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Transforming tech performance: A brain-friendly growth approach

Performance reviews are a common practice, yet they’re often a double-edged sword. On one hand, they’re seen as necessary for growth and accountability. On the other hand, they can stir up more stress than motivation and dread than development. I’ve seen firsthand how traditional performance reviews can miss the mark in creating genuine peak performers.

This isn’t just about changing a system; it’s about understanding how our brains react to feedback and stress and how this understanding can revolutionise how we nurture talent in the tech industry. Here, I’ll dive deep into why the old-school performance review might be doing more harm than good and how we can shift gears to a more brain-friendly, effective approach.

The flaws in traditional performance reviews

In the tech business, where change is the only constant, clinging to traditional performance review methods can be akin to driving with the handbrake.

Stress and anxiety

The typical performance review is often a high-stakes, high-stress event. From a neuroscience standpoint, this is crucial. When our brains are under stress, they enter a fight-or-flight mode, which isn’t conducive to open, creative thinking or learning – essentials in the tech world.

This stress response can cloud judgment, stifle innovation, and even impact mental health. This mental blockade is the last thing we need in a field that thrives on cutting-edge ideas and agile minds.

Short-term focus

Performance reviews typically happen annually or quarterly. This system inherently encourages a short-term outlook. Teams sprint to hit immediate targets, often overlooking long-term innovation and growth – vital for survival in the tech industry.

Also Read: Neuroscience to the rescue: How startups can dodge burnout

It’s like focusing on the next step rather than the marathon. This short-termism doesn’t just limit progress; it can skew the bigger picture, leaving little room for sustained, meaningful development.

Limited feedback loop

The infrequency of traditional reviews means feedback is often outdated by the time it’s delivered. Technology moves fast, so what was relevant three months ago may not be relevant today. This delay in feedback creates a gap in learning and adjustment. It’s like trying to steer a ship based on where it was, not where it’s heading. In an industry that evolves daily, real-time feedback isn’t just helpful – it’s essential.

Neuroscience insights for better performance management

Taking insights from neuroscience can offer a fresh perspective on performance management, especially in the tech sector, where mental agility and innovation are necessary.

Brain-friendly feedback

Feedback is food for the brain – how we learn and grow. But the trick is in the delivery. Continuous, constructive feedback aligns with our brain’s natural learning processes. It’s like updating an app regularly instead of waiting for the annual version upgrade. This method keeps skills and strategies fresh and relevant.

The role of motivation

Neuroscience shows us that motivation is a complex dance of neurotransmitters like dopamine and serotonin. Traditional performance reviews often miss this dance entirely. They can create a fear of failure rather than a drive for success.

In contrast, a system that recognises and celebrates small wins can boost motivation, making employees more engaged, innovative, and willing to take the calculated risks vital in tech.

Creating a growth mindset

A growth mindset – the belief that abilities can be developed – is a powerful tool in the tech industry. Neuroscience supports this, showing that our brains are malleable and capable of change throughout our lives.

Performance reviews focusing on potential and learning opportunities rather than just outcomes encourage this mindset. It’s about shifting from a ‘judging’ to a ‘learning’ approach, which can unleash a wave of innovation and problem-solving abilities in tech teams.

Rethinking performance reviews – A new approach

Knowing what doesn’t work is half the battle. The next step is crafting a new, brain-friendly performance review strategy that resonates with the innovative nature of the tech industry. Here’s how we can turn a traditionally dreaded process into a powerful tool for growth and development.

Continuous performance management

Imagine replacing the annual review with a continuous conversation. This approach, like constantly updating software, keeps pace with the rapid changes in the tech industry. Regular, informal check-ins can provide timely feedback, allowing immediate course corrections and fostering a more responsive and adaptable workforce.

Employee development focus

Shift the focus from evaluating to empowering. Instead of a report card on past performance, make each review a session for skill-building and personal growth. This can involve setting individual learning goals, encouraging professional development, and offering opportunities for new challenges. It’s about building a bridge from where the employee is to where they can be, leveraging their unique strengths and interests.

Also Read: 10x your results: The blueprint for building high-performing teams

Implementing the change – Practical steps

Revamping the performance review system is no small feat. But with the right approach, it can be a game-changer. Here’s a practical blueprint to roll out this transformation effectively.

