Finding the Path: how to improve workflows

First published as a white paper “How the Hidden Costs of Inefficient Workflows Drain SME Profits — and How to Fix Them” on the 2nd of November 2025 “Finding the Path” is the third chapter, following on from “The Obstacles”

Our businesses experience organic growth, and this sometimes results in things spreading a bit too far and wide, making it difficult to see the path in front of us — here are a few suggestions to keep you on the straight and narrow…

Be strategic

Taking a strategic approach transforms workflow management from reactive to proactive:

  • Are you making the most out of the software and services you use? Streamlining could reduce costs and technical overhead. Saas sprawl is a genuine governance risk with legal implications.
  • Investigate workflow automations services (such as Zapier, Workato, Microsoft Power
  • Automate, and IFTTT) to connect essential cloud services and eliminate repetitive tasks.
  • When using AI: write comprehensive and precise prompts; be specific about the task(s); and provide constant supervision (I’ll be discussing AI in the chapter: “Case Studies”).

Strategic thinking is about aligning technologies with purpose, ensuring that each process (and, by extension, cloud service) makes a positive contribution.

Be organised

Organisation transforms insight into action. Good processes become sustainable when software, data, and people experience consistent and careful management:

  • Audit existing software and attend to unused resources (those belonging to users who have moved on) to reduce costs, or to reallocate.
  • Maintain a calendar of subscription renewals (be mindful of punitive cancellation fees).
  • Does the software support tags? If so, create logical groups of resources, to make them easier to retrieve.
  • Gmail and similar services allow aliases: [email protected] becomes: [email protected] (most email services allow this but need manual configuration), a simple change that improves filtering and tracking.
  • Only share the data that’s required (of a task, on a cloud service et cetera) and nothing else.
  • Once data has been downloaded and used, delete it from that device.
  • Get into the habit of tracking changes in Microsoft Office and Google Docs.
  • Keep a journal — knowing that a crucial decision has been made is valuable , but so is understanding when and for what reason.

Organisation is the bridge between strategy and execution — reducing cognitive load, preventing repetition, giving structure to each subsequent improvement.

Be critical

A critical assessment keeps workflows lean, performant, and relevant. In time, each process accumulates habits and redundancies — questioning them is essential to progress:

  • Could a task be done in 3 steps instead of 5, or 3 minutes instead of 5?
  • How many people need to sign off a decision? Not having everyone available to make an important decision creates drag.
  • Minimise the lines of communication to avoid fragmentation, then document and enforce it.
  • Seek out instances of “Task X” (inefficient routines) and fix them.
  • Remember that bad habits are simple to make but difficult to break.

A culture of constructive scrutiny fosters improvements that, in time, become routine. Each refinement compounds the efficiencies gained from the last.

Be inclusive

Inclusion transforms process management from a technical task into shared responsibilities across the team:

  • Your team’s valuable experience is the difference between understanding how something is done and knowing how it should be done.
  • Reward ideas that improve workflows — a sense of stakeholdership encourages innovation and participation.
  • If supporting employees with disabilities, make sure the software supports assistive technologies (voice-to-text, screen readers, and so on).

Understanding that individual contributions often translate into organisational momentum is vital. When teams understand and shape the workflow, consistency and quality follow.

Be vigilant

No workflow is immune to disruption. Vigilance safeguards both continuity and trust — especially when data and operations depend on multiple cloud services:

  • What’s the worst thing that could go wrong? Now plan for it — this could involve the loss of critical data.
  • Ensure the data policies of cloud services align with the laws of the land.
  • Use password managers (1Password and LastPass) to safeguard important credentials, and enable multi-factor authentication where possible.
  • When using AI, do not share anything that’s considered confidential, such as: Personally Identifiable Information (PII); anything that could cause economic damage, reputational harm, or legal issues.
  • You have a WordPress website? If so, keep it and its plugins up to date! In general, this advice is applicable to alternative content management systems (CMS).
  • Keep all devices (computers, laptops, tablets, and mobile) up to date.
  • Use biometric security features when available.
  • Consider cybersecurity training — “phishing” scams and “ransomeware” attacks are on the rise.
  • Do you own and control the data? Often, what’s know as derivative data (some type of product created from the original data, such as an infographic) is owned by the vendor, while some make it difficult to export the data.

