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The challenge: Reconciling start-up agility with civil service structure

Start-ups flourish because they prioritise speed, empowerment, and creativity. They’re built to experiment, fail fast, and learn. The civil service, however, exists to ensure public trust, enforce rules, and deliver stability—values that inherently discourage risk and unproven methods. Attempting to transplant start-up methodologies wholesale into the civil service risks either diluting the essence of what makes start-ups effective or undermining the critical functions of government.

This is where Collective Intelligence comes in. By tapping into distributed decision-making and diverse networks of knowledge, the civil service can retain its core principles while integrating the dynamism of start-up culture. Collective Intelligence harnesses the insights of a broad spectrum of contributors—citizens, experts, technology, and even artificial intelligence—to co-create solutions that are innovative, inclusive, and practical.

‍Three insights for embedding start-up energy in the civil service

1. Stop centralising decision-making

Start-up culture thrives on empowerment, decentralisation, and the principle that the best ideas often emerge from unexpected places. Contrast this with the civil service’s tendency to consolidate decision-making among a select group of senior officials. While this ensures accountability, it also limits the scope for grassroots innovation.

To infuse agility, the government could embrace decentralised approaches where diverse actors – whether AI agents, community groups, or sector-specific experts – are empowered to contribute insights. By integrating these inputs through Collective Intelligence platforms, decision-making can become faster, more responsive, and inclusive, while still maintaining the necessary oversight and accountability frameworks.

For instance, imagine teams across departments autonomously piloting new digital tools to address localised challenges. AI systems could aggregate their findings, identify best practices, and propose scalable solutions – all without bottlenecks from excessive central oversight.

2. Tap the wisdom of the crowd

Traditional policymaking processes often rely on a relatively small pool of advisers, limiting the diversity of perspectives that inform decisions. What if these processes could instead draw from a much larger, more representative pool of stakeholders? By leveraging the principles of Collective Intelligence, the government could expand the range of contributors to include sector-specific experts, affected communities, and even generative AI trained on relevant data sets.

Picture this: a policy on climate change is not only drafted by civil servants but iteratively refined through a platform where environmental scientists, energy companies, grassroots activists, and AI agents collaborate. Collective Intelligence tools could synthesise these inputs, ensuring that final policies are not only robust and innovative but also reflective of real-world complexities.

3. Reward experimentation

One of the most defining aspects of start-ups is their embrace of failure as an essential part of the learning process. This approach, however, is virtually absent in the civil service, where even minor missteps can erode public trust and lead to significant political fallout.

To create a safe space for experimentation, the government could adopt “sandbox” environments—protected spaces where teams can test new ideas, technologies, or policies without the risk of public failure. These sandboxes could be powered by Collective Intelligence, allowing for iterative development supported by cross-departmental collaboration and advanced AI tools. By framing failure as a pathway to better solutions, the civil service can foster a culture of innovation without compromising public confidence.

Building a collaborative, intelligent future

As someone who has worked extensively on digital transformation in highly regulated sectors, I’ve seen first-hand the limitations of trying to innovate within traditional frameworks. What the civil service needs isn’t more layers of bureaucracy disguised as innovation but systems and cultures that allow problems to be reframed collaboratively. By leveraging the diverse perspectives of citizens, experts, and intelligent tools, the government can create solutions that are not only effective but also deeply resonant with the needs of society.

The journey to instil start-up energy into the civil service won’t be easy, but by embracing Collective Intelligence, the UK government has a unique opportunity to lead the way in modern, participatory governance. The result could be a civil service that is not only more agile and innovative but also better equipped to tackle the complex challenges of the 21st century.

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But, what does that mean in reality?

The week does include in-person conferences and awards and meet-ups, but the vast majority of the week’s content remains online and I believe this remains its secret sauce. 

Why do I believe that an online programme is better than an in-person event? Well I don’t always, but whilst a few days in London or Lisbon is a great experience and for those needing to build relationships and networks with new customers is vital, for the vast majority of us this remains an impracticality. 

Also, these big “national” and “international” in the room events are usually about big tech and those with the biggest budgets fund them and drive the agenda. “No budget, no play” as they say. It can be a format that reinforces the status quo and excludes many for whom hotels and travel is either not a practical option or not allowed by their employer. 

DLWeek is nationwide and all about those who know, sharing with those who need to find out, irrespective of where the speaker is based or the audience live. 

By making the vast majority of Digital Leaders Week online and virtual we maximise that opportunity and let our audience participate from their home desk. 

