Changing the landscape of Route Optimisation

Introduction

Getting from point A to point B is a simple enough task to be completed on most devices, through various different apps and software. But what happens when you have to get from point A to point B and now point C with consideration of other factors like availability windows and route preference? Scopta have developed Run and Route a route optimisation software that deals with the complexities of vehicle and delivery routing.

Read on to discover Run and Route and how it is changing route optimisation and vehicle routing.

Scenario

Barry is the Operations Manager at a warehouse depot for a biscuit company and is in charge of the planning and organising of the distribution of goods sold across Sydney. Barry is tasked with delivering 400 orders to be delivered between 20 trucks, exactly 20 orders per truck. For the last 10 years Barry has used a combination of Excel and Google Maps to figure out their delivery routes. He plans his delivery schedule a week in advance, and spends a large portion of the week carefully mapping out delivery routes. Barry is restricted by both time and cost, trying to figure out the fastest and most efficient route.

Planning out a delivery schedule by hand is notoriously difficult and time consuming, not to mention subject to human error. Manually working between Excel and Google Maps to find the best delivery order is inefficient and also raises challenges such as the Travelling Salesman Problem or TSP, which is simply finding the best order in which to visit a set of locations. Through traditional methods of Excel and Google Maps it won’t tell you the best way to order those stops to give you the overall shortest or fastest route but instead show you the quickest route from point A to point B. Now say you throw in point C and point D? An extra level of complexity is added with additional locations. How is Barry to know which location to begin with and the order to complete the rest of his deliveries?

With Run and Route, Barry will have a centralised solution that will allow him to input information about his locations and trucks, and automatically configure the fastest and most cost effective delivery routing schedule. Traditionally, Barry might have begun his route at point A, followed by point B, C and D in that order. By inputting this data in Run and Route, Run and Route will determine the optimal delivery schedule that would show that this particular truck should begin his delivery route at point C, then point A, then point D and finishing at point B. 

Another challenge Barry and other Operations Managers face is creating a schedule that considers delivery time windows and customer availability. Factoring customer availability and time windows is a crucial and important aspect of determining the optimal routes for a fleet of delivery vehicles. For example one shop in Bondi has a strict 2 hour delivery window between 5:00am and 7:00 am, while another customer in Redfern is a bit more flexible and is open for deliveries from 6:00 am to 12:00 am. Manually working through these intricacies one truck at a time not only requires an incredible amount of thought and time, the level of complexity dramatically increases with scale

run and route

Solution

Run and Route is Scopta’s Vehicle Routing offering, designed to simplify the planning process for last-mile delivery. It is useful for businesses with multiple vehicles that each perform multiple deliveries per day. Run and Route can help your business cut variable costs and improve your customer service. Remain efficient and competitive with a quality Vehicle Routing Solver that simplifies the role of your Operations Manager and the way you plan and schedule your deliveries. Be confident and assured with the quality and accuracy of your schedules with Run and Routes powerful engine.

Want to know more? Speak to a team member today and find out how Scopta Run and Route can automate your vehicle routing.

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3 ways Biarri Workforce can improve rostering and workforce planning

The team behind Biarri Workforce are dedicated to helping your business get the most out of our rostering software. Whether it is simplifying the job of your workforce planners or creating a team friendly roster that increases your employees satisfaction and retention, Biarri Workforce is the solution to improve your workforce planning and rostering. Biarri Workforce is tried and tested across many industries including maintenance teams, healthcare and aviation.

Read on to learn about the 3 ways Biarri Workforce improved rostering and workforce planning for the team at CQFMS and how Biarri Workforce can help your Workforce Planners and your Business. 


Reahan McBain – FMS Group

1. Biarri Workforce Software

We’ve all heard it before: 

“It is not the tools we use that make us good, but rather how we employ them”. 

This saying doesn’t always hold true, sometimes simply not having the correct tool for the correct job restricts our ability to perform; so why not start with the right tools for the right job? 

