According to Joanne Chen and Jay Gupta¹, AI is creating a paradigm shift: a transition from Software-as-a-Service (SaaS) to Service-as-Software (SaS), driven by Ariticial Intelligence (AI). At Being Guided we believe that this is a catalyst for achieving more value from less IT spend.

Forrester's John Bratincevic² goes even further, and in a blog post asked a significant software vendor executive, in relation to AI and software development, a key question: "Why are none of the vendors talking about this?". The answer was dramatic:

"Nobody wants to admit that their own death is coming soon".

This is as significant as the previous, notable pardigm shifts in the IT industry: Personal Computing (1980s); Client/Server (1980s-1990s); Internet (1990s-2000s); Open Source (1990s); Mobile (2000s-2010s); Cloud (2000s-2010s); and now, Artificial Intelligence (2020s).

As with any technology paradigm shift, the ability for organisations to respond is key. Service-as-Software is the building of Web apps on an Open Source foundation, powered by AI. Software-as-a-Service (SaaS) is is the buying of Web apps on a Closed Source foundation, albeit extendible with Low-Code software development techniques and configurable, to tailor user experience.

Service-as-Software (SaS) means a significant reduction in IT costs - both in terms of software licences and professional services. It requires a human-first approach to explaining what is, in this case, an AI-first outcome.

SaS and SaaS: Coexistence and Convergence

At Being Guided we believe that the combination of first generation Software-as-a-Service (SaaS) and system integrators (delivering in a world where maximising billable hours is the mission) is going to be displaced by AI-Powered Digital Innovation and Service-as-Software - but over time.

However, many Software-as-a-Service (SaaS) publishers are enormous corporations with significant financial power and customer bases. The market leader in this category today is Salesforce, with over 150,000+ customers and over $10billion in cash reserves.

Business-as-usual IT is bloated, driven by complex thinking and now, something that resembles the bureaucratic 'blob' of the mainframe era. At Being Guided we are inspired by Design Thinking and embrace the growing power of AI to defeat the blob.

In the real world we see SaaS and SaS coexisting for many years to come. Over time, SaaS publishers will become SaS enablers - with a pragmatic blend of build and buy approaches to AI-Powered Digital Innovation.

First Design Principle: Fierce Reduction

Our first Design Principle (and name of this blog post) is Fierce Reduction. With IT Transformation this simply means:

Eliminate everything you can - and keep eliminating everything you can.

Less is more.

IT Transformation

At Being Guided we define Service-as-Software as comprising three interdependent elements in disrupting business-as-usual IT with AI-Powered Digital Transformation, as explained in more detail below:

• Design Thinking
• Value Engineering
• AI Enabling

This is nothing less than the re-imagining of Software-as-a-Service to Service-as-Software - AI-powered Digital Innovation. It is where our Design Thinking Platform supports these three elements, as illustrated in the infographic below. It supports our quest for delivering to our customers more value for less IT spend - following our first Design Principle: Fierce Reduction.

Focusing on AI-Powered Digital Innovation

This applies to everything in business, public sector and nonprofit organisations: optimising AI-Powered Digital Innovation, typically starting with market-facing engagements. This means:

1. Setting clear, achievable goals that everyone understands and buys into.
2. Implifying and streamlining processes that deliver on the goals.
3. Asigning and measuring the execution of tasks that fulfill the processes.
4. Applying Fierce Reduction: eliminate everything you can.

We have to be human-first to facilitate radical IT Transformation. This is where Design Thinking is absolutely vital to success. This is asking customers to embrace new technologies, with many components coming from startups challenging the business-as-usual IT industry players.

As you will see below, the first stage in Design Thinking is Empathize. This is the most important stage. As a human-fist approach this means conversations with all stakeholders engaged in IT Transformation must follow this sequence:

Receptivity > Rapport > Trust > Truth

Purposeful Experimentation

Our Design Thinking Platform is our technology enabler for IT Transformation and AI-Powered Digital Innovation and Service-as-Software. This is inspired by Hasso Plattner Institute of Design and Stanford University d.school³. 