However, the challenge is to organise it well and after six attempts we now feel we have got it down to a fine art. It’s about great user experience for the speaker and for the delegate alike.

Offering to give a talk is a matter of a few clicks. Our editorial team test talks for quality before loading it up and choosing a time during the week that works for the speaker. With so many talks happening in a five day period, we try hard to make sure talks on the same topics do not coincide, but with over 250 speakers that’s not easy.

What is so great is the variety. With no barrier of cost to give a talk for speakers from government, charities and academics (we do often charge a small fee to the private sector) we get extraordinary speakers offering up real knowledge, best practice and new ideas. Many do it exactly because there is no barrier for the audience to participate and they like the inclusion.

This also means that, free of the “tyranny of geography”, speakers from the North of Scotland or valleys of Wales, or experts in the more obscure areas of digital transformation expertise can find a platform and national audience that needs their know-how.

However, making all 200 plus talks easy to find, book into and experience from your home desk, is about great UX and here I believe we have it.

The key is to make all talks accessible through a single one time registration. We make the talks that matter to you findable through listing them by time, speaker and topic. You can click on everything you want to take part in and once clicked onto, we add them to your personal calendar.

We also get our partners like DWP Digital to create badges that delegates can earn during the week. Effectively, they do the heavy lifting for them by choosing, in their case, the best ten talks about Data. 

During the Week delegates start their day with an email reminding them what they booked into and we send them extra alerts just before each talk. In the evening each day they get the recordings of everything booked into that day and after the week, the whole programme is available on-demand.

All of that would just be a week of webinars, was it not for the Digital Leaders Community itself. For us and them, DLWeek is a key part of a whole year full of activity and knowledge sharing. Those who speak are seen as adding to the community and participation and feedback for them seen as part of the community’s dna. This community aspect takes it beyond just being individual talks to a collective sense of building the UK’s digital confidence together.

That’s why, for this 12th Digital Leaders Week, I shall be staying home. 

If you would like to give a talk at DLWeek 14-18 October 2024 please submit here 

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These days, we seem to mean a lot more than Ward Cunningham did when he first coined the term in 1992. As Cunningham has helpfully clarified, he was specifically referring to coding choices made in the absence of full information – information that could only be gained by releasing a version of the code and learning how it was used. The technical debt incurred in this way could be paid down by refactoring the code as its full feature set became apparent – or could be ignored, at the risk that, just as with financial debt, servicing the debt would become all-consuming: developers would spend all their time navigating an ever more complex code base, full of incrementally added and contradictory concepts.

The idea of technical debt is powerful, and intuitively appealing to anyone who has developed software, or managed or sponsored a software development project. It is so appealing that we have used it in many more adjacent contexts. I have seen the term ‘technical debt’ applied to:

• Poor coding choices made with the intention of tidying up later (the practice which prompted Cunningham’s helpful clarification).
• Systems where hardware and software upgrades have routinely been ignored.
• Systems which have become regarded as ‘legacy’ (whatever that means), and which everybody would like to get rid of.
• Choices made which contravene architectural standards (whether those standards are useful or not).
• ‘Shadow IT’ systems which have been developed in the absence of professional software practices, and brought into the scope of the technology team.

I don’t believe that this widespread use of the term ‘technical debt’ is bad in itself. The core concept – that we sometimes have to make compromises that we must pay for later – is sound, broadly applicable and has explanatory power. However, I also believe that casual misuse of the term is dangerous, and leads us to excuse technical debt or accept its persistence.

Credit, the financial concept on which technical debt is based, is a useful tool which makes our economy possible. It enables us to move value across time and space. It enables me to buy something today which I will not be able to afford until tomorrow.

But it is easy to let the habit of spending on credit get out of control, especially when you can’t see the balance and you don’t know the interest rate. Once the concept of technical debt as a conscious choice exists, it is easy to incur debt for bad reasons: the project manager only cares about this release, so we’ll test minimally and manually; the sponsor really likes this particular technology product and, well, they’re the boss; the release schedule is full this year, so we’ll push the upgrades to next year. Putting the consequences on the technical credit card becomes a habit.

Furthermore, just as most companies usually require some form of borrowing, to invest, or grow, or acquire, we can easily fall into the trap of thinking that technical debt will always be with us. Our systems will always be a bit out of date; our architecture will always be a bit of a mess; our code base will always be a bit difficult to understand. Paying the interest on this persistent debt becomes part of what we do, until it consumes or overwhelms us.