Leadership buy-in

Change starts at the top. To shift gears on performance reviews, first, get the leaders on board. This involves showcasing the benefits of a continuous, development-focused approach – how it aligns with business goals, drives innovation, and enhances team dynamics. It’s about clearly showing the ‘why’ behind the change, ensuring leadership understands and champions the new direction.

Training and development

Once leadership is on board, focus on training managers and teams. This isn’t just about using new tools or processes; it’s about fostering a new mindset. Workshops, training sessions, and regular discussions can help embed this new approach in the company culture. Equip managers with the skills to give constructive, continuous feedback and empower employees to take charge of their development.

Measuring success

To ensure the new system is working, set clear metrics for success. This might include employee engagement scores, innovation metrics, or feedback quality. Regularly review these metrics to see what’s working and what needs tweaking. This is a continuous improvement process, much like software development – always iterating, always evolving.

In conclusion

By embracing a continuous, development-focused approach grounded in neuroscience, we can transform a traditionally stressful process into a powerful catalyst for innovation and growth.

This way not only aligns with the dynamic nature of tech businesses but also taps into the human potential of their teams. The future of performance management is about empowering, not just evaluating.

It’s time to make this shift and watch our tech teams soar to new heights of achievement and satisfaction.

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic

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2023 is the year we are working closely with AI. But what is next?

If we were to describe the global tech industry in 2023 with just one phrase, it would be artificial intelligence.

Its widespread popularity began in late 2022 when ChatGPT was launched by OpenAI and became an instant sensation with its ability to generate a wide array of content, from travel itineraries to codes for computer programs. Since then, the global tech industry’s centre of the conversation shifted from other popular verticals such as blockchain.

AI startups in many places around the world announced funding rounds; businesses have also accelerated their experimentation with the technology. Even the dramatic firing (and return) of OpenAI CEO Sam Altman was not enough to deter anyone from the verticals.

As we move towards the end of the year, we have one big question hanging in our mind: What is coming up next?

AI in Asia

According to data compiled by data analytics company AltIndex.com in recent coverage by e27, Asian AI companies are reported to have raised the second-highest value in funding rounds, or over US$96 billion.

Also Read: How Transparently.AI uses Artificial Intelligence to detect accounting manipulation, fraud

“Despite the VC funding slowdown, the strong fundraising activity continued this year, tuning 2023 into the second-best year for fundraising in the AI market’s history after 2021.”

This number is also expected to continue growing in 2024 as investors give more attention to AI companies around the world.

Outside of funding, Southeast Asian (SEA) countries such as Singapore continue to put AI on their national agenda with the announcement of the National Artificial Intelligence Strategy (NAIS) 2.0 framework, which includes a tripling of its AI expert pool.

With this development, e27 predicts that AI will continue to dominate the conversation in 2024. However, there will be a heightened focus on its security and regulatory aspects.

This was affirmed by the insights shared by Bee Kheng Tay, President of Cisco ASEAN.

“In 2024, businesses in ASEAN will have to grapple with how they can weave AI into their organisations effectively, whilst taking advantage of other emerging trends impacting the business landscape,” she writes in a commentary.

Tay stresses that a movement towards responsible and ethical AI is gaining momentum.

Also Read: These Artificial Intelligence startups are proving to be industry game-changers

“Governance, underpinned by trust and transparency, is at the forefront of this movement. While the transformative benefits of AI are evident, navigating its adoption comes with inherent risks. Organisations need a robust framework of policies and protocols to guide the ethical and responsible management of data and AI systems,” she says.

“In ASEAN, the need for enhanced AI governance is evident. Only 36 per cent of organisations claim to have highly comprehensive AI policies and protocols in place, and a concerning 21 per cent lack systematic mechanisms to detect data biases. Recognising the evolving regulatory landscape, companies must stay updated on local and international regulations. Implementing internal policies that address data privacy, security, and the ethical use of AI technology is imperative. This includes embedding security, privacy, and trust by design processes throughout the innovation lifecycle of AI applications.”

If we look at the Web3 vertical, which was the main theme of 2022, the progress we saw in 2023 is that industry players are becoming more open about working with regulators in the region.

There is a greater awareness of how far they can go by collaborating instead of competing—we saw similar changes in the fintech ecosystem years ago as more banks opted to work together with startups.

Image Credit: RunwayML

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