Like so many other businesses, CQFMS managed their workforce and planned their rosters using ever increasingly complex Excel spreadsheets. While Excel is a capable tool, rostering a growing team of people over a 24/7 period all while adhering to EBA and fatigue regulations can quickly become a nightmare of complexity. Through system driven automation and the powerful Biarri Workforce roster optimisation engine, the team at CQFMS were able to significantly reduce roster preparation time, more easily ensure compliance with EBA and fatigue requirements and manage changes to their rosters more effectively

2. Onboarding New and Existing Employees

When managing a large fleet of workers, onboarding and assigning new employees to a roster can become a time consuming task. This was the case with CQFMS, with a growing workforce. Previously, onboarding was completed using another HR software system and new employee lists were manually transferred through to Excel to begin planning the roster. This was inefficient and not scalable so CQFMS requested a more streamlined approach to onboarding. Through Biarri Workforce, Workforce Planners are now able to onboard employees much easier, as well as manage their roster in the same system. Found in the Biarri Workforce ‘Employees’ tab, you are able to onboard new employees and upload documents such as certificates and other qualifications all in one simple and easy to use interface. 

3. Creating a safe roster 

CQFMS and Biarri value safety and understand that an implied safety culture goes beyond the job site and includes appropriate roster creation. It is critical when planning a roster to have the correctly trained and skilled people for the job and to ensure that employees have current certification suitable to be rostered to work on a site. Biarri Workforce has in-built validation rules which enforce training and skills compliance to enable workforce planners to plan and roster the correct workers to be deployed on site. Another crucial aspect of roster creation that Biarri Workforce automated for CQFMS was the time consuming process of checking and managing employee fatigue. Ensuring the safety of employees meant making a roster that was compliant with EBA regulations including workplace fatigue rules.  Previously, it was difficult and time consuming for CQFMS to manually update and track overtime and employee hours for a large workforce. The Biarri Workforce rules engine and validation function will not generate a roster which breaks fatigue rules and when manual changes are made to the roster the rostering team is automatically notified if the planned roster breaches any fatigue rules. Rosters cannot be published without the Workforce Planner acknowledging and/or fixing these issues.

The right tool

CQFMS is one of many valued Biarri Workforce users. By stepping away from Excel spreadsheets and adopting Biarri Workforce, CQFMS have made noticeable improvements in how they plan and manage their rosters. Reducing time and effort to generate rosters while also automating the important task of skills and fatigue compliance.

If you would like to know more about how Biarri Workforce can improve your rostering and workforce planning or have any other further questions, feel free to leave your details below and a team member will get in touch with you. 

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Sales forecasting tool

Sales Forecasting Tool to Plan Accurately With Some Simple AI

Throughout my career I’ve worked with salespeople, as a salesman, and in roles supporting sales activities. Sales is one of the most important functions of a business as without sales, you have no business, no matter how great your product or service is. 

Sales is the fuel for any business to survive and thrive and this makes planning and forecasting sales one of the most important activities a business does.

That’s why running a business without effective and accurate sales forecasting is a bit like flying a plane without a fuel gauge. Of course, an accurate fuel gauge is not necessary or sufficient for generating or maintaining lift – the Wright brothers got away without one. But there’s a reason why modern planes have them – it gives pilots access to data to make the flight decisions to get from A to B. 

So how are you flying your venture?

Probably the same as most other businesses. 

You gather your sales team and ask them, ”how many sales will we have this year?” 

In the best case scenario, they review last year’s sales and make a guess based on gut feeling and intuition (which is not always wrong). 

Commonly enough though, a misalignment of incentives and company sales culture can manifest as a mismatch between targets (optimised for remuneration incentives) and forecasts (optimised for accuracy).

We can do better. 

And to do this we need to use data. But why is data so important?

According to the Professor of Digital Practice at QUT, Mal Thatcher, the 21st century will be the century where,

“By the middle of the century the only tangible asset on an organisation’s balance sheet will be data”

and this is true for your sales too.

To give you and your business a competitive advantage, we at Biarri have developed a simple, easy-to-use Excel sales forecasting tool for you. So it is time to become data driven now and with Biarri’s new tool this is extremely easy. 

Biarri has taken some basic AI techniques and put them into a spreadsheet that requires no macros, no plugins and nothing to install. The AI techniques in this Excel tool will help guide your sales team to make more accurate predictions for the coming year. 

You don’t need to be an expert in AI to leverage the tool. It does all of the hard work for you and provides you with data driven monthly predictions for the coming year based on quarterly sales patterns. You don’t need to know cutting edge AI to use the tool, just how to copy and base a small amount of data.

You can download the tool below for free. There is no need to leave your email address or anything. Biarri’s mission is to make the world more efficient via better decisions powered with mathematics and we believe this tool has the potential to make a difference for your organisation.

Your New Sales Forecasting Tool

Before you download the tool, it is worthwhile telling you what it is, and how to use it.