The form of technical debt that Cunningham originally wrote about was not an excuse and was not intended to be persistent: you cannot know everything about the desired behaviour of your system until you make a release, and the experience of that release will teach you that you would have done things differently if you’d had all the information. Small amounts of technical debt, paid down quickly, are an inevitable part of software development. But this is not how most organisations think about or manage their technical debt.

Perhaps one way to help us stay in control of technical debt is to ask ourselves: who are we borrowing from? In one sense, just as with all credit, we are borrowing from our future selves. But this doesn’t fit the metaphor: with true debt, there is always a lender, and it is that lender who makes us pay. I think that when we incur technical debt, we are borrowing from the systems we are building and the architectures we create. And, if we are not careful, they certainly make us pay.

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As I think back on my time leading fundraising for a nonprofit, I’m not sure I considered myself much of a data leader. But, in truth, I was utilizing data every day to steer decision-making that would ultimately positively impact our organization’s health and growth. In fact, I was likely the heaviest user of organizational data.

Data powered everything in my day-to-day, from helping me segment and send targeted messaging to donors based on preferred channels, to analyzing past giving patterns to predict when they’re likely to give again, to predicting future grant funds and event revenue so that I could plan accordingly. Data helped me track campaign performance and donor engagement, as well as show donors and foundations how their funds were impacting service population outcomes. I was able to tell incredible stories of long-term impact because of data collection and analysis. And, had I ignored what my data was telling me, I would have been aimless—instead defaulting to random gut-based decision making, unable to back up my decisions or make a case to shift away from long-held strategy beliefs.

No matter your job, data plays a critical role in both your individual success, and in the success of the organization as a whole. From influencing day-to-day decisions to informing long-term strategy, data is an essential resource to tap. And in today’s world, embracing data leadership is no longer optional — it’s a necessity.

The imperative of data leadership

In today’s digital age, data is generated at an unprecedented rate. Every interaction, transaction, and process produces valuable data points that, when analyzed correctly, can provide incredible insights, including opportunities for cost savings and new revenue streams. A McKinsey Global survey found that respondents at high-performing companies “are three times more likely than others to say their data monetization efforts contribute more than 20 percent to company revenues.”

Organizations that leverage data effectively are better positioned to outperform their competitors. A recent found that data-driven organizations are 23 times more likely to acquire customers, six times as likely to retain those customers, and 19 times more likely to be profitable. In an era where competitive advantage is fleeting, the ability to swiftly interpret and act on data can be the difference between success and failure.

Data leadership across business functions

Let’s dive into three business functions and how they benefit from harnessing their data.

• Marketing: Personalization is no longer a luxury; it’s an expectation. By analyzing data from various touchpoints, marketers can gain a 360-degree view of their customers. This includes understanding their preferences, behaviors, and pain points, which in turn enables the creation of highly targeted and relevant marketing campaigns. Data allows marketers to tailor their messages to individual customers, improving engagement and conversion rates. According to McKinsey, companies that thrive at personalization earn 40% more money from these activities than the average competitor. What’s more, data-driven marketing provides clear metrics to measure the return on investment (ROI) of marketing campaigns. This allows leaders to allocate resources more effectively, optimizing marketing spend for maximum impact.
• Sales: In sales, data is a powerful tool for identifying opportunities, improving customer interactions, and forecasting future performance. Data can help sales teams prioritize leads based on their likelihood to convert. By analyzing past interactions, demographics, and behavioral data, sales leaders can create predictive models that identify high-potential leads. Data-driven forecasting models can provide sales leaders with insights into future sales trends, helping them make informed decisions about resource allocation and target setting.
• Strategy: Strategic decision-making is inherently data-driven. Leaders who incorporate data into their strategic planning can make more informed, forward-thinking decisions that drive long-term success. Data provides valuable insights into market trends, competitor activities, and customer needs. Strategic leaders can use this information to identify opportunities for growth and innovation. When it comes to team performance, data-driven performance measurement allows leaders to track progress against strategic goals. Key performance indicators (KPIs) and dashboards provide real-time insights into how well the organization is performing and where adjustments may be needed.

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Sometimes it feels like I’m stuck in the past. Too often when faced with a new challenge, my first inclination is not to face forwards with an open mind, but to look backwards to try to extract lessons from previous experiences that help me to describe and understand it. And while relying on what’s happened before can be very helpful in many circumstances, it also brings the real danger of being too blinkered, biased, or backward. I can’t work out if my past experience is my greatest asset, or the main anchor that holds me back.