Vigilance sustains everything else. Without it, strategy, organisation, and inclusion risk becoming undermined by avoidable vulnerabilities. Taken together, these principles ensure that workflows remain both efficient and resilient.

Data governance

We return to data governance because it’s a major issue with serious implications, but there are routes forward to reduce risk. Before signing an agreement with a cloud service:

  • Demand a Data Processing Agreement (DPA) — DPAs name sub-processors, specifies data residency, and defines deletion timelines, going beyond privacy policies.
  • Ask where your data is stored — region, specific cloud provider and region, whether it’s multi-tenant or isolated.
  • Read the AI / ML training clauses — many Saas vendors now include provisions to use your data to train their models. Opt-out provisions, if available, are often buried.
  • Check sub-processor lists — your data governance is only as strong as the weakest vendor in their chain.

During the period of the agreement:

  • Maintain an inventory of Saas data — know what data category lives in each product (PII, financial, IP, credentials). Most businesses have no idea what’s in their Saas estate.
  • Keep data to a minimum — don’t put data into a Saas product because you can. Only put in what the product needs to function.
  • Do regular access audits — stale accounts and over-provisioned roles accumulate fast in Saas.
  • Test deletion — if your DPA says data is deleted within 30 days of termination, test that claim on a non-critical account before you need to rely on it.

Design communication

Design communication is what happens when we use visuals and written words to communicate messages (should they data or information), and examples would include things like logos, adverts, instructive animations, and also user interfaces.

An example of strong design communication would be a good infographic that condenses complex ideas into often colourful graphics that make complex ideas simple to understand.

In recent times, a lot of effort has been poured into user interface design to create common components and concepts (input fields, radio buttons, check boxes and so on), that have been adopted by the various software vendors, to make their products as usable as possible.

When using cloud software, be mindful of the following:

  • Is it compliant with accessibility guidelines? For example: the ability to change the size of the text; and to choose a typeface appropriate to someone with dyslexia (there are also people with specific hearing and cognitive requirements). When accessibility compliance isn’t a legal requirement, software that follows recognised standards (such as WCAG 2.1 or EN 301 549) tends to be clearer, easier to learn, and better suited to a diverse workforce. EN 301 549 is the European accessibility standard derived from WCAG.
  • Does it provide configurable dashboards that reduce clutter and present at-a-glance information aligned with each user’s priorities?
  • Are the support resources and error messages helpful? When stuck or something goes wrong, having an unambiguous path to a resolution is the difference between a single minute lost and several hours wasted.


The Obstacles: workflow problems faced by the SME

First published as a white paper “How the Hidden Costs of Inefficient Workflows Drain SME Profits — and How to Fix Them” on the 2nd of November 2025 “The Obstacles” is the second chapter, following on from “Fixing the Hidden Costs of Inefficient Workflows”

As the landscape continues to shift we have to adapt and navigate what was once familiar to find a path most optimal to our businesses.

The SME workflow problem

SMEs are underserved compared to large enterprises in terms of workflow design and optimisation. Generic software forces SMEs to adapt their workflows to the tool, as opposed to the tool fitting the hand that wields it.

Common issues:

  • Having to add the same data across multiple systems.
  • Subscription creep from multiple tools with overlapping features and concerns.
  • Maintaining old systems that are expensive and slow.
  • Cognitive overhead from learning to use multiple systems.
  • Lack of integration and incompatibilities between disparate systems.
  • Unforeseen GDPR implications introduce compliance risks.
  • Processes still reliant on paper, spreadsheets, and email.
  • Complex oversight — knowing what’s been changed by whom, where, when, for what reason and so on.