Further inspired by Jeanne Liedtka, Elizabeth Chen, Natalie Foley and Devis Kester⁴, who are the authors of The Experiementation Field Book, the Design Thinking Platform embraces what we call Purposeful Experimentation at Being Guided. To quote this book:

"Experimentation protects you from overspending on a solution that will not work for the people you designed it for. By placing small bets and learning at a fast pace, you can learn whether your concept really fulfills the unmet needs of your users."

Our AI-Powered Digital Innovation is focused on delivering tangible Service-as-Software outcomes that deliver measurably more value for IT spend. But our approach is also focused on starting small and generating results fast.

Design Thinking

Design Thinking means, as the name implies: thinking (and acting) like a designer. Being curious, restless and constantly challenging business-as-usual. It is all about solving problems in a people-oriented way. Being human-first to enable AI-first outcomes.

The Hasso Plattner Institute of Design and Stanford University (the d.school³) enabled Design Thinking as a mult-stage method for innovation and Mutual Value Discovery between buyers and sellers. As you will see below, this is a very easy to understand, common sense approach.

The Stanford d.school Design Thinking method provides six (6) stages: Empathize; Define; Ideate; Prototype; Test; and, Implement. This offers a structured yet flexible framework to better understand users, challenge assumptions, redefine problems, and for us at Being Guided, rapidly co-create AI-powered Digital Innovations with our customers.

Stage 01. Empathize

Purpose: Understanding the users and their needs.

Application in AI-Powered Digital Innovation: In-depth user research, such as interviews, surveys, and observation, provides insights into user behaviours, needs, and motivations. This is crucial to ensure that the solution developed genuinely addresses real problems.

Stage 02. Define

Purpose: Clearly articulating the problem to be solved.

Application in AI-Powered Digital Innovation: After gathering user insights, define the core problem in a user-centered manner. This stage is about synthesising observations and articulating the problem in a way that guides the development of digital solutions.

Stage 03. Ideate

Purpose: Generating a range of creative ideas to solve the defined problem.

Application in AI-Powered Digital Innovation: This phase involves brainstorming and exploring a wide array of potential solutions, encouraging out-of-the-box thinking. It's essential for AI-Powered Digital Innovation, as it embraces creativity and leads to the discovery of effective digital solutions.

Stage 04. Prototype

Purpose: Turning ideas into tangible products.

Application in AI-Powered Digital Innovation: Prototyping involves developing scaled-down versions of the product or its specific features. Prototyping is crucial for visualising how digital solutions work and for gathering feedback before full-scale Implementation at stage 06.

Stage 05. Test

Purpose: Gathering feedback and refining the prototype.

Application in AI-Powered Digital Innovation: Testing includes formal test automation plus user trials and feedback collection on the solution. This helps in understanding the user experience, identifying issues, and validating the effectiveness of digitisation.

Stage 06. Implement

Purpose: Finalising the solution and launching it.

Application in AI-Powered Digital Innovation: The final stage involves finalising the design based on testing feedback, completing the development, and launching the solution. This phase ensures that the solution is polished, user-tested, and ready for everyday use.

Value Engineering

At Being Guided, we apply AI-Enabled Value Engineering to determine Service-as-Software value over price. This includes calculating the cost for not purchasing a solution in timely manner: the true cost of remaining with IT business-as-usual.

This is key to our constructing business value pricing for our AI-Powered Digital Innovation to create Service-as-Software solutions that lead to more value for less IT spend. Value Engineering is an integral part of our three elements this approach to IT Transformation.

There has been much talk recently about AI causing a shift from Software-as-a--Service to Service-as-Software. This is a play on words. It means that the former is more a 'buy' of packaged software, and the latter is more of a 'build' of custom software, powered by AI as a Copilot.

