How?

Going Non-Linear

Get beyond the constraints of the linear services model.

Ian H Smith

As Artificial Intelligent (AI) Chatbots and Agents become increasingly adopted and as enterprises increasingly look for better value for money from their creative, healthcare, professional and tech services providers, the linear billable people hours business model is under threat from AI.

Knowledge-intensive services firms have long relied on a linear revenue model where income is directly tied to hours worked. However, the advent of AI has disrupted this structure. Tools like generative AI can draft documents, analyse data, and streamline workflows in a fraction of the time once required, reducing billable hours.

While AI enhances efficiency, it paradoxically squeezes profitability as fixed costs (e.g., salaries, overhead) do not scale down proportionally. A study by McKinsey & Company (2023)2 highlights that AI could automate up to 30% of tasks in professional services by 2030, amplifying this trend. The result is a shrinking margin where revenue growth cannot outpace cost increases.

Traditional professional services operate on a fundamentally linear business model: more clients require more billable hours, which necessitates more staff (Susskind & Susskind, 201514). Hence a linear (straight line) relationship between sales and costs.

In an increasingly competitive and dynamic market landscape, organisations who are inherently knowledge-intensive services operations face inherent limitations tied to the linear model of hourly-based services, where costs simply grow linearly with revenue.

To transcend these constraints and unlock sustainable, scalable growth, Going Non-Linear offers a transformative strategy that leverages your organisation's existing expertise - a brainware-to-software digital innovation - resulting in Software-as-a-Service (SaaS) ventures emerging.

Knowledge-intensive organisations can leverage AI-powered technologies, in the form of SaaS apps, to move beyond linear operational models and adopt strategies and initiatives that allow for exponential growth1. This means encountering and overcoming several challenges:

  • Geographical Constraints. Expanding to new regions increases workforce costs.
  • Customer Dependency. High reliance on fewer customers means delays and losses.
  • Resource Allocation. Fluctuating demand leads to inefficiencies in resource utilisation.
  • Competitive Pressures. Increasing competition drives down rates, eroding value.

These challenges necessitate a strategic pivot towards more scalable, predictable and recurring business model. Hence, Going Non-Linear.

Who?

With the emergence of AI and a growing questioning of the billable hours business model, any creative, professional or tech services firm is facing a significant decline in business1. As AI Agents become Copilots augmenting human labour, whilst this increases productivity per person, in the absence of organic growth of business-as-usual, it will ievitably lead to job cuts.

When you look at the trajectory of innovation, AI Agents will emerge as Coworkers: not merely augmenting, but also replacing human labour. Although this may start with low value, repetitive tasks, over time, this AI Automation will eat further into higher-value knowledge worker roles.

So, if you lead a creative, professional or tech services firm, now is the right time to embark on a Going Non-Linear transformation. The next section of this post provides you with a compelling argument for doing this now.

Why?

As a creative, healthcare, professional or tech services firm, with a SaaS venture you can achieve 5-10x annual revenues6 as an exit valuation of the firm, versus <1x annual revenues with a linear, billable hours services firm. Add to this limitless expansion of a SaaS business versus constraints of a billable hours model and you have a compelling reason to embrace Going Non-Linear!

By harnessing the power of Design Thinking3 and Value Engineering4, at Being Guided we can help you to build a solid case for transformation to Going Non-Linear and getting beyond a linear revenue model. This is a surprisingly easy and low risk move to make, as you will see below.

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How?

As market demands evolve and technology advances, there is now a pressing need for knowledge-intensive services firms to innovate beyond linear hours. This means embracing a combination of AI and No-Code digital innovation. At Being Guided we see this as being underpinned by Design Thinking and Value Engineering.

As the name implies: Design Thinking3 is thinking (and acting) like a designer. Being curious, restless and constantly challenging business-as-usual. It is all about solving problems in a human-oriented way. In order to generate receptivity and rapport, empathy is the key to success.

Design Thinking is strengthened by Value Engineering4: mapping out a solid use case, financial justification and technology preferences for high-value products and services.

Going Non-Linear presents a strategic, safe pathway to transform your organisation's intellectual capital into scalable SaaS solutions, ensuring sustained growth, increased customer experience and competitive differentiation in the marketplace.

Going Non-Linear is a comprehensive strategy designed to unlock the hidden potential within your organisations's expertise by transforming brainware into software. This approach enables you to:

  • Enhanced Scalability. Develop apps marketed globally with no increases in workforce.
  • Increased Margins. Technology to deliver more efficiently, reducing operational costs.
  • Improved Client Engagement. Offer innovative tools that provide deeper client relationships.
  • Strengthened Position. Establishing as a leader in innovation within your industry.

By adhering to these principles, we commit to work at Being Guided that starts with identifying and engaging your early adopter clients for new digitised services delivered on a SaaS technology. We will work with you through the entire process to timely monetisation of SaaS.