Communication fragmentation:

  • Using multiple tools for different types of communication (email, Slack, Teams, project tools like Jira or Trello).
  • Important decisions often become scattered across different channels.
  • Managers are forced to reconstruct the reasoning behind decisions, slowing projects, and creating risk.

SME productivity lags behind larger businesses. According to the British Business Bank (2023), UK SMEs contribute around 50% of GDP but suffer from a productivity gap compared to large enterprises, with output per hour up to 20–30% lower.

SMEs often lack the resources to make the most effective and efficient use of their time. When jobs overlap, priorities become blurred, everything becomes urgent, and it’s less like work than it is becoming lost in a hedge maze of our own making.

The Hidden Costs of “Task X” And How Little Inefficiencies Grow Big

Think of “Task X” as the real task, once we acknowledge the inefficiencies that come with it, slowing people down and draining their focus. In practice, these inefficiencies tend to look like:

  • switching between multiple platforms to complete a single task;
  • re-entering the same information in different systems;
  • using outdated or incomplete information because sources aren’t synchronised;
  • chasing updates or approvals across email threads and chat messages;
  • sifting through printed materials instead of using a searchable digital data store;
  • relying on slow, imprecise search functions;
  • hunting for the correct credentials to sign into an important service;
  • transferring data between incompatible systems, by hand;
  • repeating routine steps because automation isn’t available;
  • searching for the latest version of a document or file;
  • waiting for software or files to open, build, load, or download…

We often accept these as features of the terrain, but it’s best to think of them as obstacles — things to be avoided, circumvented, and sometimes removed. Here are two simplified common examples…

At the team level:

5-minute task done 3 times a week by 5 staff membersthat’s 75 minutes a week
At £70 / hour, that’s £350 / month~£4,200 / year
If streamlined to 3 minutesthe saving is ~£1,680 / year

At the executive level:

A director spends 30 minutes / week compiling a report from different sources in different formats
At £120 / hour, that’s £240 / month~£2,880 / year
If streamlined to 25 minutesthe saving is ~£1,440 / year

The major costs come in the delays to decision-making, the disruption to strategies, and the ripple effects across the team.

Of course, these numbers are educated guesstimates based on past experiences, but imagine 5–10 recurring instances of Task X across 5-10 employees, project managers, and directors, resulting in tens of thousands of pounds drained on an annual basis.

All hours shouldn’t be billable, because some time must be spent attending to organisational activities…

A simplified example of non-billable but essential organisational time:

• A project manager spends 120 minutes per week creating and managing tasks across Kanban boards and Gantt charts.

• At £70 / hour, that’s £560 / month — time that might look unproductive on paper, but is a vital investment in the business.

Imagine the consequences of not allowing sufficient time to perform these essential tasks: missed deadlines; duplicated effort; and expensive rework.

If the task is to create a square and we begin by cutting corners, it’s almost inevitable that we end up with a production line manufacturing circles.


Fixing the Hidden Costs of Inefficient Workflows

First published as a white paper “How the Hidden Costs of Inefficient Workflows Drain SME Profits — and How to Fix Them” on the 2nd of November 2025 I’ll be serialising it here, on the Octane website.

Executive Summary

Britain’s small and medium-sized enterprises (SMEs) are the backbone of the economy, weighing in at 99.9% of all businesses. Yet they face persistent productivity challenges.

All too often SMEs are dependent on a patchwork of off-the-shelf tools (Microsoft 365, Google Workspace, CRMs, accounting software, et cetera), combined with written and printed collateral, to create fragile composite workflows, prone to becoming the cause of inefficiencies and wasted time. Workflows are essential and should not be the cause of uncertainties.

Small inefficiencies (“Task X” is discussed in the chapter: “The Obstacles”) are difficult to find and fix, add up to thousands of pounds per year in lost productivity, and risk data error, duplication, and loss. Drawing on evidence from UK government reports and SME studies, it shows that modest improvements to a workflow yield measurable productivity gains.

