Attack surface management
Attack surface management: you can’t protect what you can’t see By Marios Kyriacou Wikipedia defines the attack surface of a software environment as “the sum of the different points where an unauthorised user can try to enter data, extract data,
AI led Digital Transformation in Print Manufacturing
The manufacturing industry is undergoing a massive transformation, integrating technologies like artificial intelligence, automation, and digitalisation to optimise production and boost efficiency. In print manufacturing, companies adapt to these changes by viewing AI as a tool for growth rather than a threat. In this article, John Kilburg from K12 Printing reacts to digital transformation that is led by artificial intelligence. This article is published in line with the Digital Transformation and AI Awards and Summit. To exhibit at the event, please get in touch at +44 (0)203 931 5827. The Impact of Digital Transformation on Print Manufacturing This isn’t the first major shift in manufacturing. Like many other industries, print manufacturing experienced significant digital transformation with the introduction of computers and other digital technologies. Decades ago, manual processes dominated the industry, limiting efficiency and scope. The introduction of digital tools such as computer-aided design and automated printing presses revolutionised production. This shift allowed for faster workflows, improved precision, and greater customisation. This earlier wave of digital transformation was a cause of discomfort for many in the manufacturing industry due to concern about the new technology replacing jobs. Instead, it reshaped roles without replacing them. It created opportunities for workers to upskill and move into more specialised roles such as graphic designers or other important roles within the print manufacturing industry. Today, many print manufacturers see AI as a continuation of this evolution, offering new ways to enhance their business and empower their workforce. AI’s Role in Print Manufacturing While still early in print manufacturing, AI is poised to bring substantial benefits in certain areas. At K12 Print, AI is being explored cautiously, with a focus on enhancing efficiency and creativity rather than reducing jobs. Shortly, AI is likely to assist in design elements. This would enable designers to work faster and focus more on creativity and strategic decision-making. Another practical implementation is through machine maintenance, using predictive analytics to prevent breakdowns and optimise performance, minimising downtime. Rather than letting technology drive layoffs, companies should be committed to maintaining their workforce and creating opportunities for career advancement. This approach keeps jobs in the country and the community and strengthens the company’s foundation as a tight-knit group that values each employee’s growth. Enhancing Print Quality There are many practical uses of artificial intelligence in print manufacturing. First, AI can be used to analyse and optimise images that are received from the customer. Most customers are not knowledgeable about print files or colour builds. Artificial intelligence can sharpen images and adjust colour in real time. The result of these corrections is high-quality prints in a shorter amount of time which saves money. Also, AI may come into the design elements of print when customers bring forward ideas for us to create. Several nuances go into making their idea a reality and although there are currently real people building off those ideas. AI and Sustainability The manufacturing industry is constantly evolving when it comes to sustainability. Many of the printing tools have become more environmentally friendly over the years especially when it comes to ink and other critical elements in printing. But more changes on the horizon can make printing more sustainable. The use of AI systems can help reduce waste and save on energy consumption. This can help lessen the environmental impact of the printing industry. Additionally, artificial intelligence can use its vast database (learned knowledge) to suggest other areas where printing can transition to eco-friendly materials. A practical implementation of AI could also be in predictive maintenance—monitoring the machines in use and predicting breakdowns so they can be avoided. AI and Cost AI may be cost-prohibitive to smaller print manufacturing companies in the short term. However, as history teaches us, technology tends to become affordable very quickly once it is embraced by the masses. The more we learn to embrace AI rather than fear AI, the faster it will become a tool that propels us forward. Security Every data-driven industry must think about security. And print manufacturing is no different. Another practical implementation of AI in manufacturing is within the company’s security setup. AI can identify patterns in data traffic that can be indicative of a security breach and suggest, or even implement measures to counter the breach. It can also work to prevent security breaches by enforcing user authentication and even monitoring the printing of sensitive or confidential materials. Print Personalisation Although a vast majority of the print orders that come through the shop are custom orders there is still a major market for pre-made ready-to-order looks. AI systems can use available data about customers to customise content based on that data. This can be used in marketing campaigns to create high-response materials targeted to specific audiences. Packaging and direct mail will be big beneficiaries of this. AI Won’t Replace Jobs – It Will Create New Opportunities A common concern in the workplace is that AI will lead to job loss. However, this fear may be overstated. Much like the earlier digital transformation, AI presents an opportunity to elevate both workers and businesses. K12 Print is committed to investing in education and on-the-job training for employees, preparing them to adapt and thrive in a more technology-driven workplace. Upskilling the workforce will ensure that workers move into more rewarding roles. AI will likely take over repetitive tasks, but this shift will allow employees to focus on oversight roles. For print manufacturing, this means workers can explore new career paths in roles such as AI technicians, data analysts, and advanced machine operators. Digital transformation in manufacturing is inevitable, and AI will play a crucial role in shaping the future. Get in touch For event sponsorship enquiries, please get in touch with calum.budge@31media.co.uk For media enquiries, please get in touch with vaishnavi.nashte@31media.co.uk
Transforming Banking with DevOps
This article is published in collaboration with the Digital Transformation and AI Awards and Summit. These are two separate B2B events organised by 31 Media. If you wish to exhibit your tech solutions or to advertise your brand at the event, please get in touch at +44 (0)203 931 5827. Author: Arnab Mitra, programme manager at Banking Industry Architecture Network (BIAN) The banking industry is undergoing a significant digital transformation. The emergence of fintechs and industry disruptors is forcing traditional banks to innovate faster than ever before to remain competitive and address the needs of the digital-first customer. Delivering these solutions effectively and at speed often requires an overhaul of legacy technology and the emergence of new technological-driven processes. Enter DevOps, a combination of practices and tools that is driving the future of the financial services industry. We spoke with Arnab Mitra, programme manager at the Banking Industry Architecture Network (BIAN) about the role of DevOps in banking and the need for industry collaboration to further accelerate transformation. Q1: What challenges have traditionally hindered banks from adopting DevOps, and how has the industry’s perspective shifted to embrace this methodology? Traditionally, banks were slow to adopt DevOps due to regulatory constraints, concerns about data security, and a legacy mindset that is naturally more hesitant towards change and innovation. However, the pandemic accelerated the need for banks to offer digital services, which in turn hastened the adoption of DevOps. As the benefits of DevOps became clear, banks have realised that they needed to embrace this methodology to remain competitive and keep pace with nimbler fintechs, while offering new services that are enabled through best-of-breed technologies. In today’s rapidly evolving IT landscape, DevOps streamlines transformation and enables banks to deliver innovative digital services at speed and scale. With the global drive for transformation, banks recognised that if they don’t transform, they risk being left behind, and at a significant cost. For example, a 2023 IDC Financial Insights survey found global banks are on track to spend $57.1 billion on legacy payments technology in 2028. It’s therefore no surprise that over 80% of financial services firms have embraced DevOps practices, reflecting the widespread