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Plan A – The agile approach

We have recently been working on developing a new government digital service. If you are familiar with government project cycles, then you will know that there are five stages to product delivery; discovery, alpha, beta (split private beta, public beta), live and retire. For simplicity, we haven’t included retire in our diagram below.

We began the project using this approach. The ‘discovery’ and ‘alpha’ phases were supported by research work; exploring the client’s problems, understanding the users and their needs and establishing how the system is going to work. Our plan was to continue with research into ‘beta’ so that we could obtain live user feedback during the product deployment. You’re expected to use agile delivery throughout the lifecycle of a service. It was during the alpha phase that our problems started. We used a scrum approach, delivering in two-week cycles and began to notice that the research was being stifled in favour of delivering something within the sprint. It wasn’t working. We needed a plan B.

When Plan B is needed

Agile became popular in the 2000s, and it felt like a revelation for the industry. Gone were the days of drawn-out projects where you would only see results right at the end of the project. With the agile methodology, success was measured by quality outputs during the delivery phase. An agile approach was great for creating software where the user could access revised and improved versions at a regular cadence. It also put developers in charge of their own workload, and it brought stakeholders closer to the action since they were involved in the day-to-day work.

Industry experts in the UX space saw a big flaw. An agile approach doesn’t work so well for research. With research, the length of time it takes is dependent on so many things. It depends on when the users are available. It depends on how much data you get. It depends on what outputs you need to create. All of these factors are unknown at the beginning and may not fit into the two-week sprint timeframe. So, a new approach was required to help make agile more UX-friendly, and that evolved into what we now know as dual-track agile.

Plan B – Dual-track agile

The spirit behind dual-track agile is that the entire team engages in two distinct work tracks; research and delivery. The research track utilises the team’s expertise to produce, test, and validate ideas that help strive towards a solution. The delivery track takes that validated idea and converts it into a usable product version within that sprint.

Everyone’s a researcher

From a research track perspective, it’s important to be versatile. Not every design cycle has to create something tangible; it may be used just to validate, or even invalidate an idea. Some loops can be short, others need to be larger. The dual-track approach makes space for the flexibility and versatility that the research track requires.

We learned how to focus on what’s viable, not what’s perfect, which helps shorten the iteration cycles. It is important to involve the whole team within the research track. For example, we had our technical architect support us in co-design sessions with users and stakeholders. Developers and testers would join us in user research sessions.

Dual-track agile isn’t perfect

No method is perfect. We encountered some key challenges. There were four large ones:

1. Getting one team into the two-track mindset isn’t easy

With dual-track agile, all the team work on both tracks. This was a tricky mindset for a few reasons; reluctance to donate time, context switching is hard work and there was apprehension around someone critiquing an area that wasn’t their responsibility, such as design or development. We overcame these barriers by introducing some ground rules to encourage constructive ideas and feedback within a safe space. We introduced technical refinement sessions to give everyone time to think and iterate. And we added visual reviews and UX reviews as checkpoints in the development process for the designers to review and discuss the progress whilst ensuring that the planned output still met the desired need.

2. Getting the two tracks to work coherently towards the product vision

Dual-track agile is a fast-paced method. It kept the project and team focused by creating and monitoring a roadmap for delivery. And it empowered us to be disciplined with what was needed now and later.

3. Scope creep

When you involve more people, you generate more ideas, which can lead to scope creep. Consciously sticking to the roadmap helped, but we needed something more. So, we adopted a ‘good enough’ mindset. Every solution was challenged as to whether it was ‘good enough’ to solve the problem. And if it was, we asked, ‘does it fit the roadmap’? If we got two yes’s we knew we could implement it and move on.

4. The ‘good enough’ mindset is hard to get into

Triad has a track record. Clients from ten years ago are still using us today. We work hard to hire brilliant people. We are award-winning. We want perfection. At first, ‘good enough’ felt like we were settling for second best. But we realised that ‘good enough’ isn’t settling for anything at all. In reality, ‘good enough’ is about delivering excellence rather than searching for perfection.

Reaping the dual-track rewards

There were lots of benefits to the dual-track approach. The stand-out benefits were:

1. User-centric design, informed by technical experts, ensures that you create something that is grounded in reality

That’s because you’ve tested something that has been validated by the user needs and built within the constraints of technology.