It uses historic data to establish a pattern and then extrapolates this pattern to be able to predict the coming year’s sales. 

Not only does the tool provide monthly predictions, it also takes into account quarterly sales cycles. Forecasting quarter-by-quarter aligns it with typical quarterly reporting and also captures the variance in quarterly sales. This quarter-by-quarter approach is designed for industries like retail which have some quarters with greater sales (e.g. Xmas). 

There is also a “bad month flag”. This allows users to indicate if something bad has happened in the past during months (e.g. COVID) and if similar events are predicted to occur in the future (in the PREDICTIONS tab). 

This spreadsheet comes prefilled with data to show you what it should look like. To use it for yourself, remove the data from the Monthly Sales column in the Data tab and replace it with your own data. The calculations and updates will be carried out automatically. All other cells are locked for your safety. 

How do I use the sales forecasting tool?

The steps to using the sales forecasting tool are as follows:

1. Collect exactly 36 months of contiguous sales data leading up to the month you would like to predict from. E.g. if you want to predict the yearly sales from January 2022 until December 2022, then collect the 36 months of sales data from January 2019 until December 2021. The model is set up for exactly 36 months of data, not more or less.

2. Copy this sales data into the Monthly Sales column in the Data tab (in green). The top most entry should be the oldest (e.g. in the example in 1., January 2019) and the bottom most entry should be the newest (e.g. December 2021 in the example in 1.).

Sales forecasting tool monthly sales column

3. In the Data tab now enter the first month for the monthly sales data in the month tab by choosing from the drop down menu (this cell is green). Also choose the year in the year column from the drop down menu (this cell is also in green).

Sales forecasting tool month selection

4. For each month, choose whether a bad event occurred (or not) by selecting Yes or No in the Bad Event column. If normal trading and fluctuations were occuring, then put No. Otherwise, if something truly unusual (e.g. COVID) occurred that significantly impacted your sales volumes, select Yes on the months which were affected by this (this column is coloured green).

Sales forecasting tool bad event input column

5. Once this data has been entered, go to the Model Analysis tab to see the outputs of the model. In the Predictions tab, if you predict that there will be any bad months in the future, select Yes in the corresponding months in the Bad Event column (which is in green). For this to have effect, similar Bad Events need to have occurred in the past otherwise this will have no effect.

Bad event output column

6. Finally, your predictions are shown in a graph in the Dashboard tab, with a table showing the cumulative results for each quarter.

Monthly sales prediction graph

Download the sales forecasting tool by clicking on the button below.

What does Biarri do?

Most companies begin with Excel sheets like the one provided here to start making once off decisions on key parts of their business. It is like the first flight of a plane with an often inaccurate fuel gauge caused by data issues. At some point, organisations need to lift up from Excel to correct, secure, easy to use and more powerful tools and this is where Biarri helps.

Biarri’s main value proposition is to help clients realise operational excellence in the way they run their business via AI. The core of this is excellent, data driven decision making. Biarri catalyses AI driven business decisions by using its cloud based set of mathematical tools, the Workbench.

To discuss how you can leverage your data and turn it into value to reach new operational heights, reach out with the form below now.

Get in touch

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Markdown optimisation example

The Optimal, Best Markdown Rules During COVID-19 and Beyond

When my friends talk to me about managing a retail store they all enjoy it apart from one thing. They tell me that seeing the latest trends, working with cool brands and meeting some of the stars promoting the articles is great. It’s just that there is a recurring event that makes long days longer and they are sure can be done better – markdowns.

My friends imagine that a set of retail analysts spend days figuring out the optimal markdown to make sure customers buy the remaining goods at the highest possible price to maximise the possible gross profit. 

However, in many cases, there is no group of analysts.

Instead there is a fixed set of well-worn rules, year after year: first a 10% reduction, then a 30% reduction, and finally a 60% reduction until the product clears.

It’s artificial ignorance not artificial intelligence. The retailers have the data, it’s whether they use it – and can make use of it – or not.

As if typical markdown cycles weren’t difficult enough, COVID-19 has turned these processes into a nightmare. Companies are now stuck in a vice trying to clear stock but doing so in a way that loses minimal money and keeps the company afloat. 

The old rules are no longer working so companies are experimenting with new permanent discounts – 50%, 70% and 90%! Just whatever it takes to get the stock out the door before it’s too late…

What is needed, now more than ever, is a data driven, machine learning approach to suit each individual business. The best markdown rules use analytics.