adoption and recognition of its benefits in the industry. Q2: What is BIAN’s approach to DevOps? How is this reflected in BIANs offerings? BIAN is built on collaboration across the industry and we use DevOps methodology within our member activities to encourage this. Working groups formed of members from different organisations within banks, technology vendors and consultancies come together to share thoughts, ideas and experiences to collaborate on innovative solutions, for example producing API specifications. Another example is our Coreless Banking initiative, which completed its third iteration last year. BIAN took a DevOps approach to this initiative, which was developed by a collaboration of leading banks and technology vendors, including HSBC, Zafin and IBM. The initiative, which aims to tackle the interoperability challenges banks face, resulted in an API-based services architecture that empowers banks to integrate best-of-breed technology seamlessly. Coreless Banking leverages the DevOps processes of the individual participating members to bring their components (solutions) into a published state, for other participants to use and integrate with. This allows for quick releases when any changes are required for any individual member. At the same time, using the BIAN standard for the API interface specifications means the integrated solution still works. Q3: Can you share any examples of how you’ve implemented DevOps principles on a more practical level? BIAN’s materials, including our Service Domains, are made available on the cloud, allowing members to access and use BIAN APIs for various applications within their organisations. Using BIAN’s framework, external parties can access our materials and create their own CI/CD pipeline, adapting it to their own needs. Members also have access to BIAN tooling, with functionality that allows users to match their APIs with BIAN APIs. In addition to this, we have an automated feedback loop and message modellers which enable rapid updates to BIAN models, once manually approved. Members can compare artefacts with the BIAN model content, helping to ensure APIs are compliant, within our framework. These automated processes guarantee consistent quality across all of our materials, eliminating individual preferences and ensuring regulatory compliance While we have been using DevOps in our approach for many years, we are now exploring how AI is enabling and evolving our DevOps operations. Q4: How is AI transforming DevOps practices and environments within the financial services industry? AI is a true game-changer within the industry. When applied to DevOps, the scope for automation within these environments is huge. BIAN is exploring many potential use cases for the technology. For instance, we’re looking at how we can use AI to generate sample data for Service Domain APIs to create a sandbox with quality test data that developers can use to mock up innovative solutions using these APIs. Additionally, we are piloting an AI-based API mapping app to automate the mapping process by 50-60%, significantly reducing human effort. We are focusing on training our AI-Engine with quality data, and feedback from our members supports the finetuning of this app. This means that members using our model will benefit from streamlined processes and enhanced efficiencies, while BIAN benefits from member feedback which continuously trains and improves our AI models, further supporting our collaborative environment. Q5: How important will DevOps be for the future of banking? Why is collaboration the key to transformation? As banks continue to focus on digital transformation, DevOps practices will be essential for delivering innovative products and services at speed. When development and operations teams work together closely, they can identify and address issues more efficiently, improve communication and ultimately deliver better results. By breaking down siloes – not only within organisations but across the financial services ecosystem – it creates a more cohesive and successful work environment. With the advent of new technologies, including AI, it’s now more important than ever for teams to share ideas about how this technology can be used safely and
Delivering DevOps through Platform Engineering
This article is published in collaboration with the Digital Transformation and AI Awards and Summit. These are two separate B2B events organised by 31 Media. If you wish to exhibit your tech solutions or to advertise your brand at the event, please get in touch at +44 (0)203 931 5827. Author: Fred Lherault, Field CTO, EMEA / Emerging Markets, Pure Storage Delivering on the promise of DevOps through Platform Engineering In software engineering, the Golden Path aims to provide the smoothest way forward via a self-service template for common tasks. It is enabled by platform engineers – who provide developers with the simplest possible internal developer platform and the tools they need to deliver innovation. Here we look at the emerging discipline of platform engineering, and the benefits it brings to application development via easier and faster access to services and resources, in particular using modern data management platforms built on Kubernetes containerised environments. Giving developers what they want When DevOps emerged in the late 2000s, it brought with it key principles of shared ownership, rapid feedback and workflow automation to help deliver on the vision of agile software development. It requires a high degree of autonomy for the developers and in exchange empowers them with the tools they need to be efficient. Automation is one of the key principles of DevOps since the quick pace of changes it drives is incompatible with “human in the loop” workflows. The mode of operations preferred by developers (and many technical specialist roles such as data scientists, AI researchers etc.) can often be boiled down to 3 main asks: Instant access to resources Instant results Full self-service Using the above as the “north star” when building services geared towards technical profiles is a great way to enable innovation and ensure fast adoption. While providing instant resources and results might not be always possible, getting as close as possible to instant will drive greater satisfaction. Platform engineering treats the developer as its primary customer Today, we see the coming of age of DevOps through the rise of platform engineering, a new function for a more mature era in application development, that provides a suite of self-service tools to empower developers. Platform engineering operates behind the veil to provide an easy-to-use, self-service catalogue of services and infrastructure components to support the day-to-day development experience. Best practice platform engineering aims to help application developers get on board and start building faster by providing everything that they need to experiment, develop, test and deploy. The platform made available to these developers often takes inspiration from the services popularised by the public cloud and its mode of operation. It is designed to provide instant access to not just the latest and greatest tools and software that underpin innovation, but also provide easy access to the data itself, protected by pre-determined guardrails and security protocols. Kubernetes and data management The ideal developer-focused platform also includes data management. It may build on top of Kubernetes as the means to orchestrate, deploy, run and scale cloud-native applications as well as to manage the data services required for those applications. Data management capabilities are key to platform engineering because they enable exploration and testing in realistic conditions, for example using an instant copy of production data instead of a somewhat unrealistic synthetic data set. Ideally, the data management capabilities will also be designed with self-service in mind, and deliver access to data in a highly available, reliable, elastic, multi-tenant and secure manner. Portworx from Pure Storage is an example of such a modern data platform. Fully integrated with Kubernetes, it allows the developer to easily get access to persistent data options (including data protection capabilities such as data replication, backup and archiving) but also to data sets themselves through instant data cloning, even enabling the use of self-service instant snapshot creation and restore so that developers may experiment with changes and roll back to previous states quickly and easily. Additionally, Portworx Data Services provides a catalogue of curated data services, including MongoDB, Elasticsearch, Cassandra, Kafka and PostgreSQL, simplifying deployment into just a few clicks or a single API call, so that developers can deploy or scale these data services easily with the optimal data storage configuration and protection. This foundation brings these easy-to-specify toolchains and data services to the developers so that they can easily use them as building blocks, even if they don’t have extensive knowledge of Kubernetes or how to deploy a given database engine in a secure and scalable manner. Platform engineering enables the Golden Path Platform engineering teams are busy working unseen in the background to bring the self-service Golden Path to application development. With Kubernetes as the orchestration framework, and containers and data services as key resources, the platform engineers can finally deliver fully on the vision of increased agility and greater productivity of DevOps. Get in touch For event sponsorship enquiries, please get in touch with calum.budge@31media.co.uk For media enquiries, please get in touch with vaishnavi.nashte@31media.co.uk
