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How data is paving the path to net zero

Karl Breeze, CEO at Matrix Booking

The world is facing an existential threat: climate change.

As this threat looms larger than ever before, the race to achieve net zero is on. And this is not simply a race that any tortoise can win either. Time is not on our side.

Public and private sector organisations across the globe are now feeling the pressure to act in reducing their carbon footprints and better contribute to the  goal of net zero by 2050. According to research that was published at the World Economic Forum in Davos, more than a quarter (26%) of UK CEOs feel they are moderately or extremely exposed to the threat of climate change over the next 12 months.[i]

Yet, despite the urgent need for businesses to reduce emissions and move towards a more sustainable future, there are many asking how to achieve this ambitious target. The answer lies in the power of data.

The simple notion of leveraging data-driven solutions is fast becoming a critical tool in paving the way forward. Specifically, through resource management data, businesses can gain a deeper understanding of their emissions and identify areas for improvement. With it being harder for organisations to effectively manage what space they need – due to a surge in remote working – data has become the key to taking targeted steps in reducing their carbon footprint and implementing more sustainable practices.

The clock, however, is ticking and the race to net zero is one where businesses are starting to fall behind. It’s time to pick up the pace with the help of data.

Navigating the obstacles

Without accurate data, businesses across all sectors may not even have a clear picture of their environmental impact, making it impossible to identify areas for improvement. Not to mention, adapting to the changes of the working world  has presented a plethora of challenges, too.

Between an uncollaborative approach thus far, increasing costs and business leaders trying to account for where and how people work, those dealing with an organisation’s resources are being pushed to their limits  to maintain efficiency, let alone achieve net zero. Since the pandemic, underutilised space and energy price shocks have been driving real estate executives to reset their strategies by bringing a greater focus on space optimisation and reducing energy expenditure. To support these initiatives, firms are investing in technology to drive efforts and achieve ROI.[ii]

But the biggest challenge to even acquiring accurate data is funding. Implementing energy-efficient technology or data collection software, or even investing in renewable energy sources can require significant upfront costs. This may be a barrier for many, particularly in the public sector where budgets are restricted. However, you can’t manage what you don’t measure. Data provides a clearer insight into combatting these challenges and can lead to a long-term ROI. More importantly, it  supports an organisation on their journey to net zero.

Net zero to hero

As one of the most powerful tools in the fight against climate change, leveraging the right data can allow businesses to gain valuable insights into their energy usage patterns, identify areas for improvement and track progress over time. One element for organisations across every sector to consider is how employees now work.

The shift in how we work has led to  wasted resources and unnecessary carbon emissions in other areas, specifically office spaces. Therefore, utilising the right management data can allow firms to once more fully understand their physical resources. Data can reveal certain areas of an office that can be consistently over or underutilised, indicating an opportunity to adjust the layout or occupancy allowance to save energy and improve efficiency from a business perspective.

Furthermore, saving money on reduced office space and equipment can allow for greater investment into net zero initiatives, such as green leasing. Green leases serve as a means for decarbonising real estate and opens a more collaborative effort between landlords and tenants, all in support of net zero.[iii]

Whilst reducing the size of office spaces can enable companies to cut down on their carbon footprint, there is a catch. As more people work from home, the burden of emissions is being shifted to their households instead. The individual behaviours of staff, from energy use and travel to digital footprints and waste management, fluctuate wildly and is harder to measure and control, let alone enforce by the government. Therefore, it’s crucial to instil a company culture of sustainability by setting policies and providing support to help workers reduce their environmental impact while working from home.[iv]

The path less travelled

The term net zero is not something that should lead to eyerolls and sighs – it’s a term that should inspire change. Change towards a more efficient and cost-effective business model. Rather than considering net zero as a burden, business leaders should think of it as an opportunity to improve how they operate, decrease long-term costs and increase efficiency.