In this white paper we examine the often hidden inefficiencies, how and where they emerge, and provide actionable steps to mitigate against some of them. It also contrasts the limitations of generic, off-the-shelf tools with the benefits of a custom-built workflow designed to fit existing processes, that — in time — reduces costs while lowering risk.

The Landscape

First, a sobering fact:

SMBs lose 24 working days a year to financial admin:

“New Sage research shows SMBs lose 24 days a year to financial admin, the equivalent of working 13 months but getting paid for just 12. Time drains include invoicing, chasing payments and correcting errors.” — 13 months of work, 12 months of pay: the hidden admin burden on small businesses, via Sage.

24 days isn’t too far from the average annual leave (28 days).

But, there’s hope:

If 30% of SMEs reclaimed but one admin hour per week, it could add £6.6 billion to the UK economy:

“If these 30% of businesses could reclaim just one hour per week spent on admin, it could be worth £6.6bn to the UK economy annually.” — An extra hour of SMB productivity a week worth £7bn to UK economy, via Sage.

As owners of businesses, we’re still paying wages and tax on that time, be it lost or not.

Octane is a strong advocate of digital transformation:

Adopting digital tools like CRM, e-commerce, et cetera helps reduce the administrative burden:

“The SME Digital Adoption Taskforce report highlights that SMEs adopting basic productivity-enhancing digital technologies (CRM, cloud, etc.) can reduce administrative burdens and improve competitiveness.” — SME Digital Adoption Taskforce: final report, via Gov.uk

… but adding CRM here and a CMS there creates the additional burden of having to manage disparate services owned by different vendors each with their own policies regarding data that belongs to you.

What is a workflow?

A workflow is an agreed or established sequence of tasks designed to produce a specific result: a defined sequence of tasks that combine to produce a specific result. What we create, be it physical or digital, flows through a series of processes (containing one or several tasks). When these processes are optimal, the flow is linear, like time.

When these processes aren’t optimal, our creations become stuck, lost, broken, and sometimes go backwards. Understanding the reasons these processes are failing is a crucial step towards fixing them, but then there’s the question of time and talent, both of which are needed when attending to such things.

Often, the fix is to subscribe to a cloud service to mitigate against some portion of an errant process, accelerating those processes while also reducing overhead, but in doing so we forfeit a degree of control at the expense of convenience, incurring cost creep each time we do so.

In isolation, these cloud services are a boon to our businesses, but the challenge we face is combining them into something cohesive — almost like workflows within a workflow (the chapter: “Finding the Path” examines these challenges and how best to address them).

We must take enormous care with our data — where it flows, and who owns it once it settles in the cloud.

Cloud everything…

We’ve seen a dramatic shift in the software landscape, where we’ve gone from owning to licensing:

“In 2023, artificial intelligence (AI) was adopted by 9% of firms while cloud-based computing systems and applications were adopted by 69% of firms in the UK.” — Management practices and the adoption of technology and artificial intelligence in UK firms: 2023

While there are obvious benefits (pay-as-you-go subscription models, a reduction in on-premise infrastructure, improved collaboration and so on), we’re still using the same services most often from inside a web browser.

Before proceeding, let’s sort out some of the nomenclature. Saas is an acronym of Software as a Service. Cloud is the infrastructure, and SaaS is the software that lives on that infrastructure.

Artificial Intelligence

In the two years since those statistics were released, artificial intelligence has become a disruptive force — vilified and venerated in equal measure.

Much has been written about how AI has the potential to replace hundreds of thousands of people while washing away entire business sectors. In contrast, there are those who argue AI has the potential to introduce opportunities, to create new business models, and invent entire markets that would otherwise be impossible without it.

AI isn’t without its flaws (“hallucinations” as they’ve become known, which result in factual inaccuracies, and sometimes complete fictions), so it’s up to us to take care in how, when, and also where we use it.

