Application - AI & Technology Specialist

Technology that creates value starts with understanding the business, not the tools.

I'm Brian Douglass. I have recently sold my business and I am looking for new opportunities to apply my background as a data scientist, technologist and business operator. With years of experience building systems that measurably improve business processes and decisions, I would love to discuss what real technology transformation could look like across your venues.

This cover letter is designed to highlight not just what I know, but how I think - and what that could mean for your business.

Read on Scroll
A personal note

I know your venues and I think what you have built is amazing

I have always enjoyed visiting your venues on Caxton Street (generally before a rugby match!) and I am genuinely impressed with what you have created. The quality of the experience, the attention to detail and the care that clearly goes into how your spaces feel are great. These are obviously the result of a family business that takes real pride in what it does.

That is partly why I am applying. I am not casting a wide net. I am interested in businesses that have built something worth improving and where the right technology, applied thoughtfully and correctly, can improve and extend what already works rather than disrupt it.

Reading the brief

A few observations about how this role has been framed

This role as written is doing something that is easy to miss: it is trying to bundle three quite different skill sets into one position and hoping they will fit with one person.

AI & automation strategy is about mapping business processes, identifying leverage points, evaluating tools, and building systems that actually get used. This requires analytical depth and genuine business context.

IT support and infrastructure is a reactive, operational function - laptops, routers, onboarding. Valuable, but it competes directly for time with strategic work.

Marketing and content production (even AI-assisted) is a creative discipline. Producing social posts, menus, and campaigns day-to-day is a role in itself, and one that sits very differently from building a technology foundation.

I raise this as an honest view from someone who has worn all of these hats in the past. The most valuable thing a technologist like myself could do in a business like yours is map the landscape properly first. We need to understand where staff time is being lost, where decisions are lacking data and where the right tool creates a lasting return. Once that picture is clear the solution becomes much easier to define, and you will know who you actually need and what they should be doing.

I have built and run multiple businesses and helped many more through understanding and improving their processes. I have all the skills your role calls for, but more importantly I understand how to deploy them in a way that generates real, measurable outcomes. Technology does not have to be costly or disruptive when it is set up correctly from the start, and that is where I would add the most value.

Where the value is

Three opportunities worth exploring across your venues

For me, data opportunities are not just words on a page. I have years of hands-on experience building actionable data models that measurably improve business outputs. It is where analytical thinking, not just AI tools, can deliver meaningful returns in a hospitality business like yours. It is about asking the right questions to get the right answers.

To highlight this methodology, I have come up with three problems. Click on each one to see the approach.

The problem
Perishable purchasing could be costing more than you realise
Most venues order on gut feel, prior week usage, or supplier prompts. The result is consistent over-ordering, waste, and margin leakage that rarely shows up clearly on any single invoice.
Using linear programming optimisation against predicted demand - factoring in bookings, day of week, seasonal patterns, and local events - purchasing orders can be generated that minimise waste while maintaining service levels. This is a standard operations research approach applied to food service, and it is measurable from day one. The data you need is almost certainly already sitting in your POS and booking systems.
Linear programming Demand forecasting POS integration
The problem
Your marketing is probably talking to 20% of your audience
Without audience segmentation, every campaign speaks to an average customer who may not exist. Spend concentrates on the already-engaged while lapsed visitors and high-value prospects receive the same message as everyone else.
Machine learning segmentation on your customer data - visit frequency, spend patterns, booking behaviour, tenure - creates distinct audience groups with genuinely different needs and responses. From there, campaigns can be tailored to each segment rather than broadcast to everyone. I have delivered this approach for companies including Vodafone and Woolworths. The lift in engagement and reduction in wasted spend is consistently significant.
ML clustering CRM data Campaign ROI
The problem
Staffing and planning decisions are made with low confidence
Venue operations run on forecasts whether anyone calls them that or not - the manager who decides how many staff to call in is forecasting. The question is whether that forecast is based on intuition or evidence.
Spline-based demand forecasting uses your historical trading data to model smooth, realistic demand curves across time - capturing seasonality, long weekends, school holidays, and irregular events without overfitting to noise. Combined with a simple dashboard, managers get an objective view of expected demand rather than relying on memory or instinct. Roster decisions become defensible, and when you compare actuals to forecast, you learn faster.
Spline forecasting Staffing optimisation Reporting dashboard
How I would approach this

What good technology implementation actually looks like

Good strategic technology implementations do not start with tools, they start with understanding problems. Here is a sequence I would recommend to produce real and lasting outcomes.

Discovery
Understand before building
Audit existing systems, data sources, and workflows across venues. Talk to team leads. Map where time is lost, where decisions lack data, and where technology either helps or creates friction. No tools are deployed in this phase - the output is a prioritised opportunity register with estimated return on investment against each item.
Foundation
Build what matters most
Address the highest-priority items from the discovery phase. This typically means connecting existing data sources, establishing a reporting baseline, and deploying one or two targeted automations with clear tracking built in from day one. Early wins that build confidence and demonstrate return across the team.
Roadmap
Define the full picture
From here there should be a clear technology roadmap, a measurement framework, and a concrete view of what ongoing support looks like - including who you need and what those roles actually involve. You will have data to make that decision rather than guesswork.
Background

Experience Building Things That Work

My background sits at the intersection of business operations, data science and technology - not as separate careers but as a continuous thread of building systems that generate measurable outcomes.

Masters of Data Science (with Excellence)
UNSW
Machine learning, statistical modelling, analytical systems
Managing Director
Entelligence (Consulting)
Analytics for Woolworths Online, Vodafone customer profiling, conversion rate optimisation
Owner / Operator
EMBRI (Mr Stoves)
Built ML-driven customer categorisation and probabilistic pricing from scratch inside a real operating business
Army Officer
Royal Australian Signals Corps
Iraq, East Timor, Commonwealth Games - leading technical teams in complex, high-stakes environments

The thread that runs through all of this is an ability to translate between technical complexity and business reality and to build things that non-technical people can actually use and trust.

Next steps

Let's have a conversation about what you actually need.

I am genuinely interested in the problem you are trying to solve and I would welcome the chance to talk through what that could look like in practice.

Email Brian 0402 083 465