Using workflow automations to minimise development downtime
This article is published in collaboration with the Digital Transformation and AI Awards and Summit. These are two separate B2B events organised by 31 Media. If you wish to exhibit your tech solutions or to advertise your brand at the event, please get in touch at +44 (0)203 931 5827. In this article, you’ll learn how you can minimise development downtime with workflow automation. Author: Steve Barrett, VP of EMEA, Datadog Minimising development downtime and disruption through workflow automation DevOps teams are under constant pressure to deliver software applications as quickly as possible. At the same time, DevSecOps and security operations centre (SOC) teams face an ongoing challenge in detecting and remediating constantly evolving security threats. These challenges can be exacerbated by the various complex and often error-prone processes involved in responding to disruptions and changes to an organisation’s systems. A large amount of time can be spent switching between different tools to gather the context required for remediation, and in the manual execution of tasks needed for incident management, significantly prolonging downtime and causing further disruption. It can be hard to prioritise and manually respond to the high volumes of alerts generated by larger and more complex systems, further delaying resolution and increasing the risk of human error. Fortunately, a range of new workflow automation tools are available to support DevOps, DevSecOps and SOC teams, specifically in the observability and real-time monitoring of servers, databases, SaaS tools and services across their organisations’ cloud and IT infrastructure. Automate end-to-end processes Workflow automation helps teams more confidently manage the health of their systems and resolve issues faster, automating and orchestrating complex flows of tasks in response to specific threats, events, and alerts, and allowing teams to incorporate human input into those flows where required. By allowing them to combine monitoring and remediation into a single, streamlined solution, new workflow automation tools can enable DevOps to automate and orchestrate entire end-to-end processes across their infrastructure and tools, helping them to quickly remediate any issues that might arise. Consider alerts, for example. Whether monitoring network health, application performance, or infrastructure resources, DevOps teams must set alerts. By letting them know the moment an issue occurs, an alert allows them to respond in an appropriate and timely manner. But responding to alerts manually can be repetitive and time-consuming: an alert might send notifications in the middle of the night, or engineers might have to restart an application to resolve the issue manually. However, creating a workflow which consists of connected remedial actions that automatically execute when a specific alert is triggered can significantly reduce a team’s mean time to resolution (MTTR). Tackling emerging threats The technology has considerable benefits for DevSecOps and SOC teams, too, enabling them to orchestrate an automated series of actions in response to an alert, and quickly tackle any emerging threats to their system’s security. By chaining together specific actions in a workflow, or actions from integrations such as AWS, Okta and others, teams can configure workflows to trigger a specific alert and automatically execute an important security process, such as blocking a suspicious IP address, performing tier–one triage—such as reviewing and adding context to threats detected by cloud SIEM—or rolling back a code deployment that introduces a vulnerability. An organisation might use Okta for identity and access management, for example, and has a rule in place which detects when a user attempts to access an application without authorisation. Configuring and adding a “Suspend Suspicious Okta User” workflow means that if and when that rule is triggered, the suspicious user will be automatically suspended Workflow automation can even help create new rules that establish whether an alert has detected a real threat or a false positive. Although security signals provide much information, it’s not always enough to indicate whether an alert requires further investigation. By enriching cases with relevant context from the observability data generated through real-time monitoring, teams can better identify and eliminate false positives and determine whether an incident is a malicious event. DevSecOps and SOC teams can also combine new cloud SIEM and automated workflows to automate repetitive security tasks like detecting emerging vulnerabilities or triaging security signals. Traditionally separate automation, SIEM, and case management capabilities can be unified in a single pane of glass, allowing teams to create a centralised workspace for investigating their security signals. Not only does this help teams reduce tool sprawl and spending, but the combined use of cloud SIEM and automated workflows also reduces the burden on security engineers, allowing them to focus on more complex tasks. Streamlining monitoring and troubleshooting Today’s security teams operate in a constantly evolving, increasingly complex, and challenging environment. The use of disparate point solutions only adds to this complexity and can risk an ineffective security posture. Workflow automation helps mitigate this risk, streamlining monitoring and troubleshooting by automating end-to-end processes and executing actions in response to alerts, security threats, and other insights. As well as boosting productivity and saving valuable time, implementing automated workflows in response to security threats allows an organisation’s DevOps, DevSecOps, and SOC teams to focus on the most critical security issues and more quickly and easily detect and defend against potential attacks. Get in touch For event sponsorship enquiries, please get in touch with calum.budge@31media.co.uk For media enquiries, please get in touch with vaishnavi.nashte@31media.co.uk
Finalists announced for DevOps awards 2024
The finalists for the 2024 DevOps Awards were officially announced on September 30, 2024. Organised by 31 Media, this prestigious awards programme recognises excellence in DevOps across various industries, entering its 8th year of celebrating remarkable achievements. 31 Media has been at the forefront of organising industry-leading conferences and awards for over 17 years. The DevOps Awards are an independent, globally recognised programme, open to businesses, teams, and individuals across the world. With a multitude of categories, the programme allows multiple entries and provides a unique opportunity for participants to gain recognition for their contributions to the DevOps community. Reaching finalist status in these awards is a significant achievement, highlighting the talent, dedication, and innovative work of the competing companies and individuals. The event offers a chance to showcase your organisation’s expertise and elevate your brand visibility among top professionals in the DevOps and quality engineering sectors. The DevOps Awards ensure an impartial and transparent judging process. Judges, carefully selected for their extensive experience in the DevOps domain, hold senior leadership roles across diverse industries. To maintain complete fairness, all entries are judged anonymously, with identifying information removed. Winners are determined solely on merit, regardless of the size, budget, or influence of the company. Some of this year’s judges include: David Jambor – Senior Director, Tech and Secure Infrastructure at BCG Darren Griggs – CTO Advisory Matt Day – Head of App / Dev Technology Practice at Google Cloud UK/I Maria Stefanova – Head of Agile PMO and Digital Transformation at International Airlines Group Himanshu Kansal – Director of Engineering at Reed.co.uk Basit Tanveer – Head of Business Platforms at Lebara Chandri Krishnan – Engineering Leader at Meta Ravi Jay – Head of Agile Delivery at Jaguar Land Rover Lisa Li – Head of Engineering at Sainsbury’s Ruben Bell – Head of Technology Strategy & Governance Jason Ward – Head of Architecture & Engineering at Rethink Underwriting Ltd View the full list of finalists here. The 2024 DevOps Awards ceremony will take place in London on October 22-23, where the winners will be revealed. For table bookings or inquiries, please contact the team at grant@31media.co.uk.