At Being Guided we believe that this collaborative approach will lead to you achieving greater customer satisfaction, stronger product-market fit (PMF), and ultimately, greater financial success. Now let's take a look at where Going Non-Linear applies and then, what technology we apply.

Where?

Let's consider typical knowledge-intensive services that are vulnerable to AI commoditisation.

At Being Guided we deliver No-Code innovation and SaaS solutions on a world-class technology: Google AppSheet, powered by Google Gemini AI. Going Non-Linear addresses the declining linear revenue challenge by introducing No-code apps rapidly and at low cost.

Here's some use case scenarios:

Legal Services: Contract Analysis and Generation.
Law firms traditionally bill substantial hours for contract review and drafting. Several forward-thinking legal practices have developed AppSheet applications that leverage Gemini AI to automate these processes. A mid-sized corporate law firm can create an AppSheet application that allows clients to self-generate customised NDAs, employment agreements, and service contracts. The app can use Gemini AI to analyse input parameters and generate appropriate clauses based on the firm's expertise. What once took 3-5 billable hours can now happen in minutes, as the firm collects subscription revenue from hundreds of users (Katz, 20138).

Architectural Design: Space Planning and Visualisation
Architectural firms typically charge hourly rates for preliminary space planning and design concepts. An architectural practice specialising in commercial interiors can develop an AppSheet application that allows clients to input space requirements, budget constraints, and aesthetic preferences. The app, powered by Gemini AI, can generate preliminary floor plans and 3D visualisations based on the firm's design principles and experience. This tool will serve as both a lead generation mechanism and a standalone SaaS product, creating a new revenue stream while reducing the time architects spend on initial concepts (Bernstein, 20189).

Management Consulting: Strategic Analysis
Strategy consultants traditionally conduct market analyses through labour-intensive research and expert interpretation. A boutique consulting firm can create an AppSheet app that automates competitive intelligence gathering. The app can use Gemini AI to crawl public data sources, analyse financial reports, and synthesise findings according to the firm's proprietary frameworks. Clients subscribe to industry-specific dashboards that previously would have required weeks of consultant time to produce (Christensen et al., 201310).

Creative Agencies: Content Generation and Campaign Planning
Advertising and marketing agencies bill substantial hours for content creation and campaign planning. A digital marketing agency can develop an AppSheet app that helps clients generate social media content calendars and ad copy variations. The app can use Gemini AI trained on the agency's successful campaigns to suggest content themes, create draft copy, and recommend posting schedules. What once required ongoing agency involvement now operates as a self-service tool with tiered subscription levels (Kietzmann et al., 201811).

Financial Advisory: Investment Analysis and Portfolio Optimisation
Financial advisors traditionally charge for personalised investment analysis and recommendations. An investment advisory firm can create an AppSheet app that provides automated portfolio analysis and rebalancing recommendations. The app can use Gemini AI to apply the firm's investment philosophy to client portfolios, identifying opportunities and risks based on market conditions. This tool extends the firm's reach beyond high-net-worth clients to a broader market segment through a subscription model (Fisch et al., 201912).

When?

Converting brainware to software requires careful planning. Davenport and Kirby (2016)13 suggest focusing on tasks that are:

  • Rule-based and repeatable: Processes with clear decision trees.
  • Data-intensive: Activities requiring analysis of large information sets.
  • Expertise-driven but formulaic: Work that follows established patterns.

This is when to apply Fierce Reduction: the practice of aggressively simplifying all business processes, tasks and information systems by removing redundant or non-essential elements before considering a brainware to software transformation. We always start Going Non-Linear transformation with a simplifying mindset. Less is more.

As described above, Fierce Reduction woreks best when embracing Design Thinking as the way to engage all stakeholders in Going Non-Linear, reinforced by the financial validation of applying Value Engineering.

What?

Simply put, Going Non-Linear means digitising your know-how (brainware) into what we call a No-Code Platform: a technology that lets non-programmers (Citizen Developers) translate everyday processes and tasks into published software - specifically, Software-as-a-Service (SaaS) applications. So, this means co-designing apps with a broader set of stakeholders.

At Being Guided we deliver No-Code innovation and SaaS solutions on a world-class technology: Google AppSheet, powered by Google Gemini AI. Going Non-Linear addresses the declining linear revenue challenge by introducing No-code apps rapidly and at low cost.

Google AppSheet, acquired by Google in 2020, exemplifies this low-cost, low risk approach with Going Non-Linear by enabling firms to create apps from existing data sources like Google Sheets or Salesforce, while Gemini AI enhances these apps with Natural Language Processing (NLP) and AI generative capabilities7.

If you are a Google Workspace customer with Business Plus licences, AppSheet is free. At Being Guided we can deliver fixed-price Annual Subscription Fees for your first SaaS app, including the complete design, development support, starting at just £9,000 per annum.

What Gemini gives us is the ability for Citizen Developers to scope-out a Google Appsheet app, as the starting point for No-Code First innovation in pursuit of Going Non-Linear.

