Knowledge-intensive professional services firms suffer from the inherent limitations of the billable hours business model. Costs and revenues grow in a straight line and are invariably constrained by the availability of talent, the retention of key people, and all too often, a struggle to build an export business - missing out on the world's fastest-growing economies in the Asia-Pacific and elsewhere.

This model is Linear Revenues. If you look at it from a founders/shareholders/owners perspective, a services firm is rarely, if ever, valued at more than 0.5x Annual Recurring Revenue (ARR). Now look at how a Software-as-a-Service (SaaS) firm is valued. According to my AI-powered research today, this multiple compares to a range of 8-15x ARR.

In this blog post I set-out how we enable professional services firms to break out from challenges and risks of managing a business built on billable hours and constrained by geography, talent acquisition and talent retention. This is not a high risk, 'disruptive' value proposition but a safe, affordable transformation.

Getting Beyond Linear Revenues

The transition to SaaS is compelling for a knowledge-intensive services firm. It's brainware-to-software. And it's safe and fast. Time-to-market should be no more than 90 days to engage the first early adopter customer, followed by no more than another 90 days to have an approved, trusted app on the Salesforce AppExchange.

In summary, the compelling case for a professional services firm to transform brainware-to-software may be summarised as 5 things:

01. Increase income predictability.
02. Enable global reach.
03. Enhance profit margins.
04. Accelerate shareholder exit value. 
05. Reduce entry costs for clients.

Non-Linear Transformation

So, let's look at how a services firm can build a new digital venture. It's called Going Non-Linear. Let me explain why. Unlike the billable hours business model, a digital business venture, spun-out of a services firm, can grow revenue significantly faster than costs - hence, the name: Going Non-Linear.

At Being Guided, we help services firms to create a digital venture by designing a Software-as-a-Service (SaaS) application on a foundation of the Salesforce Lightning Platform. We blend the Salesforce technology with two other things to drive success: Design Thinking; and AI.

This journey to Going Non-Linear can be realised for initial costs of £12,800 to engage in Design Thinking Workshops and Value Engineering Discovery of 4 x 2-hour interactive Google Meet sessions. Thereafter, we move through clearly-defined stages of Discover, Design, Develop and Deliver - typically over a first release lifecycle of 90 days, lauching a Minimum Viable Product.

From engaging say, one early adopter end-customer with the Minimum Viable Product, as mentioned above, we typically see a rollout to a full release on Salesforce AppExchange in a complete life cycle of 180 days, including the Security Review process expanded on below.

Why Salesforce?

As a professional services firm, we are asking you to break away from the constraints of the Linear Revenues model and engage in Going Non-Linear with a brainware-to-software transformation. But why Salesforce?

Simply put, by designing and developing new SaaS apps on Salesforce Lightning Platform, the professional services firm avoids reinventing wheels, which is what happens when you adopt the 'full stack' approach to software design and development.

As illustrated above working with Salesforce becomes a Buy v. Build decision. Buy the Platform-as-a-Service (PaaS) and Infrastructure-as-a-Service (IaaS) layers. Build the Software-as-a-Service (SaaS) layer that's unique to your branware-to-software transformation.

Do not reinvent the PaaS or IaaS wheels by pursuing 'full stack' development

Salesforce Lightning Platform is a readily available PaaS and IaaS combination - with the IaaS layer running on Amazon Web Services in named geographic regions to meet exacting data residency requirements. The IaaS layer runs on Amazon Web Services (AWS) managed by Salesforce.

Do not reinvent the PaaS wheel by pursuing 'full stack' development. The costs are deceptively high - especially to achieve high-levels of certified cybesecurity. Do not be exposed to the financial risks of buying the IaaS layer directly AWS, Google Cloud Platform, Microsoft Azure).

The 'elastic' usage pricing model of these IaaS layers are notoriously difficult to predict with 'full stack' developments of the PaaS and SaaS layers, as your related customer acquistion and revenues grow. With Salesforce you simply pay a fixed fee, calculated as Per User Per Month.

The Emerging Role of AI

It would be a statement out of the 'University of the Bleedin' Obvious' to say Artificial Intellience (AI) is a truly transformative technology. So, saying anything about AI can be rapidly seen as outdated, as the innovation from big tech and some startups.

In the context of selecting Salesforce for a brainware-to-software transformation, Ai may be viewed as two categories of technology: Embedded AI; and, Overlay AI.

Embedded AI
For Salesforce Embedded AI was launched at Dreamforce 2024 as an extension of its technology, under the Agentforce brand. It is an AI Agent technology designed to work within the 'guardrails' of data inside Salesforce. As the Atlas Reasoning Engine becomes available in early-2025, Agentforce will go onan exponential journey of innovation and become a significant part of the Salesforce tech.