Biarri’s research has shown that too many goods are too heavily marked down, even in a time of crisis like this, meaning lost profit margins. In addition, a one-size-fits-all approach doesn’t work – each business needs to take its own unique conditions into account for such markdowns to be successful.

The early conclusion? The best markdown rules

In the current situation, you need an advanced analytics tool (AI, Machine Learning, Optimisation) that takes into account the unique circumstances of your business and can answer questions such as:

  1. Each store has different stock coverage for an article, so how do we balance a single store’s need with a regional markdown strategy that mandates one markdown for all stores in a region? Or even more difficult, a national markdown strategy?
  2. If we allow markdowns to vary between stores, then how do we create a markdown strategy that prevents customers shopping between your different stores searching for the biggest discount?
  3. How do we accurately model price elasticity for goods with only a few sales each month and even fewer historic price points?
  4. When marking down, how do we pick a smart price point – an “anchor” – that increases demand much more than the surrounding price possibilities? 
  5. How do we accurately predict the demand for each individual article to know what its markdown sticker should show to maximise profit?

As well as much more.

A tool that maximises your gross profit needs to get all the above right for you and your business, not for a generic retailer in a generic retail environment – these disappeared a long time ago.

The way you resolve these challenges is by having an analytics tool which can:

  1. Group stores together using geographic and sales profiles to provide simplified markdown strategies which staff are prepared to implement.
  2. Provide a set of optimal markdowns, determined from the historic sales data, which can be applied equally across all stores in a similar area.
  3. Compute accurate price elasticities. Price elasticity is often like sausages; everyone likes them, but it’s better not to see them being made. Biarri avoids elasticity problems by bootstrapping data to measure how volatile the elasticity estimates are and then weights them accordingly.
  4. Cleverly choose price points based on known rules of customer pricing behaviour instead of just basing it on the markdown percentage times the price.
  5. Predict accurately the demand for an article at a given price point by not predicting a number at all – we predict a range.

The last point is key as merely having a “point” forecast is of little value, you need ranges of values so that you can meet your business needs to ensure that you will either:

  • Sell all stock with a high certainty at a good price, or
  • Ensure the shelves are never empty and you don’t leave customers with a bad impression.
Best Markdown rules forecasts

How do I use it?

So now that we’ve identified the key criteria to create the optimal set of markdowns to maximise profit but also clear out the goods, the final step of a successful markdown strategy tailored to your business is building trust in it. This means rolling out the new AI created marks in a smart way. If you roll it out across your entire range and there are any issues, the entire project will be doomed to fail – even if it was immensely successful on some articles.

The way to make this succeed is to do some simple tests in a scientifically correct way. Create a control group where you do what you normally do and test it against a treatment group with the new optimal markdowns. This can be done either on a store by store basis (A/B tests), but if that is not possible then it should be done across similar product categories so we can draw valid conclusions from the experiment to find the best markdown rules.

What are the benefits?

If instead of using intuition and “What we always did” to markdown products, you turn to analytics to do this smarter, the gross profit improvements can be significant. This technique has been the success story of a number of giants such as Walmart and Target Corporation in their retail divisions. Not only has Biarri seen significant benefits from using optimal markdowns, studies have also concluded that it is possible to improve profits by up to 20% by using analytics instead of gut feelings.

COVID-19 is affecting everyone, irrespective of industry, however the retail industry is one of the worst hit. People are scared and not visiting stores leading to a drop in foot traffic of up to 50% and supply chains malfunctioning with over half of retailers impacted by supply chain issues having too much of some stock (sporting jerseys) and not enough of another (running gear). 

So something smart needs to be done – and right now. Analytics based markdowns are exactly what are needed to turn the retail industry around. Off the shelf tools don’t cut it for a situation like this as they are not customised to cope with so-called “out of sample” events like the current coronavirus crisis.

So reach out now to find out how you can clear out unwanted stocks effectively and maximise profit at the same time. Biarri’s tools are simple to use, customised to each customer and driven by accurate and correct mathematics to ensure the best result. They provide you with the best markdown rules every time.

Better yet, to simplify things, Biarri is offering its markdown tools as a managed service, so no IT work for you to do! We’ll do the analysis and provide you with the best possible markdowns.