How to build a digital-first company culture in recruitment
This article is published in collaboration with the Digital Transformation and AI Awards and Summit. These are two separate B2B events organised by 31 Media. If you wish to exhibit your tech solutions or to advertise your brand at the event, please get in touch at +44 (0)203 931 5827. In this article, you’ll learn how to build a digital-first company culture in talent acquisition Author: Gonzalo Guillen, CEO at HR Exchange Building a Digital-First Company Culture in Talent Acquisition As the world of work continues to evolve, companies are being challenged to rethink how they approach talent acquisition. The shift toward a digital-first strategy has transformed not only how we recruit but also how we build a company culture that thrives in a modern, tech-driven environment. I’ve had the privilege of working with companies across various industries, and I’ve seen firsthand how a digital-first approach can unlock new opportunities in talent acquisition. Here’s my perspective on what it takes to build a digital-first company culture in this critical area. The core principles of a digital-first company culture At the heart of a digital-first culture is the ability to harness technology to improve efficiency and scalability while keeping the human element intact. In talent acquisition, this means using digital tools like applicant tracking systems, AI-powered candidate sourcing, and communication platforms to enhance the recruitment process. But it’s not just about technology for technology’s sake—it’s about how you apply these tools to create a seamless experience for your team and the candidates. It’s essential to design processes that are efficient but also respectful of the candidate’s time and experience. Keeping the recruitment process personal in a digital world One of the biggest concerns with digital talent acquisition is the fear of losing the personal touch. We’ve all heard stories of candidates feeling like they’re just a number in the system. The truth is, that automation doesn’t have to be impersonal. With the right tools, you can create more personalised experiences. For example, AI-driven chatbots can handle initial inquiries quickly while tailoring responses based on candidate history. Video interviews and interactive assessments also allow us to get to know candidates better, ensuring that technology enhances – not replaces – the human connection. How Does Remote Work Enhance Collaboration in Talent Acquisition? Remote work has changed the game for recruiting teams. Tools like Slack, Zoom, and collaborative platforms allow teams to stay connected and move quickly, regardless of where they’re located. What I’ve found is that remote work, combined with the right digital tools, actually fosters better communication and collaboration. It creates a flexible environment where people can contribute meaningfully without being tied to a physical office. For talent acquisition, this means faster decisions, more diverse perspectives, and a stronger alignment with company culture. Assessing Soft Skills in a Digital-First Environment Soft skills are often harder to evaluate, especially when you’re not meeting candidates face-to-face. However, digital tools give us new ways to assess how someone thinks, communicates, and interacts with others. Video interviews are great for this – body language, tone, and communication style come through in ways that a resume can’t capture. Online simulations or real-world scenario tests are also excellent tools for evaluating a candidate’s problem-solving skills and adaptability. With these digital approaches, we can get a fuller picture of a candidate’s potential. Using Data to Shape a digital-first Talent Acquisition Strategy In a digital-first strategy, data is your best friend. When used correctly, data analytics can provide critical insights into your recruitment process, helping you identify areas for improvement and make smarter decisions. I’m a strong advocate for using metrics like time-to-hire, quality of hire, and candidate conversion rates to drive decisions. Predictive analytics can also help identify candidates who are more likely to thrive in your company’s environment, saving time and resources while increasing the chances of a successful hire. Real-World Examples of Successful Digital-First Talent Acquisition There are plenty of companies that have successfully implemented digital-first recruitment strategies, and I’ve had the pleasure of working with a few of them. Take IBM, for example – they’ve integrated AI throughout their hiring process, reducing the time to screen candidates while improving the quality of hires. They’ve also built a strong digital culture that supports remote work and collaboration. Another great example is Microsoft, where they’ve embraced digital tools to speed up recruitment and create an inclusive culture that prioritises employee well-being. The key to building a digital-first company culture in talent acquisition is striking the right balance between technology and human connection. When done correctly, it can transform the recruitment process, making it more efficient, data-driven, and candidate-focused. At the end of the day, it’s about leveraging digital tools to enhance – not replace – the relationships that make your company unique. Get in touch For event sponsorship enquiries, please get in touch with calum.budge@31media.co.uk For media enquiries, please get in touch with vaishnavi.nashte@31media.co.uk
How data visualisation shapes software development
This article is published in collaboration with the Digital Transformation and AI Awards and Summit. These are two separate B2B events organised by 31 Media. If you wish to exhibit your tech solutions or to advertise your brand at the event, please get in touch at +44 (0)203 931 5827. In this article, you’ll learn how the trends in data visualisation are shaping the future of software development. Author: Karel Callens, CEO, Luzmo How data visualisation trends are shaping the future of software development The volume of data being created, shared and stored worldwide is growing exponentially. The ability to effectively visualise the information contained within that data has become increasingly crucial for businesses across all verticals. No longer just a tool for data scientists, data visualisation has emerged as an essential skill for a far broader pool of users, all of whom need to transform complex datasets into clear, actionable insights. Consequently, developers are increasingly being tasked with integrating data insights into products, but analytics is just one of many complex elements that need their attention. This, coupled with the fact that the field of data visualisation is evolving at a breakneck pace, can be a major innovation challenge. Moreover, software users have heightened expectations from data. They want real-time AI-powered insights to be seamlessly embedded within the software they rely on. End users also demand highly interactive, hyper-personalised and customisable experiences, and they want it yesterday. It stands to reason that organisations with the most advanced analytics are more likely to outperform the competition. However, 2023 research from Accenture revealed only 25% of organisations were realising the potential of their data and analytics projects. Software apps today generate an overwhelming amount of data points, and product users need the best available visualisations to make sense of it all. With such a rapidly evolving industry, knowing what represents the “best available” is a challenge of its own. The decline of traditional dashboards Users of enterprise software will be more than familiar with the classic KPI dashboard, often hidden away under an “analytics” tab. These traditional dashboards are being phased out in favour of more integrated, immersive