John Cotterell
Analyst · Citi. Please go ahead
Thank you, Laurence. I'd like to thank you all for joining us today, and I hope you're all well. We're pleased to be here to provide an update on our business and financial performance for the three months ended March 31st, 2023. Despite the challenging macroeconomic environment, we reported another solid quarter with revenue totalling GBP203.5 million for Q3 of our fiscal year 2023, representing a 20.3% year-on-year increase from GBP169.2 million in the same period in the prior year. We ended the quarter with an adjusted profit before tax for the period of GBP43.4 million, representing a 21.3% adjusted profit before tax margin. While the near-term outlook might be more challenging, we are managing the business for the long -term. We remain very focused on our Vision 30, which is our planned scale up as we head to 2030 and we are gearing Endava for exciting market opportunities. Post-COVID, we experienced an increase in demand which made it difficult to undertake some business optimization actions required to deliver on this vision. The recent cooling down in demand has given us a chance to recalibrate the business and to better position ourselves for continued growth into the next decade. Over the past three years, we have been building our industry vertical focus, establishing teams who market, sell, ideate and deliver into specific industries. This enables the incubation of technologies and capabilities attuned to the specific needs of clients and differentiates our solutions from generic horizontal technologies. We have now reorganized internally into our industry verticals and continue to invest in talent to help our clients adapt to the new disruptive technological waves, including AI and ML. As I highlighted in our last earnings call, last December, we saw a change in behavior as some clients added another level of due diligence to their decision making cycles, slowing the commencement of new projects and in some cases pausing existing spend as they reassess their priorities. I also noted that we'd seen an uptick in activity in February, which resulted in March being our highest revenue month in our history. Unfortunately, the recent bank failures triggered another wave of caution and as a result, the momentum going into March stalled and we now see lower demand than our previous guidance. To give this some color, the banking failures triggered a significant change in behavior in our PE portfolio company clients where they curtailed spend sharply. The drop in revenue in Q4 from Q3 is down to PE portfolio company reductions with the rest of the business flat allowing for lower working days in Q4. We believe that this now pent up demand will return when economic conditions recover. In the last quarter, our revenue growth year-on-year was driven primarily by both the expansion of work for our existing clients and the acquisition of new ones during the quarter. We continue to prioritize our efforts on larger relationships that can grow and scale. As a result, we continued growing the number of larger clients with a total of 155 clients, each paying us in excess of GBP1 million per year compared to 118 in the same period last year, representing a 31% year-on-year increase. We also saw the cohort of our largest clients, those who each spend over GBP5 million per year with us grow by 35% from 23 in the same period last year to 31 last quarter. Moving on to technology, it will be of surprise to no one that data and AI related work has been an important part of our business for a long time and has continually grown in scale, value and complexity as we engaged in larger and more involved pieces of work for our clients in recent years. Today I'll highlight some of the work we've been doing using this technology. It's important to note that the inherently exploratory and iterative nature of generative AI work aligns with Endava's natural way of working. We strive to work in an exploratory way with our clients, from ideation to production, working iteratively to understand their needs and opportunities. Applying the right technology in the right way and deepening our knowledge and the client's understanding as we progress together. This allows us to achieve a rapid time to initial value, but also lasting and sustainable value for the client in the long-term. We deliberately bracket data and AI together as AI is dependent on data to train its models to extract patterns and insights. So our skills across the data spectrum directly support our work in the AI field. Our work in data and AI is varied, both in business domain where we work across a wide range of industries and in the technical nature of the work. This area is varied being a continuum from traditional BI based data work at one end to AI based analytics and generative AI at the other with the different aspects complementing each other. Our projects vary from data warehousing and reporting through modern data engineering where we solve the big problems clients have in organising their data, so that it can be used profitably through building leading edge data platforms to provide clients with environments to exploit the potential of their data. We also provide advanced analytical work to unlock the value of data and AI projects where we harness the latest advantages in AI technology to solve practical problems in ways that simply wouldn't have been possible a few years ago. The first example I'd like to share is work we did for a dynamic New York based digital marketing agency who was struggling to manage and capitalize on the large amount of data they were collecting. We created a cloud based data platform to allow advertising budget allocation across different marketing channels based on real-time channel performance during an advertising campaign. This revolutionized our clients understanding of their in-flight campaigns, avoiding the long delays associated with traditional approaches by providing immediate insight into campaign performance through visual dashboards and analytics, allowing them to seize opportunities by responding immediately to trends and insights. In a completely different domain, we created a novel solution for bad debt collection for an international insurer. Our client recognized an opportunity to improve the bad debt collection process by analyzing data from a range of older systems. We implemented a data platform solution that materially improved their understanding of this difficult part of their business by providing analysis and visualization of patterns and trends in bad debt collection. This allows tactical response to immediate problems as well as strategic optimization of the process. SOPHiA GENETICS, a global cloud native data driven software company in the healthcare space, engaged us to optimize a federated data query processing implementation to increase throughput and lower cloud costs. Our team did a cost performance comparative analysis between various technologies and designed the architecture and implementation. Moving on to a more AI centric example, we applied modern AI to a very traditional industry when we worked with a Central European bank, [NLP] [00:20]*05 banker to supply AI to modernize their retail banking experience. Our client's goal was to make their customer's financial management insight proactive, engaging and empowering. To do this, they needed a powerful mechanism to classify banking transactions. We created a categorization engine that classifies very large numbers of retail bank transactions into categories such as grocery shopping, health and leisure, adapting