Conceptually, the argument here is that as AI-Powered Digital Innovation increasingly automates everyday tasks, organisations will need less Users for any particular Service-as-Software app. At Being Guided we see this argument as rhetoric and that the Per User Per Annum Pricing Model is still relevant for many Service-as-Software use cases.

There will be a growing number of Service-as-Software use cases where Usage Pricing, based on some form of metering of transactions or other measurable value is agreed. There may be use cases where it is blend of User Pricing and Usage Pricing works. Whatevever it is, it cannot be a price book where one size fits all.

Mutual Value Discovery

At Being Guided we apply Mutual Value Discovery to help our customers and partners to agree on value-based pricing that works for everyone. Overall, our goal with AI-Powered Digital Innovation is to generate more value for less IT spend. This is Fierce Reduction, applied.

The combination of Design Thinking and Purposeful Experimentation is our method to ensure meaningful, measurable outcomes from our customer's commitment to Service-as-Software IT Transformation.

ROI Modelling

We start with a simple question for the buyer:

What is the cost of NOT buying the Service-as-Software Solution?

Firstly, let's look at the Return On Investment (ROI) Model - a general formula:

ROI = (Cost of Investment / Net Profit​)×100%

To adapt this formula for an As-Is vs. To-Be comparison, consider:

Net Profit: This will be the difference in profits between the Future State (To-Be) and the Current State (As-Is).

Cost of Investment: This is the cost incurred to move from the Current State (As-Is) to the Future State (To-Be).

Given the above considerations, the formula becomes:

ROI = (ProfitTo−Be​ − ProfitAs−Is​​ / Cost of Transition) × 100%

Where:

Profit To-Be = Profit or (benefit) in Future State
Profit As-Is = Profit (or benefit) in Current State
Cost of Transition = Cost to move from As-Is to To-Be

Note: If you're measuring benefits other than strict monetary profits, such as time saved or other intangible benefits, ensure you can convert these benefits into a monetary value for this to be valid.

To calculate the Return On Investment (ROI) from Digital Innovation with the specified inputs, we can formulate several equations. Let's define the variables first:

BVAs-Is = Current State (As-Is) Business Value generated per annum without Solution.
BVTo-Be = Future State (To-Be) Business Value generated per annum after investing in Solution.

COS = Cost of Solution.
ROI = Return on Investment as a ratio relative to the Cost of Solution.
CoD = Cost of Delay per day when not investing in Solution.
CoDN = Cost of Doing Nothing per day when not investing in Solution.
CoDday = Cost of Delay per day when not investing in Solution.
CoDNday = Cost of Doing Nothing per day when not investing in Solution.

Calculating ROI from Solution:
Net_Gain - BVTo-Be - BVAs-Is

Calculating ROI:
ROI - Net_Gain - CDI / CDI
The ROI is expressed as a ratio. Multiply by 100 to get a percentage.

Cost of Delay (CoD):
This represents the loss per day by delaying the Solution purchase. Assume the delay starts from the beginning of the year and goes on for d days:
CoD = BVTo-Be - BV As-Is (d x CoDday) - CDI / CDI

Cost of Doing Nothing (CoDN):
This is the loss per day for not implementing the Solution. Similarly, for d days:
CoDN = BVAs-Is - (d x CoDNday) - CDI / CDI

This Return On Investment (ROI) Modelling must also be set in the context Current State ('As Is') versus Future State ('To Be'). This is where the quantification of the value of AI and a simplified Service-as-Software underpinning it leads to creating a compelling argument for your timely Digital Innovations. This leads to the third element: AI Enabling.

AI Enabling

Ai Enabling is a rapidly-evolving features of IT Transformation: from AI Copilots that improve human productivity to Agentic AI that operates autonomously, without constant human input. It is the former - AI Copilots - where we see the biggest gains today in delivering the Ozma.io Open Source solution, as illustrated below.