Despite uncertain short-term market prospects, many UK companies do plan to increase investment to reduce their carbon footprints. Almost half of business leaders (49%) surveyed by the British Property Federation plan to accelerate the delivery of their net zero programmes over the next 12 months.[v]

Now more than ever, data can be used to inform and drive business decisions to capitalise on climate action. However, achieving this will require a full-scale review of an organisation’s internal strategy, targeting precisely where they can reduce emissions and eliminate waste. With the application of data management systems, companies can leverage insights that not only align with their business objectives but also their net zero objectives, enabling them to better understand their environmental impact and accurately forecast reduction scenarios.

With mounting pressure from governments across the world as well as growing awareness amongst the general public, the race to net zero is one that business leaders need to pick up the pace on  before it’s too late.


[i] Green Retail World,PwC CEO survey: Businesses feel significantly exposed by climate change

[ii] Ben Readman, Verdantix, 2022

[iii] JLL, Green Leasing 2.0: Bridging the owner-occupier divide to deliver shared ESG value.

[iv] Harvard Business Review, Is remote work actually better for the environment?

[v] i-FM,Property looks to accelerate decarbonisation

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Business

Driving business success in today’s data-driven world through data governance

Source: Finance derivative

Andrew Abraham, Global Managing Director, Data Quality, Experian

It’s a well-known fact that we are living through a period of digital transformation, where new technology is revolutionising how we live, learn, and work. However, what this has also led to is a significant increase in data. This data holds immense value, yet many businesses across all sectors struggle to manage it effectively. They often face challenges such as fragmented data silos or lack the expertise and resources to leverage their datasets to the fullest.

As a result, data governance has become an essential topic for executives and industry leaders. In a data-driven world, its importance cannot be overstated. Combine that with governments and regulatory bodies rightly stepping up oversight of the digital world to protect citizens’ private and personal data. This has resulted in businesses also having to comply e with several statutes more accurately and frequently.

We recently conducted some research to gauge businesses’ attitudes toward data governance in today’s economy. The findings are not surprising: 83% of those surveyed acknowledged that data governance should no longer be an afterthought and could give them a strategic advantage. This is especially true for gaining a competitive edge, improving service delivery, and ensuring robust compliance and security measures.

However, the research also showed that businesses face inherent obstacles, including difficulties in integration and scalability and poor data quality, when it comes to managing data effectively and responsibly throughout its lifecycle.

So, what are the three fundamental steps to ensure effective data governance?

Regularly reviewing Data Governance approaches and policies

Understanding your whole data estate, having clarity about who owns the data, and implementing rules to govern its use means being able to assess whether you can operate efficiently and identify where to drive operational improvements. To do that effectively, you need the right data governance framework. Implementing a robust data governance framework will allow businesses to ensure their data is fit for purpose, improves accuracy, and mitigates the detrimental impact of data silos.

The research also found that data governance approaches are typically reviewed annually (46%), with another 47% reviewing it more frequently. Whilst the specific timeframe differs for each business, they should review policies more frequently than annually. Interestingly, 6% of companies surveyed in our research have it under continual review.

Assembling the right team

A strong team is crucial for effective cross-departmental data governance.  

The research identified that almost three-quarters of organisations, particularly in the healthcare industry, are managing data governance in-house. Nearly half of the businesses surveyed had already established dedicated data governance teams to oversee daily operations and mitigate potential security risks.

This strategic investment highlights the proactive approach to enhancing data practices to achieve a competitive edge and improve their financial performance. The emphasis on organisational focus highlights the pivotal role of dedicated teams in upholding data integrity and compliance standards.

Choose data governance investments wisely

With AI changing how businesses are run and being seen as a critical differentiator, nearly three-quarters of our research said data governance is the cornerstone to better AI. Why? Effective data governance is essential for optimising AI capabilities, improving data quality, automated access control, metadata management, data security, and integration.

In addition, almost every business surveyed said it will invest in its data governance approaches in the next two years. This includes investing in high-quality technologies and tools and improving data literacy and skills internally.  

Regarding automation, the research showed that under half currently use automated tools or technologies for data governance; 48% are exploring options, and 15% said they have no plans.