2. Structured creativity creates stability and confidence

Because the entire team is involved in the research track and delivery track, what you end up with, is the ability to create something that is truly deliverable. This is helped by the ‘good enough’ mentality in that you have solved lots of small problems with simple solutions that collectively end in an intuitive product that isn’t trying too hard. It doesn’t put demands on the user to ‘over-think’. Therefore, everyone has confidence in it.

3. Dual-track agile encourages a forward-thinking approach

Fostered collaboration increases dialogue between your specialists across the team. It creates a better overall decision-making process. It forces the delivery workstream to adopt a forward-thinking approach and be mindful of what problems may be on the horizon rather than waiting for them. It also helps validate the research and prevents developers delivering something that doesn’t solve your client’s problem.

It’s a wrap!

Now, in public beta, we can safely say that the dual-track agile approach worked for us. It was the ideal method for a heavy UX project that kept the scope contained within a tight timeline. We have some great learnings. It’s important to adapt your methods as the project goes on. It is ok to veer from the original Agile principles,or from what everyone else does. You’re unlikely to always get it right the first time. And that’s ok. Agile your agile process. Iterate your iteration process. And go on that journey to let research inform delivery at every sprint.

Originally posted here

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The role of digital leaders in shaping sustainable practices and driving positive change has never been more imperative. The gathering of such a great bunch of individuals at the Trampery was a testament to the commitment towards a more sustainable future, and for me and many others I spoke to created such a sense of pride in the strides the UK is making towards a better world.

Reflecting on the day, several key points I wanted to share

Foremost among them was the awe-inspiring showcase of finalists and award winners, whose contributions warrant attention and recognition. I highly recommend exploring their work further, which can be found here. I especially wanted to congratulate Matt Adam who was awarded the Founders Award after a really endearing speech about Matt and both of their founder journeys from Gori Yahaya. 

Addressing the ‘E’ in ESG, CGI’s Head of Sustainability, Mattie Yeta set the tone with a poignant discussion on the significance of data in driving sustainable development. Her wealth of experience in this arena provided compelling insights into emerging focal points from very comprehensive slides. A notable highlight was the panel discussion featuring Dr. Maria Carvalho of NatWest, shedding light on the bank’s proactive approach in supporting sustainable practices among the UK’s SME sector. Dr. Carvalho underscored the pivotal role financial institutions play in facilitating the transition to a net-zero economy, emphasising the importance of customer engagement and the provision of tailored tools and services. Dr. Carvalho’s presentation showcased NatWest’s initiatives, including empowering SMEs to track their carbon footprint and that of their supply chain partners which was impressive to see. 

Andrew Morris, VP at aql, furthered the conversation by elaborating on the utilisation of “Good Energy,” offering valuable insights into aql’s pioneering efforts in this area. Julie Furnell, CEO of Mobilityways, shared compelling insights into the environmental benefits stemming from remote working, particularly in achieving Zero Carbon Commuting.

Then onto the ‘S’ in ESG, Duncan Parker, MD of The 44 Group, delivered a keynote on the Purpose Revolution, emphasising the role of investment in driving Sustainable Development Goals (SDGs). Then the panel, featuring Moses Setler of Screen Share and Becky Burgess of Rochdale Borough Council, highlighted the transformative potential of digital inclusion, with an incredible story on the impact of refugees and community support initiatives.

Julia Chippendale from We Are Group advocated for a unified “one front door” approach supported by technology to streamline support services for vulnerable people, exemplifying this through partnerships such as the excellent one with Lloyds Banking Group to provide digital skills assistance from the comfort of people’s homes.

Turning to the ‘G’ in ESG, discussions centered on governance amidst societal challenges. David Kempster shared insights into property-level governance, while Mariam Chrichton, CEO of 7Sataya, articulated the importance of global technology solutions in fostering positive impact.

Louise Campton of Primary Goal shared an inspiring narrative of leveraging training levies for continuous professional development (CPD) in schools. We then had Gori Yahaya of Upskill Universe and Elizabeth Vega, CEO of Informed Solutions, engaged in a thought-provoking dialogue on organisational culture management, which from what I could see really resonating deeply with the audience.

Finally, what a team!  special acknowledgment goes to the Digital Leaders Team for their commendable efforts, supported by Daisi Parker on the day too. The magnitude of their accomplishments, including hosting numerous events and honouring outstanding organisations, underscores their dedication to fostering meaningful change. This fantastic event was in a week where the team also led 80 other events with 12,000 registrations. Just incredible. 