Overlay AI
The coexistance of Salesforce Embedded AI and a growing number of AI Agents that are developed independently of Salesforce, but act as a Connected Copilot will also grow fast in the weeks and months ahead. For our brainware-to-software transformations we aew working with Supercog as the developer's digital assistant (Connected Copilot) that can help with a large variety of tasks.

Connected Copilot

Supercog Agents are semi-autonomous programs that follow simple English instructions. Each Agent is powered by a Large Language Model (LLM) which gives it the ability to understand language, make plans and execute tasks, faster.

A Supercog Agent is composed of three parts:

Model. The LLM Model powers the Agent. You can choose amongst many different LLMs, including GPT3/4/4.o/4.o-mini, Anthropic Claude 3, and Meta LLama3.x.

Instructions. The Instructions describe the work that the developer would like the Agent to perform. If you just want to experiment it is not necessary to write any Instructions. But when you want to devote an Agent to a specific task, then the developer 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. 

Brainware-to-Software Transformation

We enable you to take the Brainware-to-Software journey through a series of Design Thinking Workshops. and Value Engineering Discovery sessions.

The Hasso Plattner Institute of Design and Stanford University (the d.school) 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 method provides 7 stages—Empathize, Define, Ideate, Prototype, Test, Iterate and Implement. This offers a structured yet flexible framework to better understand users, challenge assumptions, redefine problems, and for us at Being Guided, rapidly create No-Code Platform digital innovations.

Stage 01. Empathize

Purpose: Understanding the users and their needs.

Application in 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 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 No-Code Platform digital solutions.

Stage 03. Ideate

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

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

Stage 04. Prototype

Purpose: Turning ideas into tangible products.

Application in Digital Innovation: Prototyping involves developing scaled-down versions of the product or its specific features. Prototyping is crucial for visualising how No-Code Platform digital solutions work and for gathering feedback before full-scale Implementation at stage 07.

Stage 05. Test

Purpose: Gathering feedback and refining the prototype.

Application in Digital Innovation: Testing includes formal Test Automation plus user trials and feedback collection on the No-Code Platform Prototype. This helps in understanding the user experience, identifying issues, and validating the effectiveness of digitisation.

Stage 6. Iterate

Purpose: Try, This, Try That (T4) - fail fast, be brave!

Application in Digital Innovation: Iterating takes you back through any other previous stages and ensures that a mindset of continuous improvement is adopted and where moving fast does not mean breaking things, but every stakeholder fully engaged.

Stage 7. Implement

Purpose: Finalising the No-Code Platform and launching it.

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

AI-Powered Value Engineering

To price the SaaS app as Annual Recurring Revenue (ARR) - e.g. as per User per Annum - we apply Value Engineering to determine value over price and calculate the cost for end-customers not purchasing in timely manner.

This is where we combine Salesforce technology with Supercog, an AI Agent Platform, to act as the 'Connected Copilot' in converting the services firm's brainware into software. This technology is explained further below.

As the developer's digital assistant (Connected Copilot), Supercog can help with a large variety of online tasks. Unlike widely-available AI chat programs such as Chat GPT-4.o, Supercog safely connects to your real systems and real data, and helps developers get real work done, faster.

Supercog Agents are semi-autonomous programs that follow simple English instructions. Each Agent is powered by a Large Language Model (LLM) which gives it the ability to understand language, make plans and execute tasks, faster.

A Supercog Agent is composed of three parts:

Model. The LLM Model powers the Agent. You can choose amongst many different LLMs, including GPT3/4/4.o/4.o-mini, Anthropic Claude 3, and Meta LLama3.x.

Instructions. The Instructions describe the work that the developer would like the Agent to perform. If you just want to experiment it is not necessary to write any Instructions. But when you want to devote an Agent to a specific task, then the developer 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.

Creating the ROI Model

As with any new technology, for our early adopters of a new SaaS solution we must enable the services firm creating a new SaaS venture to answer a simple question:

What is the cost of NOT buying the SaaS app?

Firstly, let's look at the Return On Investment (ROI) Model - ageneral 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 Digital Innovation.
BVTo-Be = Future State (To-Be) Business Value generated per annum after investing in Digital Innovation.

CDI = Cost of Digital Innovation as a Recurring Annual Subscription.
ROI = Return on Investment as a ratio relative to the Cost of Digital Innovation.
CoD = Cost of Delay per day when not investing in Digital Innovation.
CoDN = Cost of Doing Nothing per day when not investing in Digital Innovation.
CoDday = Cost of Delay per day when not investing in Digital Innovation.
CoDNday = Cost of Doing Nothing per day when not investing in Digital Innovation.