But this shift speaks nothing to the foundational problems faced by the average small to medium-sized enterprise — while large enterprises are already throwing hundreds of millions of pounds at AI implementations, the SME instead has to be nimble, selective, and innovative.

Data governance

When thinking about what artificial intelligence is, as a thing, we tend to forget (or perhaps not understand that) we are its data model, and what we share today becomes its training data tomorrow.

We’re now seeing AI used on smartphones at home and in the workplace, blurring the divisions between the two. A common practice is to share a spreadsheet with an AI and ask questions about it, but what if that data is confidential, or contains Personally Identifiable Information (PII)?

From the perspective of data protection, these actions could constitute:

  • A transfer of personal data to a third-party data processor.
  • A potential cross-border data transfer (most AI providers are US-based).
  • A possible breach of confidentiality obligations to clients or staff.
  • In regulated sectors, a potential regulatory breach on its own.

Cloud software (using AI or not) comes with its own set of issues when it comes to data governance, often opaque at best, which isn’t reassuring.

In general, only share with a cloud product what is needed to accomplish the task at hand, and nothing else, and extend that thinking to AI, also (I’ll be expanding on these challenges in the chapter: “Finding the Path”).


Industrial Revolution 2.0

The wheels of change are relentless, and — in the end — the successful are those behind the wheels driving them forward while everyone else is in front of them, adapting to their path.

As AI wipes jobs, Google CEO Sundar Pichai says it’s up to everyday people to adapt accordingly: ‘We will have to work through societal disruption’

I assume everyone is up to date with their understanding of what happened during the Industrial Revolution? I ask because that’s something we tend to celebrate, in spite of the enormous social and economic upheaval.

Without turning this into a historical excursion, the Industrial Revolution swept aside the cottage industries of cotton weavers, forcing most of them into cities to work on the machines that had replaced their labours. Then the disruption turned to agriculture.

You get the idea.

Is there a modern parallel? Yes, sort of, but it’s already happened, in that everything we’ve accomplished has been transformed into training data undergirding these artificial intelligences.


We’re the cotton weavers and the farmers in front of the colossal wheels of change, careful to avoid their vast shadows, awaiting their next turn.


How do we respond to this? No doubt, as predicted, some types of businesses won’t survive this cycle of change. Everyone else, much like those Octane has had as a client since 1999 stand a chance because — and this is the ironic part — while their uniqueness has given them a competitive advantage it was also the same thing that made it difficult to build a sustainable workflow.

Allow me to rephrase: It’s the human component of their businesses that could insulate them from the disruptive nature of this emerging AI revolution.

What I’ve learned from using AI here at Octane are these 3 simple rules:

  • precision prompts;
  • specificity of task(s);
  • constant supervision.

Yes, the human component is what makes AI do amazing things.

I accept this could change, because that’s the nature of a revolution, and it’s up to us to be among those harnessing these wheels of change, but to also be mindful of those in front of them, and to not run them down in pursuit of progress and success.

Octane builds precision workflows for small and medium-sized enterprises (SMEs), who are the
backbone of the economy, weighing in at 99.9% of all businesses.

Download our White Paper to learn more about the hidden costs of inefficient workflows and
how to fix them.


We are AI

Some have predicted that the amount of AI-generated data and information is due to outnumber human-generated by up to 90% some time in 2026.

What about the cost of creation? $0.10 versus $10

When thinking about what AI-generated is, as a thing, we tend to forget (or perhaps not understand that) we humans are the data model, so the onus is on us.

At the moment, most AI agents don’t have access to up-to-the-minute data, but that’s bound to change (think of that as a tomorrow problem).

While these agents are more than capable of articulating statistics (hallucinations aside) that include us and what we’ve accomplished as some sort of homogenised average, they know nothing of the specifics that make us who we are: what we think; and how we think.

So, in time, I imagine that 10% would be where the valuable uniqueness is to be found, because it’d be the exact same place our inimitable human qualities would be found.