This shows us a clear appetite for data governance investment, particularly in automated tools and new technologies. These investments also reflect a proactive stance in adapting to technological changes and ensuring robust data management practices that support innovation and sustainable growth.

Looking ahead

Ultimately, the research showed that 86% of businesses recognised the growing importance of data governance over the next five years. This indicates that effective data governance will only increase its importance in navigating digital transformation and regulatory demands.

This means businesses must address challenges like integrating governance into operations, improving data quality, ensuring scalability, and keeping pace with evolving technology to mitigate risks such as compliance failures, security breaches, and data integrity issues.

Embracing automation will also streamline data governance processes, allowing organisations to enhance compliance, strengthen security measures, and boost operational efficiency. By investing strategically in these areas, businesses can gain a competitive advantage, thrive in a data-driven landscape, and effectively manage emerging risks.

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The Benefits of EV Salary Sacrifice: A Guide for Employers and Employees

As the UK government continues to push for greener initiatives, electric cars have become increasingly popular. The main attraction for both employers and employees is the EV salary sacrifice scheme.

By participating in an EV salary sacrifice scheme, both employers and employees can enjoy cost savings and contribute to environmental sustainability along the way! This article will delve into the specifics of how these schemes operate, the financial advantages they offer, and the broader positive impacts on sustainability.

We will provide a comprehensive overview of the mechanics behind EV salary sacrifice schemes and discuss the various ways in which they benefit both employees and employers, ultimately supporting the transition to a greener future in the UK.

What is an EV Salary Sacrifice Scheme?

An EV salary sacrifice scheme is a flexible financial arrangement that permits employees to lease an EV through their employer. The key feature of this scheme is that the leasing cost is deducted directly from the employee’s gross salary before tax and National Insurance contributions are applied. By reducing the taxable income, employees can benefit from substantial savings on both tax and National Insurance payments. This arrangement not only makes EVs more affordable for employees but also aligns with governmental incentives to reduce carbon emissions.

For employers, implementing an EV salary sacrifice scheme can lead to cost efficiencies as well. The reduction in National Insurance contributions on the employee’s reduced gross salary can offset some of the costs associated with administering the scheme. Additionally, such programmes can enhance the overall benefits package offered by the employer, making the company more attractive to prospective and current employees.

Benefits for Employees

1. Tax and National Insurance Savings

By opting for an EV salary sacrifice scheme, employees can benefit from reduced tax and National Insurance contributions. Since the lease payments are made from the gross salary, the taxable income decreases, resulting in substantial savings.

2. Access to Premium EVs

Leading salary sacrifice car schemes often provide access to high-end electric vehicles that might be otherwise unaffordable. Employees can enjoy the latest EV models with advanced features, contributing to a more enjoyable and environmentally friendly driving experience.

3. Lower Running Costs

Electric vehicles typically have lower running costs compared to traditional petrol or diesel cars. With savings on fuel, reduced maintenance costs, and exemptions from certain charges (such as London’s Congestion Charge), employees can enjoy significant long-term financial benefits.

4. Environmental Impact

Driving an electric vehicle reduces the carbon footprint and supports the UK’s goal of achieving net-zero emissions by 2050. Employees can take pride in contributing to a cleaner environment.

Benefits for Employers

1. Attract and Retain Talent

Offering an EV salary sacrifice scheme can enhance an employer’s benefits package, making it more attractive to potential recruits. It also helps in retaining current employees by providing them with valuable and cost-effective benefits.

2. Cost Neutrality

For employers, EV salary sacrifice schemes are often cost-neutral. The savings on National Insurance contributions can offset the administrative costs of running the scheme, making it an economically viable option.

3. Corporate Social Responsibility (CSR)

Implementing an EV salary sacrifice scheme demonstrates a commitment to sustainability and corporate social responsibility. This can improve the company’s public image and align with broader environmental goals.

4. Employee Well-being

Providing employees with a cost-effective means to drive electric vehicles can contribute to their overall well-being. With lower running costs and the convenience of driving a new EV, employees may experience reduced financial stress and increased job satisfaction.