Calculating ROI from Digital Innovation:
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 digital innovation. 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 innovation. Similarly, for d days:
CoDN = BVAs-Is - (d x CoDNday) - CDI / CDI

Engaging with our 4D Process

Our 4D Process has two initial phases: Discover and Design. These stages combine the 7 stages of Design Thinking with Value Engineering, to determine a solid Statement of Work (SoW) for the subsequent phases of Develop and Deliver, as illustrated above.

Discover
Objective: Uncover and map the firm's core competencies, unique methodologies, and client needs.
Activities:
Conduct Design Thinking Workshops abnd Value Engineering Discovery with key stakeholders to identify areas ripe for brainware-to-software.
Analyse existing processes to determine efficiency gaps and opportunities for enhancement.
Gather client feedback to understand pain points and desired outcomes.
Create a Software-as-a-Service (SaaS) solution on Salesforce where value may be defended over price and where the selection of either a Salesforce ISVforce or OEM Partner engagement - see below.
Design
Objective: Blueprint the Salesforce-powered SaaS applications that will encapsulate your firm's expertise. This is the realisation of brainware-to-software.
Activities:
Employ Design Thinking principles and Value Engineering outcomes to foster creativity and user-centric design.
Develop an App Objects, Fields and Flows using the Salesforce Lightning Platform.
Iterate designs based on stakeholder feedback to refine functionality and user experience.
Develop
Objective: Build robust, scalable, and secure Salesforce-powered SaaS applications that reflect your firm's brainware.
Activities:
Utilise the Salesforce Lightning Platform for rapid development and deployment, as either an ISVforce or OEM Partner with Salesforce - see below.
Integrate the Supercog AI Copilot to enhance functionality, automate tasks, and provide intelligent insights.
Implement best practices in software development to ensure reliability, security, and compliance.
Deliver
Objective: Launch and scale the SaaS apps, ensuring seamless adoption and continuous improvement.
Activities:
Develop comprehensive training programs and support materials for users.
Implement go-to-market strategies to promote the Salesforce-powered SaaS offerings to existing and new clients via an ISVforce or OEM Partner engagement with Salesforce - see below.
Monitor performance metrics and user feedback to drive enhancements and feature updates.

Engaging with Salesforce

At Being Guided we introduce knowledge-intensive professional services firms to Salesforce early in and Design Thinking and Value Engineering engagements, to ensure that the right Partnership model is taken for each phase towards monetising new SaaS apps.

There are two types of Salesforce Partner: ISVforce; and, OEM.

ISVForce: ISV Partners build and enhance Salesforce functionality, aiming for AppExchange listings. This is typically priced by Salesforce at 15% of the SaaS app List Price, calculated on a Pricing Model of Per User Per Annum Subscription Fees. So, in practice, you, as the ISVforce Partner, signing a contract directly with the end-customer, who inturn, sign a direct contract for Salesforce licences, with the same Pricing Model.
 
OEM: Partners create packages for both Salesforce and non-Salesforce customers, including embedded licenses. Here you, as the OEM Partner, typically pay 25% of the combination of your SaaS app and the appropriate Salesforce technology (e.g. Salesforce Lightning Platform. This is know as a Percent Net Revenue (PNR) calculation. Example: your end-customer pays £400 per User per Annum in Annual Subscription Fees and you, in turn, pay Salesforce the PNR Fees of 25%, equalting to £100 Per User Per Annum.

The monetising of Salesforce-powered SaaS apps as either an ISVforce or OEM Partner is accomplished via the AppExchange store. Prior to launch, each Salesforce-powered SaaS app must pass a rigrous Security Review, which we help to run smoothly.

The AppExchange Security Review tests the security posture of your solution, including how well it protects customer data. The security review helps you and us identify security vulnerabilities that a hacker, malware, or other threat can exploit.

To distribute managed packages, Salesforce Platform API solutions on AppExchange, they must pass this Security Review. During this process, Salesforce tests your solution with threat-modeling profiles that are based on the most common Web vulnerabilities. The tests attempt to penetrate the defenses programmed in your solution. Their goal is to extract or modify data that they don’t have permission to access, just as security threats attempt to do.

Here’s a small sampling of the common security threats that Salesforce test for:

SOQL and SQL injection.
Cross-site scripting.
Non-secure authentication and access-control protocols.
Vulnerabilities specific to the Salesforce platform, such as record-sharing violations.