Looking ahead, it is evident that digital leaders will continue to exert a profound influence on ESG initiatives, setting new benchmarks for responsible leadership and sustainable business practices. The journey towards a more sustainable and inclusive world remains ongoing, with digital leaders spearheading the transformative agenda and I am so proud to have played a small part in the day

Can’t wait for next year! 

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To do what is needed, businesses need improved access to more reliable data, as well as much greater collaboration with suppliers throughout the supply chain ecosystem. There are four critical steps to achieving both of these objectives.

Creating a shared value approach

We recently conducted a supplier survey which found that people were more willing to share data when they believe it will benefit society, when they understand how the data will be used, and when the data-sharing processes are easy. Incorporating these principles into supply chain engagement initiatives can lead to better results in reducing Scope 3 emissions and achieving Net Zero goals. These shared values create both economic value but also value for society, for example:

• Identification of the benefits of data collection can contribute to core business objectives, such as supply chain resilience and cost reduction.
• Collaboration between organisations with similar regulatory requirements can create a more joined-up view of value chain emissions.
• Customer satisfaction can be improved by incorporating sustainability data provision into Net Promoter Score (NPS) surveys.
• Increased knowledge of sustainable outcomes to promote a reduction in energy usage can also make financial savings.

Taking a human-centred design approach to supply chain sustainability will help organisations understand both the barriers and drivers for data sharing. This understanding will allow businesses to create initiatives that benefit everyone and ensure data-sharing processes are effective in mitigating our collective environmental impact.

Engage SMEs through awareness and support

Despite increasing regulatory pressure, lack of accurate and complete data impacts large organisations subject to regulations such as Streamlined Energy and Carbon Reporting (SECR), with SMEs facing less regulatory burden. Add to this the fact that only 53% of UK SMEs had sustainability plans in place, according to a 2021 poll – and that most businesses’ supply chains will include SMEs, the need for a supply chain sustainability approach that delivers shared value is critical.

In order to benefit from innovation, efficiency, cost savings and enhanced brand reputation, it is important for all parties involved in procurement and supply to collaborate closely on environmental matters. Sharing insights and best practice is one way in which sustainability experts on the procurement side could educate and support non-experts on the supply side.

Engagement should focus on creating a mutual understanding of sustainability risks and impacts. Buyers can provide value by sharing sustainability expertise and offering training or consulting to suppliers.

Engagement at all levels, rather than just at the board level, is important for success. Everyone can have an impact and should be empowered to believe that they can provide positive results. Raising awareness can also help suppliers identify missed opportunities for improving sustainability, such as the ability to use the data the customer wants, to engage employees and incorporate it into marketing and sales material.

Transparent communication to build trust

Transparency in communication is a cornerstone of building trust, enhancing reputation and ensuring accountability. Achieving this requires collaborative efforts among all stakeholders to develop data-driven strategic plans which incorporates the objectives and priorities of the different suppliers. Regular communication to stakeholders is key to ensuring accountability as well as managing performance against the roadmap.

To build trust, businesses need to be transparent about how they collect and use data. This transparency is especially important when working with suppliers who might be reluctant to share data if there are concerns about the potential negative impact on their selection. For businesses with limited knowledge in this area may need help to provide accurate data and insights.

The key lies in establishing clear channels of communication, sharing best practices and collaboration can lead to continuous improvements in emission outputs, both for suppliers and buyers.

Make it easy with technology

The collation of supply chain sustainability data is a complex task, with only 38% of businesses calculating their supply chain footprint, and a substantial portion of these relying on overly manual data collection processes.

There are no universal standards for sustainability accounting, causing suppliers to complete numerous different disclosures. By understanding suppliers’ needs and using automation technologies, businesses can improve data collection processes. And as the technologies improve there is opportunity to make processes even more efficient.

Reporting tools like dashboard systems can provide valuable insights and track progress towards sustainability goals, providing a future of industry-led benchmarking, which businesses can work towards as they mature in the process.

Designing a sustainable supply chain programme that incorporates these four considerations will help businesses improve access to better quality data, enabling them to take more informed action on sustainability towards their Net Zero goals.

Collecting and using data will help organisations defend against greenwashing claims, support the development of sustainability and business opportunities, improve supplier relationships and provide valuable insights for all parties involved.

Originally posted here

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I needed cheering up. With so many dark and disturbing stories in the news these days, I decided that I should escape for a while and remind myself of happier times by spending a few hours on the sofa under a duvet re-reading Douglas Adam’s wonderful series of “Hitchhiker’s Guide to the Galaxy” books. Taking me away from today’s pressing problems and into another world where anything and everything is possible.

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