the categories over time by learning from customer input. The categorization is an important component of the bank's new digital customer experience driving customer loyalty, a push for new customers and new cross-selling opportunities by allowing the bank to better understand their customers and the customers to understand and optimize their spending patterns. We've also done ideation work in the AI area. For example, we completed a project for a management consultancy firm to encode data from medical records into knowledge graphs, which could then be analyzed using a graph neural network for anomaly detection. This is designed to drive better patient outcomes and help medical practitioners to improve their medical practice by identifying potential mistakes in treatment and insights into physician behavior and decision making. Another advanced project example is one of our internal R&D projects in the area of generative AI, which developed a system to allow game designers to generate 3D visual assets such as characters and gameplay environments using natural language, significantly improving the productivity of the game designers by providing them with a rich source of inspiration as well as an artistic digital assistant to rapidly perform many of the routine graphical design tasks for them. Endava is currently engaged in the development of two distinct accelerators, concentrating on large language models, leveraging our partnership with Google. We've been given early access to their enterprise generative AI tooling. We've applied this against the insurance industry, successfully, demonstrating the practical utility of generative AI within a business environment. We've developed an interactive workshop highlighting the optimization of interactions between brokers, underwriters and compliance officers by employing instruction based tasks and chain of thought reasoning prompts. This innovative approach has the potential to transform complex business processes, ultimately enhancing clients operational efficiency and positively impacting their bottom line. The second accelerator involves a comparative analysis of cost performance features and industry specific capabilities of various commercial and open source LLMs. Endava is currently evaluating models from Open AI, Google and open source within the context of three industry verticals healthcare, financial services and insurance. The analysis evaluates the strengths and capabilities of each model in relation to industry specific client implementations. The knowledge we gain from this exercise is foundational in delivering effective applications of AI for our clients because the nuanced understanding we are gaining of how the different models behave in different industry scenarios will allow us to apply the right technology to each client scenario. So de-risking the work and avoiding lengthy experimentation phases for model selection. The hunger for data to train computer vision based machine learning models has prompted us to build a synthetic data generation accelerator. This highly customizable pipeline can generate tens of thousands of uniquely rendered images tailored to specific scenarios, all geared to accelerate the training and continued performance enhancement of these models. Paired with our comprehensive data science and machine learning expertise, this new capability has opened up new opportunities with both existing and new clients. Finally, we're working with large language model technologies like ChatGPT and GitHub Copilot, trialling them within the firm and building proof -of-concept applications with them to explore their potential, understand their limitations and identify the problems that we can apply them to in our business and with our clients. In summary, data has been an important area for us for a long time and we see more and more interest and an increasing variety of work in this area, which is being accelerated further by the recent advances and interest in AI, which we are well placed to respond to. We believe these latest technological developments will be an important source of additional work opportunities for Endava. Clients will spend less on legacy work, leaving larger budgets for complex transformation work that will continue to need delivery by experienced, high performing cross-functional teams who will deliver results faster using generative AI tools. Additionally, this new technology will improve productivity across the board, allowing for higher spend. And finally, we expect lots of high value projects to emerge as our clients try to apply generative AI to their businesses for which they are likely to need our help. I'm excited about our recent acquisition of Mudbath, an Australian based technology firm specialising in strategy, design and engineering services. Mudbath partners with businesses to build new digital solutions, enhance user experiences, and accelerate digital transformation programs across enterprise systems, web and mobile products using their proven agile delivery methodology. Mudbath's clients span broad industry verticals, including retail mining and adjacent activities, including rail and tools, health insurance, banking and travel and will help in our strategic intent of diversifying away from the UK and from payments and financial services. The acquisition follows our organic entry into Australia in 2021 and the acquisition of Lexicon, an Australian based consulting design and engineering firm in 2022. We continue to see Australia as a growing and attractive market with strong demand for high quality technology product creation delivered both onshore and near-shore by multidisciplinary delivery teams. Mudbath's teams and strong client relationships are expected to complement Endava 's expanding near-shore capability in Malaysia and Vietnam to continue to deliver innovative, high quality digital solutions. I remain excited about our growth prospects in the Asia Pacific region. We're delighted to share some highlights of our We Care sustainability approach over the past few months. To mark International Women's Day, throughout March, we recognized the impactful work and contribution of women across our global organization. We featured some of these amazing women and their stories internally and on social media. We also organized internal and external events to support our women in Tech Focus. We brought together some of the most senior women at Endava across geographies and business functions to talk about the importance of diversity, the role women play in the working world. Sharing some of their career journeys and giving advice to women in the tech space. To celebrate Earth Day, we rallied behind this year's theme Invest in our Planet, which highlights the importance of dedicating our time, resources and energy to understand and address climate change and other environmental challenges. As an example, we started to engage with our suppliers for awareness and joint actions to reduce the environmental impact of our operations. We ended the quarter with 11,742 employees, a 6.7% increase from 11,001 in the same period last year. We've made the strategic decision to increase our selectivity regarding our recruitment efforts and are focusing on areas of strong demand plus sales and marketing. In summary, despite the recent challenges based on our conversations, we believe clients continue to prioritize digital transformation in their IT budgets. I'll now pass the call on to Mark, who will walk you through our financial results for the quarter and provide guidance for the coming quarter and the fiscal year.