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Agribusiness Optimisation Solutions

Maths and Machine Learning for Agribusinesses

Mathematics powered by computers is changing the world we live in. At Biarri we see this everywhere, across every industry, and I’m sure you do too. Recently we have delivered a number of Machine Learning and Mathematical Optimisation solutions for Agriculture businesses in Australia and were fortunate enough to be invited to speak at the recent Case IH agri-business conference in Mackay.

Ash Nelson, Biarri’s co-founder, presented on Maths and Predictive Analytics for better business decisions. He described how our everyday lives are being changed by corporations leveraging large data sets, advanced statistical analysis and powerful computing resources. Ash then outlined how these same set of technologies can be utilised to improve business decisions in agriculture. This includes optimising agricultural supply chains and port operations, reducing unplanned equipment failures by using intelligent predictive maintenance algorithms or to improve health and safety outcomes for farm workers by better identifying areas of best practice to inform injury prevention initiatives.

Are you interested in leveraging your data using advanced maths to make better business decisions? Don’t hesitate to get in touch with our friendly team.

Healthcare Solutions Thumbnail

The Biarri Score: Predictive Analytics for better integrated healthcare

Many Health and Hospital services around the world have introduced integrated care activities to coordinate Primary (Community and GPs) and Secondary (Hospitals) care levels in order to increase the effectiveness of care being provided at all levels. 

Biarri delivered a predictive data analytics solution which successfully identified hospital patients in the community who were most likely to readmit to hospitals. Statistical analysis proved the Biarri Solution is able to identify the top 1% of the population at risk of hospitalisation with 90% accuracy.

In January 2018, Ron Calvert, the CEO of Gold Coast Health and Hospital Services (GCHHS) was in the news recognising Biarri’s predictive analytics in the form of a ‘Biarri Score’, which predicts an individual’s likelihood of readmission to hospital with ‘remarkable levels of accuracy’. Check out the article here.

The Biarri Score is now in place in the Gold Coast University Hospital emergency department. Also, patient criticality scores are integrated into local GP practices to provide intra-facility collaboration of healthcare services and prevent unnecessary admissions.

This application of Commercial Mathematics has resulted in increasingly better identification of patient who are likely to readmit, in order to improve the effectiveness of the Integrated Care activities and reduce demand on emergency departments.

 

Get in touch to learn more about Biarri’s Predictive Analytics capability or to learn more about applicaitons of Commercial Mathematics in other areas!

Biarri -Hospital and Health Services

Trimming away hospital costs: A bi-product of saving lives with statistics

Healthcare service delivery in most systems can be described as fragmented at best. In many healthcare systems, there has been very little continuity of care and integration for services provided by General Practices (GP), Hospital and Health Services (HHS) and other healthcare providers. Integrated Care is a worldwide trend in healthcare reforms that focuses on co-ordinating these different services.

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Supply Chain planning

Making the most of storage facilities in large construction projects

Large construction projects have a huge logistics component often requiring equipment from all over the globe to be brought together through a complex supply chain. In an ideal world, our suppliers would produce items on time and they would be transported to our construction contractors just as they needed them.

Unfortunately, we don’t work in an ideal world – suppliers can fail to produce on time, problems can occur in transit, and external forces outside our control can interrupt the construction schedule. For this reason, we want a contingency plan – usually in the form of a storage facility where we can hold spare or excess items if our supply and demand schedules don’t match up.

These facilities are used heavily over a short period of time, meaning that any inefficiencies quickly add up to large, unnecessary costs. However, given the size of these projects, identifying and fixing these issues is far from easy or intuitive. It is through analytics that you can drive quantitative answers and support effective decisions in your logistics and facility planning.

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Mitigation by Iteration

Mitigation by Iteration – Facilitating the Optimisation Journey

For companies to remain competitive, they require smart systems that solve their unique day to day business problems. However, when applying these systems many decision makers get lost in the complexity due to limited communication and collaboration within the implementation process.

We are at the cutting edge of the latest optimisation methodologies and web technologies. However, unlike many other optimisation, and analytics companies out there, one of our main goals is to make powerful optimisation accessible in the real world to bring value to our clients.

We specialise in the development of web applications and smart optimisation engines– delivered in less time than you would probably think. It’s not unusual for us to go from an initial workshop with a client, to understanding their problem, and then having a fully functional optimiser in a production environment within three months.

On top of this the same people are often involved through the entire SDLC (software development life cycle) i.e. from the spec/design, theory, implementation and delivery/support. This reduces the overhead many organisations incur by having different people in business analytics and developer positions. The people implementing the solution actually understand and work with you to solve your problem.

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