data experiences. Rather than being confined to static screens, insights are embedded throughout applications—popping up during tasks like inventory management, marketing segmentation, or even report creation, blending seamlessly with other features to offer users relevant data right where they need it. Furthermore, visualisation tools like Tableau and Power BI while excellent for analysts, can be cumbersome for everyday users who need quick, actionable data. Instead of relying on separate tools, metrics and visualisations are increasingly being embedded directly into the software users work with daily. The missing piece of these integrated analytics solutions is that they do not react to context. The technology now exists to make these integrated components reactive to the other information being surfaced by the dashboards. This change in data does not only mean adding more information. Users have a limit on how many pieces of information they can process concurrently, the very best systems will only present the information that is needed. For developers deciding what not to show is almost as important as deciding what data to present without overloading the end user. Integrating analytics in this way streamlines workflows, making data-driven decisions more intuitive and natural. The next generation of data visualisation The days when data analysis was reserved for specialists are fading. Recent advancements in AI are democratising data access, allowing anyone to analyse large datasets using natural language. For example, users can simply type a question like, “What was my top-selling product last quarter?” and receive a visual representation of the data instantly. This shift toward conversational data analytics is also fostering a new era of data storytelling, where AI helps users uncover and communicate compelling narratives within their data. In the not-too-distant future, static charts could be obsolete as interactive data visualisation tools become the norm. As AR glasses and interfaces are beginning to enter the market, live analytics in a HUD could be one route to achieving the next generation of data visualisation. For example, a plant manager could be observing the factory floor while an analytics solution highlights areas for concern in real-time. This is currently a very niche use case, but as the costs of AR systems come down, it is an area businesses could explore to further increase productivity. In industries like healthcare, manufacturing, and finance, timely decision-making is crucial. Companies using real-time data analytics are seeing significant benefits. Modern data visualisation prioritises real-time insights, ensuring that users can act quickly on the most current information. Whether through alerts, pop-ups, or other real-time features, these tools help teams respond swiftly to complex data scenarios. As organisations continue to harness the power of data, visual representation enables quicker decision-making, improved communication, and a deeper understanding of trends and patterns. The rise of data visualisation underscores its growing importance in making sense of today’s data-driven world. An awareness of the trends shaping data visualisation is a big step in the right direction, executing that awareness though is going to take work. The rise of the hyper-personalised No two users are the same. For instance, an organisation might have developed a social media platform for marketers: the KPIs for a head of marketing will differ significantly from those for a social media manager, and even two managers at different companies might focus on entirely different metrics. Modern data visualisations must be able to adapt to the user’s context, showing metrics relevant to their specific role, industry, and even platform usage. This level of personalisation extends to localisation, ensuring data is presented in the user’s language and timezone, and remains responsive across devices. AI will play a crucial role in making future applications personalised, already there are examples of AI agents that customise analytics interfaces depending on the user’s role and context, down to their historic use of the platform. This technology can infer what insights the user might be looking for
Benefits of automation in DevOps
This article is published in collaboration with the Digital Transformation and AI Awards and Summit. These are two separate B2B events organised by 31 Media. If you wish to exhibit your tech solutions or to advertise your brand at the event, please get in touch at +44 (0)203 931 5827. In this article, you’ll learn about the benefits of automation in DevOps for content management systems. Author: Nick Barron, Senior Director of Technical Services at Contentstack Innovation from the ground up: the benefits of automation in DevOps DevOps is a general collection of flexible software creation and delivery practices that looks to close the gap between software development and IT operations. Two critical but often misaligned efforts. By working together, development and operations teams can eliminate roadblocks and focus on improving the creation, deployment, and continuous monitoring of software, while simultaneously driving innovation for their company. There are many ways headless CMS (content management system) companies are utilising automation internally to improve their all-around operations. DevOps can be leveraged in various ways, including using it as a tool to maintain a constant cadence of effective workflow and to deal with bug fixes early on in an efficient manner, driving innovation from the ground up. Striving through automation From an automation perspective, DevOps tactics like automation analytics testing allow businesses to pinpoint where the weak spots are in their infrastructure in little to no time. This cuts down time on human testing, eliminating the reliance on in-depth quality assurance. Through automation, companies can test all elements of the platform and service in one go. With small factors making a huge impact on the overall performance of a CMS platform, automation helps save buckets of human time. This allows human efforts to be placed into more useful activities including creativity, innovation, and design. For example, CI/CD pipelines are automated workflows that streamline the process of software development, integration, testing, and deployment, reducing the time required to bring new features and products to market. This speed allows companies to quickly respond to market demands and innovate more rapidly. Continuous Delivery (CD) automates the release of code changes to a production environment, allowing coders to push out code more efficiently, ensuring that the software can be released reliably at any time. At the same time, Continuous Integration (CI) is the practice of merging all developers’ working copies to a shared mainline several times a day. By integrating code changes regularly, the system ensures that all changes are compatible and work together. Automation for CMS platforms CMS platforms can leverage DevOps in various ways, allowing entire platforms to be up and running with virtually zero downtime, enabling them to constantly evolve with changing market demands. Through automation, CMS companies can help brands publish faster and personalise their content more. Scalability is another essential factor that can be achieved through automation, which is key to maintaining top-notch website performance, equipped with fast loading times and smooth user experience. Automation and DevOps is what keeps CMS platforms running in the most effective and efficient ways possible. The CMS industry is at the forefront of what is possible for DevOps, with teams continuously testing new capabilities and rolling out new tools and methodologies. Being an industry pioneer in the sector takes a lot of resiliency, constant