How to Implement an EV Salary Sacrifice Scheme

1. Assess Feasibility

Evaluate whether an EV salary sacrifice scheme is feasible for your organisation. Consider the number of interested employees, potential cost savings, and administrative requirements.

2. Choose a Provider

Select a reputable provider that offers a range of electric vehicles and comprehensive support services. Ensure they can handle the administrative tasks and provide a seamless experience for both the employer and employees.

3. Communicate the Benefits

Educate your employees about the advantages of the scheme. Highlight the financial savings, environmental impact, and access to premium EV models. Provide clear guidance on how they can participate in the programme.

4. Monitor and Review

Regularly review the scheme’s performance to ensure it continues to meet the needs of your employees and the organisation. Gather feedback and make adjustments as necessary to enhance the programme’s effectiveness.

Conclusion

The EV salary sacrifice scheme offers a win-win situation for both employers and employees in the UK. With significant financial savings, access to premium vehicles, and a positive environmental impact, it’s an attractive option for forward-thinking organisations. By implementing such a scheme, employers can demonstrate their commitment to sustainability and employee well-being, while employees can enjoy the benefits of driving an electric vehicle at a reduced cost.

Adopting an EV salary sacrifice scheme is a step towards a greener, more sustainable future for everyone.

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Machine Learning Interpretability for Enhanced Cyber-Threat Attribution

Source: Finance Derivative

By: Dr. Farshad Badie,  Dean of the Faculty of Computer Science and Informatics, Berlin School of Business and Innovation

This editorial explores the crucial role of machine learning (ML) in cyber-threat attribution (CTA) and emphasises the importance of interpretable models for effective attribution.

The Challenge of Cyber-Threat Attribution

Identifying the source of cyberattacks is a complex task due to the tactics employed by threat actors, including:

  • Routing attacks through proxies: Attackers hide their identities by using intermediary servers.
  • Planting false flags: Misleading information is used to divert investigators towards the wrong culprit.
  • Adapting tactics: Threat actors constantly modify their methods to evade detection.

These challenges necessitate accurate and actionable attribution for:

  • Enhanced cybersecurity defences: Understanding attacker strategies enables proactive defence mechanisms.
  • Effective incident response: Swift attribution facilitates containment, damage minimisation, and speedy recovery.
  • Establishing accountability: Identifying attackers deters malicious activities and upholds international norms.

Machine Learning to the Rescue

Traditional machine learning models have laid the foundation, but the evolving cyber threat landscape demands more sophisticated approaches. Deep learning and artificial neural networks hold promise for uncovering hidden patterns and anomalies. However, a key consideration is interpretability.

The Power of Interpretability

Effective attribution requires models that not only deliver precise results but also make them understandable to cybersecurity experts. Interpretability ensures:

  • Transparency: Attribution decisions are not shrouded in complexity but are clear and actionable.
  • Actionable intelligence: Experts can not only detect threats but also understand the “why” behind them.
  • Improved defences: Insights gained from interpretable models inform future defence strategies.

Finding the Right Balance

The ideal model balances accuracy and interpretability. A highly accurate but opaque model hinders understanding, while a readily interpretable but less accurate model provides limited value. Selecting the appropriate model depends on the specific needs of each attribution case.

Interpretability Techniques

Several techniques enhance the interpretability of ML models for cyber-threat attribution:

  • Feature Importance Analysis: Identifies the input data aspects most influential in the model’s decisions, allowing experts to prioritise investigations.
  • Local Interpretability: Explains the model’s predictions for individual instances, revealing why a specific attribution was made.
  • Rule-based Models: Provide clear guidelines for determining the source of cyber threats, promoting transparency and easy understanding.

Challenges and the Path Forward

The lack of transparency in complex ML models hinders their practical application. Explainable AI, a field dedicated to making models more transparent, holds the key to fostering trust and collaboration between human and machine learning. Researchers are continuously refining interpretability techniques, with the ultimate goal being a balance between model power and decision-making transparency.

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