Larry, the AI Digital Analyst for Sales & Supply Chain

Meet Larry, your AI analyst

Does the analysis: collects and prepares your data, predicts what will happen and weighs the trade-offs, every day and at scale.
Recommends and shows why: each recommendation comes with the numbers behind it, at the moment your staff need it.
Learns: self-learning algorithms update automatically as new data and results come in.
Keeps your people in control: Larry recommends; your team makes the call.

Good decisions create value – whether they’re pricing decisions, marketing decisions, resource allocation decisions, or production decisions. Poor decisions, on the other hand, destroy value. The problem with making good decisions – particularly in complex and dynamic environments – is the daunting amount of data analysis that must be undertaken. By the time it’s done – if at all – the opportunity has usually expired. For this reason, business decisions are usually sub-optimal at best. And the greater the operational scale and complexity, the more sub optimal they become. Powered by the latest advances in AI, Larry, the Digital Analyst® automates these complex analytical tasks and workflows, empowering staff across multiple business functions to make better & faster decisions.

What Larry does every day

Larry is built into each Decision Cloud^® module, so the analysis lands where the decision is made. These are the jobs Larry takes on:

Plans promotions. Which promotions to run, when and at what price, with the predicted volume, revenue and margin impact of each, optimised against your trading terms. e.g. “Move this promotion to a different week and use a shallower discount: higher predicted margin for similar volume.” In PCM and TPM & TPO
Prices every quote. A margin-optimised price for each product and customer, in front of sales staff while they quote. e.g. “Quote this customer at this price: it protects margin without pricing above what they usually accept.” In Order Management System (OMS) and dynamic pricing
Tells reps who to call and what to talk about. A prioritised call list and a Next Best Conversation™ for every visit, based on share-of-wallet gaps, churn risk and cross-sell opportunities. e.g. “Visit this customer this week: orders in their core category have dropped off.” In Customer Opportunity Profiler (COP)
Suggests what else to sell. Cross-sell, up-sell and substitute products for each quote, order or online basket. e.g. “Customers who buy this also buy that: add it to the order.” In OMS and the E-commerce Recommendation Engine
Forecasts demand and orders stock. A forecast for each product, and the replenishment orders that follow from it. e.g. “Order more of this line now: demand is forecast to rise ahead of the next promotion.” In Demand Planner and inventory & replenishment optimisation
Builds schedules. Production, maintenance, equipment and labour schedules built around your business rules, and re-optimised as conditions change. e.g. “Run these two jobs back to back on the same line to cut changeover time.” In the Integrated Planning & Scheduling Optimiser
Tests a decision before you make it. Simulates changes to capacity, resources, shifts, schedules, demand and inventory before they happen. e.g. “Adding a second shift meets the extra demand; moving the work to another site would not.” In the What-if Simulator & Optimiser

Examples are illustrative. The recommendations Larry makes depend on each organisation’s data, rules and objectives.

How Larry works

Larry runs the analysis on its own, around the clock. It doesn’t act on its own: every recommendation goes to a person to approve.

Collects and prepares data from your internal systems (sales, orders, promotions, stock) and from external sources.
Predicts what is likely to happen, using models trained on your own data.
Optimises: weighs the trade-offs and searches for the best option within your business rules and constraints.
Recommends the decision, with the numbers behind it, inside the Decision Cloud^® module your team already uses.
Learns by comparing results with its predictions and tuning itself as new data comes in.

Under the hood, Larry combines techniques such as Bayesian networks, artificial neural networks and genetic algorithms, chosen and configured for each problem.

Decision Cloud^®

Modularised software platform

Internal and external data feed Larry, the Digital Analyst®, the AI engine behind every Decision Cloud® module.

AI engineLarry, the Digital Analyst®

Software products

Decision Cloud^® is powered by our AI engine Larry, the Digital Analyst®, named the Australian Innovation of the Year, and optimises decisions across three business functions:

Marketing optimisation

Plan, simulate and optimise promotions and trade spend across the range.

Sales optimisation

Direct sales staff to the best opportunities, with what to offer and what price to quote.

Supply chain optimisation

Forecast demand more accurately and optimise inventory, production and logistics.

AI governance: how Larry stays accountable

AI that recommends commercial decisions has to be trustworthy. This is how Larry is set up:

People decide. Larry recommends; your staff accept, change or reject each recommendation in their normal workflow. Nothing is changed without them.
You can see why. Recommendations come with the numbers behind them, such as the predicted volume, revenue and margin of a promotion, or the reason a customer has been flagged.
Your rules, your objectives. Larry optimises within the business rules, trading terms and constraints configured for your organisation.
Your data stays yours. Decision Cloud^® runs on Amazon Web Services with a separate instance for every customer, and customer data is never shared, re-used or re-sold. Complexica is ISO 27001 certified. Read our information security policy.
Learning is monitored. Models are trained on your own data, tune themselves when performance moves outside an agreed threshold, and are retrained with you when new factors such as channels, products or competitors need to be added.

Questions about how Larry would work with your data and processes? Talk to our team.

Common questions

Can we start with one module?

Yes. Decision Cloud^® is fully modularised, so you can start with the module that solves today’s problem (for example pricing, promotions or demand planning) and add others as you grow. Every module runs on the same AI engine and the same data.

How long does implementation take?

It depends on the scope. Every engagement starts with a no-cost workshop, followed by a fixed-price, fixed-time scoping engagement that defines the deployment milestones, cost estimates and business benefits. Deployments are then staged rather than “big bang”, which reduces risk and brings forward the return on investment. See our frequently asked questions for each stage of the engagement model.

Will my data be reused for the benefit of competitors?

No customer data is ever shared, re-used, or re-sold in any way. Each Complexica customer has their own AWS instance where Larry, the Digital Analyst® is trained and configured using that customer's data plus any relevant external data. Customer data is also covered under the provisions of the Confidentiality Clause of Complexica's standard terms & conditions.

More: How does Larry "learn"? and other questions in our FAQ.