innovation, trial and error and an openness to change, which DevOps makes possible. The bottom line All in all, thanks to different developments, advancements, and changes through the tactics, DevOps is a service that unites software development and IT operations, allowing more effective collaboration and innovation. It combines the necessary parts of software teams, brings them together, and promotes a more diverse work culture as it automates the mundane or complicated parts of software development. As the work becomes more cloud-focused, DevOps allows not only for more flexibility within languages, workflows, and practices but also increases the companies’ ability to manage teams more efficiently and collaboratively. With these automation improvements, companies can focus on what is most important and delegate tasks accordingly as it becomes easier to understand the data and the code rather than have to swim through it. As such, it gives companies a meaningful competitive edge in the market, regardless of the industry. DevOps is a rapidly evolving market with significant expansion. Advancements like Gen AI are set to profoundly impact a range of DevOps tasks, helping companies drive innovation from the ground up more than ever before. Get in touch For event sponsorship enquiries, please get in touch with calum.budge@31media.co.uk For media enquiries, please get in touch with vaishnavi.nashte@31media.co.uk
Role of Agile methodologies in digital transformation
This article is published in collaboration with the Digital Transformation and AI Awards and Summit. These are two separate B2B events organised by 31 Media. If you wish to exhibit your tech solutions or to advertise your brand at the event, please get in touch at +44 (0)203 931 5827. In this article, you’ll learn about how agile methodology impacts digital transformation. Author: Saraha Burnett, Chief Operations Officer at TMG How Agile methodology drives success in digital transformation and beyond In today’s fast-paced and ever-evolving business landscape, digital transformation has emerged as a pivotal driving vision for companies striving to stay competitive and relevant. As organisations seek to harness the power of emerging technologies and redefine their operational models, digital transformation offers a strategic pathway to enhance efficiency, foster innovation, and deliver exceptional value to customers. However, successfully navigating this transformative journey requires more than just adopting new technologies; it necessitates a fundamental shift in how companies approach their operations and strategy. Agile methodology stands out as a crucial component in this transformative vision. Embracing it as a driving priority enables enterprises to respond with agility to rapidly changing market demands, technological advancements, and competitive pressures. By prioritising Agile frameworks and the roles necessary to support them, companies can cultivate a culture of innovation, enhance customer-centricity, and maintain operational efficiency—all critical factors in achieving long-term success in a digital-first world. Key Aspects of Digital Transformation Digital transformation involves integrating advanced technologies such as cloud computing, artificial intelligence, data analytics, and IoT to boost operational efficiency and expand service offerings. It also requires optimising business processes to improve efficiency and customer satisfaction by reengineering workflows to meet digital marketplace demands. Cultural change is crucial, as organisations must develop a culture that embraces change, innovation, and continuous improvement to support a digital and Agile operational model. Enhancing customer experience through digital channels and technologies is a primary goal, aiming to provide a more personalised and seamless interaction, ultimately driving greater customer satisfaction and loyalty. How Agile methodology supports digital transformation Agile methodologies are highly effective in dynamic environments where rapid change is constant. Leveraging iterative planning, development, and incremental delivery, it enables organisations to swiftly adapt to shifting customer needs, technological advancements, and competitive pressures, keeping them ahead in the digital landscape. This approach fosters a culture of innovation and experimentation, encouraging teams to test, gather feedback, and refine strategies based on real-world data, which supports continuous improvement and innovation. Moreover, Agile enhances planning cycles by leveraging customer-centricity by integrating regular feedback to ensure that products and services meet user needs, making features and enhancements more relevant and valuable. It also mitigates risks in digital transformation by breaking projects into manageable components for frequent assessment and adjustment, thus reducing the likelihood of large-scale failures. It even promotes cross-functional collaboration, continuous delivery, and data-driven decision-making, while frameworks like SAFe and LeSS ensure scalability and flexibility as organisations expand their digital initiatives. Companies using frameworks like SAFe report a 30-75% faster time-to-market, a 20-50% increase in productivity, and 25-75% improvements in quality. From a Consulting Perspective Agile is a widely preferred method of delivery in consulting due to its inherent flexibility and responsiveness. The iterative development and incremental delivery allow for quickly adapting to changing client needs and market conditions. This adaptability ensures that projects remain aligned with client objectives and can easily incorporate feedback throughout the development process. By breaking down projects into manageable components, Agile enables them to deliver frequent updates and adjustments, ensuring that clients receive valuable, functional solutions sooner and with greater precision. Furthermore, it fosters a collaborative environment that enhances communication and transparency. Through regular feedback loops and iterative reviews, clients are actively involved in the development process, allowing them to influence the direction of the project and make informed decisions. This close collaboration not only improves client satisfaction but also helps mitigate risks by addressing issues early and often. The focus on continuous improvement and responsiveness drives success in today’s rapidly evolving business landscape. In conclusion, as digital transformation becomes a central vision for modern enterprises, adopting Agile methodologies is essential for turning this vision into reality. The emphasis on iterative development, rapid adaptation, and continuous improvement not only supports but accelerates the digital transformation journey. By integrating these practices, organisations can enhance their ability to respond to market changes, foster a culture of innovation, and improve customer satisfaction. The synergy between digital transformation and Agile ensures that companies are not only equipped to navigate the complexities of today’s digital landscape but are also positioned to thrive in a future defined by constant evolution and opportunity. Embracing it as a strategic priority will empower enterprises to realise their digital transformation goals and achieve sustained success in an increasingly dynamic world. Get in touch For event sponsorship enquiries, please get in touch with calum.budge@31media.co.uk For media enquiries, please get in touch with vaishnavi.nashte@31media.co.uk
The impact on digital transformation by rising startups