Vibe Coding, introduced by Karpathy in early 202516, leverages large language models (LLMs) to shift programming from manual coding to conversational AI-driven development, reducing the need but not (yet) eliminating the need for traditional human coders.

Gemini AI then processes Instructions to generate, refine, and even debug an entire codebase as No-Code at its core, Vibe Coding lets non-programmers focus on the big picture -what they want to build - rather than getting bogged down in syntactical details

Think of Vibe Coding as communicating the essence or 'vibe' of what you want, while Gemini AI handles the technical implementation with the No-Code Platform: Gemini AppSheet. Rather than coding from scratch, you articulate your requirements in plain language.

The alternative to Google AppSheet as a No-Code Platform is Salesforce Lightning Platform. At Being Guided we have built many SaaS apps on Salesforce technology, often enhancing its core CRM product: Salesforce Sales Cloud. This is perhaps better known than Google AppSheet, but carries relatively higher subscription fees, although still provides a solid No-Code foundation.

In some cases there may be a good use case for Salesforce acting as the primary data source for Google AppSheet, especially if Salesforce CRM systems are in place at the time of starting a new digital transformation with Going Non-Linear.

There is a common AI architecture between Google and Salesforce, where Gemini was recently adopted by Salesforce for its future AI innovations, due to the inherent strenths of this AI Large Langiage Model (LLM)16.

Next?

Let's Meet to explore this further.

References

  1. Iansiti, M., & Lakhani, K. R. (2020). Competing in the age of AI: How AI is redefining business strategies. Harvard Business Review, 98 (1), 60-67.
    https://hbr.org/2020/01/competing-in-the-age-of-ai
  2. McKinsey & Company. (2023). Valuing high-growth companies. https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/valuing-high-growth-companies
  3. The Hasso Plattner Institute of Design. (2004) Stanford d.school. https://dschool.stanford.edu/about
  4. Miles, L.D. (1947). The Lawrence D. Miles Value Engineering Reference Center Collection.
    https://minds.wiscon.edu/handle/1793/301
  5. Jobs, S. (1997) Apple Worldwide Developers Conference. https://apple.fandom.com/wiki/Worldwide_Developers_Conference
  6. Bessemer Venture Partners. (2022). The state of the cloud 2022: SaaS valuation benchmarks.
    https://www.bvp.com/atlas/state-of-the-cloud-2022
  7. Google Cloud. (2023). AppSheet. No-code app development.
    https://cloud.google.com/appsheet
  8. Katz, D. M. (2013). Quantitative legal prediction—or—how I learned to stop worrying and start preparing for the data-driven future of the legal services industry. Emory Law Journal, 62(4), 909-966.
    https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2187752
  9. Bernstein, P. G. (2018). Architecture, design and data: Practice competency in the era of computation. Routledge.
    https://www.researchgate.net/publication/328045022_Architecture_Design_Data_Practice_Competency_in_the_Era_of_Computation
  10. Christensen, C. M., Wang, D., & van Bever, D. (2013). Consulting on the cusp of disruption. Harvard Business Review, 91(10), 106-114.
    https://hbr.org/2013/10/consulting-on-the-cusp-of-disruption
  11. Kietzmann, J., Paschen, J., & Treen, E. (2018). Artificial intelligence in advertising: How marketers can leverage artificial intelligence along the consumer journey. Journal of Advertising Research, 58(3), 263-267.
    https://www.researchgate.net/publication/327500836_Artificial_Intelligence_in_Advertising_How_Marketers_Can_Leverage_Artificial_Intelligence_Along_the_Consumer_Journey
  12. Fisch, J. E., Labouré, M., & Turner, J. A. (2019). The emergence of the robo-advisor. In J. Agnew & O. S. Mitchell (Eds.), The disruptive impact of FinTech on retirement systems (pp. 13-37). Oxford University Press.
    https://academic.oup.com/book/35249/chapter-abstract/299804888?redirectedFrom=fulltext
  13. Davenport, T. H., & Kirby, J. (2016). Only humans need apply: Winners and losers in the age of smart machines. Harper Business.
    https://hbr.org/webinar/2016/04/only-humans-need-apply-analysts-in-the-machine-age
  14. Susskind, R., & Susskind, D. (2015). The future of the professions: How technology will transform the work of human experts. Oxford University Press.
    https://academic.oup.com/book/40589
  15. Karpathy, A., & Roose, K. (2025, March 10). Vibe coding and the rise of AI-driven software development: A paradigm shift. Journal of Artificial Intelligence Research, 82, 145–167.
    https://www.index.dev/blog/vibe-coding-ai-development
  16. Salesforce. (2025, February 24). Salesforce and Google bring Gemini to Agentforce, enable more customer choice in major partnership expansion. Salesforce Newsroom. https://www.salesforce.com/newsroom/salesforce-and-google-bring-gemini-to-agentforce