Key Benefits
- Strengthen your ability to value technology companies by applying valuation methods to tailored business models
- Address key technology company valuation challenges with confidence
- Understand how intellectual property, cost structures, and key technology metrics influence company valuation
Technical Content
Part One
Session 1
Defining the Problems
Differences between traditional corporate valuation and technology valuation
Handling data problems that emerge with early-stage technology companies
Summary review of valuation techniques and applications to technology businesses Dividend-based models
Main drivers of valuation: growth, risk and reinvestment rates
DCF model approaches
Cost of capital and risk discount rates
Cost to replicate models
Contributory asset charge calculations
Relief from royalty rates method
Multiples and benchmarking
Venture capital methods
Valuing early-stage development businesses and projects
A life cycle view of start-up companies
Start-up companies in context
Lifecycles and corporate cashflows
Characteristics of start-up technology companies and sectors
The key challenges with technology companies
Visibility – a key valuation challenge
Understanding the technology and applications
Market growth and penetration rates
Which benchmarks to use for future performance
Likelihood of success
Case study example of a current AI/ML technology company valuation
Session 2
Valuing Technology Companies
Valuation issues – Intrinsic Value and using DCF How to value existing assets
Cash burn and the effect on existing assets
Estimating cashflows and expenditure patterns
Evaluating the expected growth rate
Estimating the market size and rate of maturity development
Assessing the competitive response
Combining growth rate with investment intensity and return on investment
The future of the business – high growth and growth phases
Applying the appropriate discount rate and varying the rate over time
Evaluating the stable growth stage and calculating the terminal value
Inherent problems of using the DCF model to value technology companies
Assessing the likelihood of potential failure and adjusting the valuation figure
Valuation issues – Relative Valuation
Pitfalls in using multiple approaches for technology companies
Importance of using EBITDA if possible
Using revenue multiples
Using statistical analysis to improve the multiple comparisons
Determining the starting point – revenue multiples vs profitability multiples vs other multiples
Case study example of using the DCF and multiple approaches for technology valuation
Part Two
Session 1
Using AI Tools in Tech Valuation
Examples of valuation platforms using AI
Using AI tools to access data more efficiently
Benefits of AI models Speed to identify the most relevant benchmarks
Process unstructured data to provide deeper insights
Continuously update valuation models with real-time market data
Case study valuation model of Nvidia using ChatGPT5 to assess valuation inputs
Valuation Issues for a SaaS Type Business
Key valuation drivers Financials
Customer acquisition
Operations
Niche
Customer base
SaaS key metrics review
Churn rate Customer segment and monthly average churn rate
Customer acquisition cost (CAC) and customer lifetime value (CLTV)
Monthly revenue rate (MRR) and annual recurring revenue (ARR)
Magic number!
Customer acquisition channels
Valuation issues for specific tech companies, such as marketplace platforms, Web3/crypto companies, and AI-as-a-Service businesses
Case study example of valuing an AI-as-a-service business
Using the Real Options Approach
The problems inherent in using the NPV/DCF approach to valuation
Defining real options – patent rights, expansion option, abandonment option
Why real options are more applicable to technology companies
Basics of real option valuation using binomial trees and a lattice approach
Financial option pricing (Black-Scholes) and the link to real options
Management options and the value of strategic flexibility
Using real options approach to improve the understanding of technology valuations
Case study example of using the real options approach to value a technology start-up business
Session 2
Structuring an Exit
Governance/shareholders agreements in minority and majority acquisition Protecting VC’s investment
Exert influence to drive growth
Execute restructuring
Exits Trade sale, M&A, secondary purchase, repurchase, earn-outs
Majority versus minority rights
Stress testing the assumptions
Haircuts to the liquid market
Size of the market – possible restrictions on achieving exit
Controlling/veto/blocking powers for restructuring
Potential for restructure and impact on valuation
Liquidity impact on the fund
Covenants/lock-ups/gates/redemptions
Liquidation preference Multiples or accruing dividends
Non-participating, capped or uncapped
Anti-dilution protection full ratchet and weighted average provisions
Case study: achieving a successful exit
Training Objectives
Develop a comprehensive understanding of the unique challenges and intricacies involved in valuing technology companies, from start-ups to mature businesses.
Master the application of advanced valuation techniques specifically adapted for technology-driven business models, supported by extensive real-world case studies and practical examples.
Analyse the key financial and non-financial metrics that influence the valuation of tech companies, including SaaS-specific metrics, growth potential, and market trends.
Evaluate and compare various valuation models, such as DCF, real options, and multiples, to identify the most appropriate methods for different stages of a tech company’s lifecycle.
Gain expertise in handling common data limitations, uncertainties, and risk adjustments inherent in tech company valuations, especially in early-stage ventures.
Understand the impact of intellectual property, product lifecycles, and customer acquisition costs on the valuation of technology companies.
Effectively apply statistical techniques and benchmarking to refine relative valuations, ensuring robust comparisons across similar businesses.
Have copious use of practical examples throughout the course to illustrate the valuation techniques and problems.
Training Course Summary
This one-day programme has been designed to give a thorough review of the practical valuation of technology businesses, including AI/ML and SaaS. There will be copious use of practical examples throughout the day using AI tools such as ChatGPT5 and Grok as appropriate to illustrate the valuation techniques and problems. Delegates will use Excel to utilise the various model approaches.
Your trainer
Course Trainer · 17 yrs experience
- Valuation Courses
Our Valuing a Technology Company trainer is the Managing Director of an international advisory company specialising in advisory and development services to the corporate, banking and finance industry, which he has owned for the past 17 years. He is an experienced corporate finance professional with practical experience and extensive knowledge of corporate and structured finance in global financial markets.
He is a Visiting Fellow in the M&A department and Programme Director at Executive Development, Sir John Cass Business School, London, a member of the Visiting Faculty at Fuqua Business School and has previously worked as an advisor to the Overseas Development Administration in the UK, as well as EU PHARE and TACIS programmes throughout Europe and Russia.
The trainer’s main areas of expertise are corporate finance, M&A, corporate analysis and structured finance, asset securitisation, risk management, valuation, corporate credit processes, project finance and treasury management. He currently works with many global corporate and banking clients in these areas and he also acts as an Expert Witness for London law firms in respect of his areas of expertise.
The list of global clients is extensive and covers both European, Middle East, African and Asian markets. In the corporate market, he works extensively with large corporate clients, private equity firms, private investors as well as public sector companies such as the NHS and major law firms. He provides advisory and development services to these organisations, either through the relevant departments or directly to the senior line management.
He is also a well-known figure within the various training and development companies within Europe and regularly gives seminars throughout the world on his specialist topic areas and is a recognised expert in this area by many organisations.
He was previously the Managing Director of a subsidiary of Union Plc, a London merchant bank having previously worked with several high-profile global investment banks. He left Union Plc in 1996 to form his own international advisory Company.
The list of financial institutions and corporates with whom he has worked over recent years is extensive and includes: Allied Irish Bank, Alpha Bank, Bank of America Merrill Lynch, Bank of China, Barclays, Bayern LB, BT plc, Citibank, China Construction Bank, Credit Agricole, Credit Suisse, Danone, DECC, Deloitte, Dexia, Emirates Bank, E&Y, Euler Hermes, First Gulf Bank, FSA London, Garanti Bank, HBOS, Hohhot Bank Mongolia, HSBC, HVB, Iccrea Banca, Intesa SanPaolo, Central Bank of Ireland, KPMG, L’Oreal, Malta FSA, Mongolian Stock Exchange, Morgan Stanley, Mubabdala, NHS and many others.
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