and Business Analysts.  

Regulatory changes such as the General Data Protection Regulation (GDPR), codifying guidelines on data and its protection is a European Union initiative however the globalisation of the economy means that it is being adopted by any organisation who may interact with EU citizens.  Similarly, global accounting standards such as IFRS17, specific to insurers is being adopted by major firms globally, impacting insurance contracts and their underlying revenue, with a deadline set for early 2021.  

The impact of global initiatives and changes increases short-term (1 -3 years) demand of the Technology Staff with strong understanding of Data and experience in regulatory change, such as GDPR or IFRS17.  There is a further premium for those with such experience as well as strong business stakeholder skills to engage with business, compliance and marketing functions.  Currently, many of these SME’s are employed by the Top 4 consulting firms.  The positions below represent some of the placements we are seeing here at Kapital (for further information on salaries, bonuses and day rates for the below, please contact shane.nash@kapital.com.au).

Head of Data

Data Analytics Lead

Data Scientist

Data Architect

Data Engineer

Salary ranges can vary vastly due to the dependent on the specialised knowledge and skills of candidates.  Those with strong technology skills and the ability to engage with business functions effectively are proving to be the most in demand due to the additional value they provide.  Business acumen, influence and emotional intelligence to navigate complex change associated with such projects as data transformation and or regulation changers is a mandatory feature to the success of any change.  The consequence of this is that the overall cost is often greater for organisations seeking talent with such attributes.  Retention of such talent will also be a key feature of any organisation in the current market.  

As the use of data is such a powerful magnifier for all organisations, data talent, unlike many of the other areas of technology before are industry agnostic.  The result of this is that banks, consulting firms, insurers and fund managers are competing with the likes of Google or Atlassian to bring on the best talent.  The demand for data skills will likely continue to grow, so how organisations work with their best data talent to provide value to them will be a key feature.  

For more information on current market and trends, please reach out to shane.nash@kapital.com.au or follow Shane on LinkedIn at https://www.linkedin.com/in/shane-nash-9b2231a0/

How Artificial Intelligence (AI) and Machine Learning (ML) is affecting the recruitment industry

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Hey guys,

In this newsletter we’re going to discuss the ways Artificial Intelligence (AI) and Machine Learning (ML) are affecting the recruitment industry as well as how they affect client-side talent acquisition teams. Although AI and ML have brought lots of positive changes, it’s always a good idea to examine the possible downsides too. Examining both sides of the argument is the best way to prepare for the changes AI and ML could bring.

How Artificial Intelligence (AI) and Machine Learning (ML) are changing the recruitment industry

Both AI and ML are excellent for automating processes. There’s no denying that recruitment can feel a little time-consuming, especially when we’re in the earlier phases of sifting out unsuitable candidates. When AI and ML work to automate correctly, they give recruitment teams extra time to spend on the more important aspects of the hiring process.

Now, although all this automation is excellent in terms of efficiency, there are a few shortfalls. In order for AI and ML to automate successfully, they need to mimic the behaviours of those who would usually eliminate unsuitable candidates during the early phases of recruitment. AI and ML are technologies which have algorithms who’s sole purpose is to “learn” behavioural patterns, predict outcomes and relies heavily on the person imputing the data to ascertain what is good and reliable for its use. That person is likely to focus on what has worked well for the company in the past and if the company is trying to change their hiring process and aim to unearth niche talent pools of candidates with innovative, entrepreneurial ideas and new ways of thinking, then how would this work? As these platforms are based on historical search patterns and learned behaviour, once those behaviours are in place for the AI software to use, they’re hard to alter even when a company needs to change its approach to hiring.

AI and ML could potentially exclude highly-qualified candidates

Let’s say the behaviours inputted into autobots that exclude candidates and don’t look beyond basic flaws for human explanations. One example of this is excluding candidates with gaps in their CV’s. Unfortunately, this could result in the exclusion of highly-qualified, career rich and excellent candidates who’ve taken career breaks for secondments or parents returning to the workplace who have years of experience behind them.

The autobots filtering candidates are only as good as the person programming behaviour criteria

It’s always worth remembering that the autobots that filter candidates during a recruitment process are dependent on human programming. As such, if the person inputting behaviours isn’t overly familiar with the industry they’re representing, they could accidentally encourage inappropriate candidates through the recruitment process.

For example, in the tech world there are significant differences between a Python, Javascript front end developer, a Python Automation Programmer and a Software Engineer with basic Python. If the human providing the autobots with search patterns and behaviours doesn’t recognise this, AI and ML then becomes burdensome in the recruitment processes rather than efficient.