For Agentic AI our Design Thinking Platform provides a solid foundation to calculate the value and design proof-of-concepts of autonomous automation versus human task management. As the underlying Large Language Models (LLMs) improve, so too our AI Copilots and Agentic AI solutions will generate yet more simplication of IT. Remember: it's always Fierce Reduction.

With Design Thinking and Value Engineering in place, our Design Thinking Platform provides the tools to execute digital innovations with AI-powered Digital Innovation. As described below, this is managed via series of Objects and Templates:

The Design Thinking Platform Templates including Customer Relationship Managerment (CRM) Objects are summarised below :

CRM Objects

• Leads. Lead Records
• Contacts. Contact Records
• Accounts. Account Records
• Opportunities. Engagement Pipeline

Design Thinking Templates

• Trackers. Progress Tracker
• Matrixes. Value/Effort Matrix
• Snapshots. Concept Snapshot
• Storyboards. Storyboarding Engagement
• Assumptions. Surfacing Assumptions
• Prioritisations. Prioritising Assumptions
• Evidence. Evidenced Assumptions
• Sorts. Data Sort
• Continuums. Say/Do Continuum
• Decisions. Test Design Decision Flow
• Digests. Test Digest
• Formats. Prototype Format Selection Tool
• Checklists. Test Audit Checklist
• Histories. Concept Test History
• Chats. Supercog and ChatGPT AI Integrated
• Models. Return On Investment (ROI) Models

AI-Powered Platforms

Our Design Thinking Platform Templates and CRM Modules are the foundation to deliver custom Service-as-Software solutions. As illustrated above, this is an Open Source Service-as-Software (SaaS) solution built on the Ozma.io technology.

Leading Software-as-a-Service (SaaS) solutions will continue to evolve and, again, as illustrated above, this is where Supercog provides the AI-Powered Integration between multiple systems. At Being Guided we have a real world customer for this: NHS - Europe's largest organisation.

Supercog combines unstructured knowledge with structured data, knowledge search and real-time system access. So, as illustrated in the infographic above, this could be a 'Text-to-Action' use case combining Salesforce and Slack reciords with information extracted from multiple documents.

For Open Source Service-as-Software Hosting Amazon Web Services (AWS) provides a foundation with choice of Data Residency and assured security and uptime performance. This is the same Infrastructure-as-a-Service (IaaS) that underpins Salesforce Software-as-a-Service.

AI-Powered Integration

In the real world, starting with AI-Powered Digital Transformation requires Design Thinking and Value Engineering to determine Assumptions and Prioritisations as its Roadmap over sensible timelines. This becomes a lifecycle progression: Integrate > Surround > Replace.

Here we apply our Supercog Agent Platform to accelerated Integrations between new AI-Powered Service-as-Software and multiple IT systems. Supercog comprises three elements:

Large Lanuage Model (LLM). This powers the Agent. You can choose amongst many different LLMs, including: GPT4o-mini; and, Claude Sonnet 3.5.

Agent. The Agent Instructions describe the work that you would like the Agent to perform. When you want to devote your Agent to a specific Task, then you will want to explain that Task in the Instructions.

Tools. You enable agents to perform work by giving them tools. Without any Tools an agent is limited to the capabilities of the underlying LLM. Tools include: Amazon S3; Discord; DuckDB; GitHub; Gmail; HubSpot; Jira; Salesforce; ServiceNow; Slack; Snowflake; and, Zapier.

References

1. Chen, J., Gupta, J. (2024) AI leads a service-as-software paradigm shift. Foundation Capital. https://foundationcapital.com/ai-service-as-software/
2. Bratincevic, J. (2024) AppGen Is An Existential Threat To The Enterprise App Business. Forrester Research, Inc. https://www.forester.com/blogs/appgen-is-an-existential-threat-to-the-enterprise-app-business
3. Stanford d.school. https://dschool.stanford.edu/about
4. Liedtka, J., Chen, E., Foley, N. and Kester, D. (2024) Experimentation Field Book. New York: Columbia University Press.