This article is published in collaboration with the Digital Transformation and AI Awards and Summit. These are two separate B2B events organised by 31 Media. If you wish to exhibit your tech solutions or to advertise your brand at the event, please get in touch at +44 (0)203 931 5827. In this article, you’ll learn about the role of the rising number of startups on digital transformation as a whole. Author: Dmitry Matveev, CTO of Approveit How startups are leading the digital transformation charge In today’s rapidly evolving business landscape, digital transformation is no longer a mere trend, but a necessity for survival and growth. Startups are often founded on disruptive ideas that challenge traditional business models and industries, they are often more willing to experiment with new technologies and promote new business models to the masses than large corporations, which undoubtedly influences the development of the digital sector as a whole. For example, the use of AI for personalised financial advice, blockchain for secure transactions, and mobile apps for seamless user experiences has reshaped consumer expectations and set new standards for the industry. Leveraging cutting-edge technologies Unlike traditional companies, startups frequently operate in high-uncertainty environments where data can provide actionable insights and guide strategic choices. It’s a competitive edge, as by using data analytics, startups can make informed decisions, optimise operations, and tailor their offerings to meet market demands. Data analytics enables startups to identify key performance indicators (KPIs), monitor progress, and allocate resources more effectively. By focusing on data-backed insights, startups can avoid costly mistakes and concentrate their efforts on strategies that demonstrate a higher likelihood of success. Besides, by leveraging data, startups can refine their products, target their markets more effectively, and enhance user experiences. Startups gather user feedback through surveys, reviews, and direct interactions. By analysing this feedback, along with user behaviour data such as click patterns and feature usage, startups can identify pain points and areas for improvement. This data-driven approach enables them to make informed decisions about product enhancements or modifications. Impact of startups on industries and global business practices There is no question that startups change industries. From a long-term perspective, the effect is tremendous and for many industries, the question of whether to use a startup as a service or partner will look like “Do we want to stay in the market and be a leader?“. Especially if we are talking about AI products and see them as auxiliary tools for increasing productivity. The problem I see is that many companies stay conservative and biased against quite fresh startups and that slows down the process of changing and improving the existing biz environment and processes. In my opinion, we should have more champions in companies who open and are willing to improve businesses, could take risks and of course must have frameworks for risk mitigations if a new approach fails (eg: startup closure). The sooner we get rid of conservatism the faster we will see how all rapidly changes and new practices will come as a result. Shaping the future of digital transformation All breakthroughs in all industries have been done mostly by startups. There is no doubt that new startups with great ideas will be arising and leading digital transformation. There are a few main topics in my opinion startups should focus on and evolve in these directions: The democratisation of Technology – By democratising access to advanced technology and giving almost a zero entrance threshold. They create platforms, APIs, and tools that enable small businesses, developers, and non-technical users to leverage complex technologies. For instance, no-code/low-code platforms and cloud-based solutions have empowered non-experts to build digital products and services, reducing the reliance on expensive development resources. Disruption of Traditional Industries – Many startups focus on disrupting traditional industries like finance (FinTech), healthcare (HealthTech), logistics, and manufacturing by introducing digital-first solutions. For example, FinTech startups are revolutionising how financial services are delivered, pushing incumbents to rethink their business models and accelerate their digital transformation efforts. And there are a lot of things for improvement. Agility and Innovation – startups are more flexible and can pivot quickly to adapt to market changes much faster than established corporations. This agility allows them to experiment with cutting-edge technologies, disruptive business models, and new approaches without being burdened by legacy systems or bureaucratic processes. Get in touch For event sponsorship enquiries, please get in touch with calum.budge@31media.co.uk For media enquiries, please get in touch with vaishnavi.nashte@31media.co.uk
Digital platform ecosystems and their capabilities
This article is published in collaboration with the Digital Transformation and AI Awards and Summit. These are two separate B2B events organised by 31 Media. If you wish to exhibit your tech solutions or to advertise your brand at the event, please get in touch at +44 (0)203 931 5827. In this article, you’ll learn about the role of digital platform ecosystems in innovation and the impact of UX. Author: Dennis Lenard, CEO of Creative Navy UX Agency The role of digital platform ecosystems Digital platform ecosystems have become central to how humanity functions and innovates. Boasting major influence in every sector, from marketplaces for goods and services to IoT and smart city infrastructure, it’s undeniable that they’re the main facilitators of value sharing among businesses, individuals, and organisations. I like visualising digital platform ecosystems as trees: their complex network of interconnected entities functions around a central, core digital platform, as branches do around a sturdy trunk. It can only thrive for as long as its users can exchange value, much like how a tree may fall if its core is rotten or shed the branches have dried. Essentially, without a core digital platform that brings added value to users, the ecosystem is doomed to fail. Digital platform ecosystems as facilitators Each digital platform must balance internal operation management with contributing to the ecosystem, as the success of each part contributes to that of the whole. Additionally, each component should meet a set of criteria to ensure the ecosystem’s health: to be interoperable, to scale well, to be secure, to follow government guidelines, and most importantly to be user-centric. According to a 2020 report from McKinsey: “Companies leveraging platform business models grow 2.3 times faster than their peers and achieve 2.5 times higher profitability.” Digital platform ecosystems’ major impact on business growth and performance is undeniable. They’ve infiltrated our lives to the point where they’ve become indispensable and changed many social conventions: how we interact with one another, how we share personal updates, original creations, or technical knowledge, how we shop, how we manage our households, how we plan our vacations. The true role of digital platform ecosystems is that of facilitators and intermediaries. These are just a few key examples of their wide range of capabilities: Online Marketplaces: Is there anyone among us who can say they’ve never used Amazon or eBay? Sellers are reaching potential buyers in corners of the world beyond their wildest imaginations. These types of digital platforms are major catalysts for economic growth. Collaboration and Innovation: I’ve never met a developer that’s not on GitHub. Such collaborative environments allow users to share code, swap ideas, suggest corrections or improvements, and innovate together. These platforms support and encourage the creation of new apps and services, thus enriching the ecosystem. Social Networking: We’re living in an era where everyone is on social media, from baby boomers to Gen Alpha. Social