One of our best hires to date was a 24 year old with a long standing financial services client  of ours in Sydney. His profile was a mix of Cisco Networking, .Net Development, Text Mining, Social Scraping and some Python within DevOps. I can almost guarantee that he would not have shown up through the use of AI and ML for a Data Analysis SME (Subject Matter Expert) within a trading environment and this is where the inquisitiveness of the human mind over a machine prompted our team to meet him and 3 years later he is still one of their best hires.  

However, we can use AI and ML, we just need to use them wisely

At Kapital, we believe that there is a place in recruitment for AI and ML. However, we’re also of the mindset that we need to test software cautiously and provide the right level of human input to ensure it’s successful. This usually means finding software programs that are culturally appropriate and right for each unique recruitment process.

As an IT recruitment agency, we take a forward-thinking approach that uses software and human skills. Our consultants cover multiple technical disciplines for individual clients across industries creating “one touch points” for our clients and HR/Talent Teams, which means you can avoid the costly mistakes that come with poorly implemented AI recruitment processes.

Remember to follow our company page here and you can view our other newsletters here.

Till next time from The Kapital Team – Recruitment Made Simple

2018 IT Recruitment Newsletter for Finance, Prop Trading & Funds Management clients

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Hey guys and welcome to the 2018 addition of our Kapital IT Recruitment newsletter for Prop Trading and Funds Management clients. In this issue we will talk about the number of clients we service in each space, market movements, placements, what we seeing with salaries and also what we expecting for 2019.

Quick Market Summary across Financial Services

The financial services industry, right across the board in retail banking, superannuation and parts of insurance, continue to get hit very hard with the Royal Commission and as such the majority of hiring has been for Risk and Compliance and very specialist technologists to work on systems which can help with regulation and reporting around the issues they are facing. We see this continuing for at least the next 3-6 months

Tech and FinTech Start-ups have grown substantially over the last 12 months with a number of new entrants into the market. The big focus for the newcomers is around open source and cheap technology which can be leveraged across their platforms. For more established props, there seems to be more of a bullish push across DevOps and Automation to synchronize there trading activity

There are also a number of Financial Services clients across the board who are embarking on BigData Delivery and Greenfield Data Analytics builds to commercialize large data sets and leverage legacy system builds

So lets start with our Prop Trading clients. Kapital is on the panel for 5 Prop Trading clients across Australia and 1 in Hong Kong. We are also working with 2 new prop trading start-ups (one in Sydney and another in Melbourne) over the last couple of months who are seeing tremendous growth and solid backing. The prop trading space as always is about speed to market, efficiency and ease of market access. This year we have noticed a huge increase in the demand from prop trading clients looking for DevOps, Automation and Data Analytics / Visualization skillsets. The usual Network, Infra and Development positions are still being sourced as teams grow and 2 of our clients have moved offices this year to new upmarket and funky locations. There has also been a number of clients opening up new trading desks to target Asian exchanges with a lesser focus on the US and EU for now.

In terms of prop trading placements, Kapital has placed : 

  • Snr Exchange Connectivity/Market Links Engineer
  • Trading systems Apps support
  • DevOps Engineer
  • Desktop support
  • Python software engineer
  • Project Manager
  • C++ Developer
  • Tech support specialist (Network and Infra)
  • FPGA/VHDL/C++ Dev

Prop Trading salaries and threats

We are seeing Prop market salaries lift across most prop trading clients of ours in Australia. This is as a result of a number of job being turned down for tech start-up job offers in the market and high day rate contracts with banks working on Royal commission tech initiatives. The number of tech and FinTech start-ups across Australia has grown tremendously and has had an unprecedented effect on hires across not just prop trading but other industries too. We are seeing VC incubators moving start-ups from angel funding to Series A funding and now many start-ups who were assisted by the likes of stone and chalk or blue chilli are hitting the market in high volumes with financial backing. Start-ups are paying decent salaries with share options on top for the right skillsets. The market still has to be educated on the potentially high bonuses which prop trading clients have to offer. The length of the interview process is also proving to be a bit of a hurdle. All props are wanting top end candidates and therefore give them a lengthy tech interview process, start-ups on the other hand are only initiating 1-2 tech assessments then making a decision pretty quickly which is also a threat for props.

What we are seeing for 2019

There will be more hiring of similar skills but we feel the Automation and Data Analytics space will take off next year across many props. We will continue to face similar issues with start-up competitors and agencies on your panels need to ensure they are communicating the prop offering to potential hires better than ever

Moving onto Funds / Investment Management clients. Kapital is on the panel of 6 clients across Funds/Investment Management in Australia and also working closely with 2 others. This industry has seen a huge uplift of both temp-2-perm, converting contractors and also hiring of Data Analytics SMEs. There’s been a lot of new acquisitions of customers on-boarding and transitioning funds which is creating and cultivating a market of buoyancy which we see continuing through 2019. Funds and investment management along with many other industries are seeing a hike and review of their data Analytics platforms and how they can assist sales distribution teams on the road in front of customers with the use of Tableau, PowerBI, Snowplow or Alteryx tools which is exciting times ahead for funds management. We have also seen a number of tech initiatives across the funds industry in Australia from new Fund/OMS system builds, Reporting initiatives and new CRM system builds. None of our clients have moved locations this year and have all been hiring on a decent level across all technical disciplines.

In terms of Funds/Investment Management placements, Kapital has placed :

  • Program Manager
  • Technology Project Manager
  • Test Manager
  • Lead Tech BA
  • 3 x Tech BA’s
  • Front Office Equities Tech BA
  • 2 x Data Analytics SMEs
  • Change Manager
  • C#.Net Developer
  • Desktop Support

Salaries and threats

Salaries have been pretty consistent with no real rise other than Data Analytics and Visualisation SMEs (probably the 2nd highest pay to a head of tech across all industries). We tend to find candidates across funds have a genuine interest in funds and investment management and although we had a couple of offers being countered, we are seeing that generally candidates are loyal to staying within this space as the industry fund systems and exposure to full life cycle trade processes keeps it interesting. We are seeing a lot of new projects and initiatives starting up across our client base ranging from fund onboarding, analytics and CRM.

What we are seeing for 2019

The industry is showing no real sign of softening with regards to projects and hiring for 2019. We foresee more clients will come onboard the Data Analytics and Visualisation path and salaries in this space will continue to rise.

We hope you have received some useful information and if there is any other information you wish to see either now or in our next issue, please let us know.

Also check out our other startup newsletter here and remember to follow us on Kapital Consulting

Till next time.

2018 IT Recruitment Newsletter for startups

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Welcome back and we hope your 2018 year finished with a bang and that you have set yourselves up for 2019 success. One of the key elements for a successful startup, regardless of industry, is to make sure you have a unique value proposition and that you have a product or service which is truly fixing a need, gap in the market or an inherent business pain, something that is broken or in need of bettering or automating to make more efficient.

Some of the best and most interesting times in the life of a startup, although time consuming but really fun, is pitching for business which can take the form of getting in front of new potential customers but also in front of active VC and PE firms looking to invest in seeded funding.

So to that end make sure you have thought really carefully about your target audience and ensure you have a TAM (Total Addressable Market) of at least $20bn as VCs and Private Equity firms will be looking for 5×5 ratios which means 5% in a $20bn TAM would see their return on investment become $1bn which is the unicorn they all after and will make your proposition more appealing to them.

Your industries regulation is also a very important factor to think about. A prime example is FinTechs in the current climate of the royal commission where banks and financial institutions are getting heavy penalties levied against them and possibly not being trusted as much as they have in the past. I am not talking about what the current regulation is in your industry for 2018/2019 but what it could possibly look like for startups, FinTechs and online banks 5 or 10yrs from now. You do not want to be setting up a FinTech without thinking about this as there could be an equivalent Royal Commission of sorts for online banks and FinTechs 10yrs from now and I know this is tough to gauge but as a business startup director/owner you need to think about the possibilities of what this may look like and safe guard yourself and your business.

From a recruitment viewpoint, pre-Series A funding means you are probably like most, building an MVP (minimum viable product or Service) on a shoestring of a budget. It probably means too that you are just ensuring your website and portals are ready for external customers and clients to use and therefore hiring full stack web  developers. With Sydney and Melbourne now becoming the new silicon valley with companies like Atlassian, Campaign Monitor, Canva and many others getting in the Australian limelight on a global stage, sticking out is becoming more and more difficult. Sourcing the right candidates into your business will make a remarkable difference in the long run so use a recruitment firm who is flexible and not set in the traditional ways of how the recruitment industry works. You may not want to pay fees of any kind however we have witnessed how hiring the wrong talent at such an early stage can be detrimental in the long run to a startup.

Startups should look at as much media exposure as they can, VC and PE firms look at this closely when doing due diligence and using analytics tools to validate potential investment opportunities and are keen on companies with an already well placed media presence – check out

https://www.smartcompany.com.au/startupsmart/advice/pr-pro-how-to-get-media-coverage-startup/

We are always keen to hear from startups so if you looking for further information, need recruitment advice or looking for further market information, please give us a call. Till next time!

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