media platforms have charmed millions with how easy it is to share, connect, and build communities. Business and Supply Chain Management: Cross-country supply chain teams can now coordinate in real-time and track their cargo. These ecosystems have even changed how we find and interact with prospects and clients. Accessing Services: Accessing critical services looks completely different than 50 years ago. Telemedicine, financial services, travel services, and educational resources are all at our fingertips. These ecosystems have democratised access to healthcare and education for users who would otherwise experience barriers to entry (poverty, a handicap that might affect their mobility etc.). IoT and Smart Cities: Home and urban life management helps users track energy use, manage costs, and be more environmentally conscious. Because the power of digital platform ecosystems is centralised, their impact on competition, user privacy, and market fairness has often been brought into question. Big tech companies act as gatekeepers to their ecosystems, controlling who can access their information. This raises many ethical concerns, especially when considering that they’re supposed to be at the service of users, and often end up abusing their trust instead. The impact of UX on digital platform ecosystems One of the key characteristics of a successful digital platform is its user-centricity. Frankly, something that isn’t built for people and with people in mind is set up to fail from the get-go. Users who walk away from such a platform are very unlikely to come back, and they’ll associate the company that built it with their feelings of frustration. A 2021 Forrester report reveals that companies with strong user experience (UX) see an average increase in customer satisfaction of 20% and revenue growth of 10%. Happy people spend more money, no surprises there. Even so, advocating for great UX shouldn’t just be about the financial incentive, but also about treating your customers ethically. User attraction and retention, engagement, added value and trust all depend on the quality of the platform’s UX. Poor UX is like a poison to a digital ecosystem: it will kill it slowly and steadily. Nothing sends people running to the competition like difficult navigation, inconsistencies, and inadequate support. A dissatisfied user is bound to disengage, and digital ecosystems are nothing without the people who use them. It’s best to stay ahead of the game and address UX issues proactively. A successful digital platform ecosystem needs people who are constantly asking themselves: “How can I make it better?” Get in touch For event sponsorship enquiries, please get in touch with calum.budge@31media.co.uk For media enquiries, please get in touch with vaishnavi.nashte@31media.co.uk
How to leverage automation to optimise order-to-cash
This article is published in collaboration with the Digital Transformation and AI Awards and Summit. These are two separate B2B events organised by 31 Media. If you wish to exhibit your tech solutions or to advertise your brand at the event, please get in touch at +44 (0)203 931 5827. In this article, you’ll learn how you can leverage automation to optimise order-to-cash. Author: Kauleen Adiutori, Chief Operating Officer at TreviPay Leveraging automation to optimise order-to-cash Automation has often been associated with disruption and logistical challenges. However, the narrative has shifted as automation has revolutionised our approach to business operations. Far from being a cautionary tale, automation has become a catalyst for optimising essential tasks, driving operational efficiency and enhancing both employee and customer experiences. For organisations aiming to scale effectively while maintaining quality, embracing automation is not just advantageous—it’s indispensable. In today’s fast-paced commerce landscape, organisations increasingly adopt automation systems, particularly Robotic Process Automation (RPA) technology, to streamline the order-to-cash (O2C) process. From my experiences working with large enterprises, RPA – a market expected to grow to more than $13 billion by 2030 – represents a transformative leap in back-office operations. RPA can streamline complex, repetitive tasks, such as processing orders or cash applications while enhancing accuracy, efficiency and customer satisfaction. What is order-to-cash? O2C describes fulfilling customer orders, beginning when a customer first places the order through when the business receives and processes payment. For B2B transactions, an efficient O2C process also enables merchant invoicing and collecting from other businesses. According to a recent survey of global business buyers, paying with net terms (30-, 60-, 90-days to pay) on an invoice – also referred to as trade credit – is the most preferred way to pay, and 51% would even switch to a different supplier if it offers flexible net terms. This underscores the need for businesses to be able to offer this payment preference. As a business B2B sales channel expands, optimising the O2C process not only enhances the customer experience but also reduces costs, eliminates inefficiencies and ensures prompt payment. By minimising friction and effectively managing O2C with automation tools, businesses can create a better purchase experience and boost loyalty. Does your O2C need support? There are a few common signs when a business is not maximising its O2C process, including ageing Accounts Receivables (A/R), missing payments, increasing bad debt and growing customer complaints from lengthy processes and errors. Business customers are also increasingly requesting eInvoicing, which brings its own complexity and unique requirements for a merchant. Ignoring any of these signs can quickly manifest into more complicated problems. For example, salespeople may need to spend time dealing with A/R activities taking them away from key sales opportunities. Ageing A/R could also lead to an increased Days Sales Outstanding (DSO), the average number of days it takes a company to receive payment, which can signal poor cash flow impacting other business needs. Benefits of O2C automation Businesses looking to optimise the O2C process must keep scale and quality in mind. Forward-thinking leaders should ask themselves: what does our customer or employee experience look like when this automation is done correctly? Scaling effectively is essential to maximising the profitability of a B2B growth strategy. Companies often see B2B profits diminished by labour-intensive processes and increased capital expenditures without proper scaling. When scaling efforts are aligned with high-quality service, both customer and employee experiences improve, leading to greater overall efficiency and satisfaction. Balancing these elements ensures that as a business grows, it does so in a way that enhances value for all stakeholders. When scale and quality are addressed simultaneously and done right, an efficient O2C process should include: A/R ageing that doesn’t exceed 60 days past due Minimal bad debt Delighted and loyal customers Expenses scaling more profitably with growth Invoices are delivered when and how the buyer wants them Salespeople focused on sales opportunities Payments are received on time and properly reflected on the customer’s account Today, back-office automation is integral to reducing inefficiencies and eliminating monotonous work, from routine administrative tasks to complex decision-making processes. Leveraging AI and RPA tools in the order-to-cash process can help businesses achieve faster, more cost-effective operations. This leads to a better payment experience and an increased likelihood of returning customers. Get in touch For event sponsorship enquiries, please get in touch with calum.budge@31media.co.uk For media enquiries, please get in touch with vaishnavi.nashte@31media.co.uk
