AI Driven Business Decisions

AI Driven Business Decisions

As COVID descended upon the assisted care industry, many were unsure how they would survive. Providing education services for children with disabilities such as autism is not something that can be easily carried out remotely. As the healthcare crisis mushroomed into a potential years long drama, people were questioning whether the service providers could even survive.

This feeling of despair was facing most industries as they tried to desperately pivot their businesses to stay afloat. Organisations in sectors like e-commerce were well positioned to grow, others like the assisted care providers less so. 

However, there have been some pioneers who have thrived. We can learn from their successes.

All businesses which have pivoted to digital have discovered one thing – a deluge of data. This deluge of data means that the next phase of growth out of COVID will be defined by two paradigms:

  • Businesses harnessing their digitally generated data to enter a new phase of growth defined by:
    • Cheaper and personalised marketing, 
    • Extended flexibility in delivery of services and products
    • Better operating margins
  • Businesses who are unable to leverage their digital assets and will continue to struggle throughout the crisis praying for it to end unable to meet the challenge.

The AEIOU Challenge

AEIOU is a provider of educational services to children with autism. Their mission is to provide early intervention that enables children with autism to live their best lives. 

In early 2020, it became clear to their dedicated team that the year was going to be different. As the global economy grinded to a halt and social distancing became the norm, the staff began worrying that possible COVID outbreaks in their centres could shut them down.

However, they had a trick up their sleeve – the Little Steps educational platform.

Over the previous nine months, the AEIOU team had been working indefatigably with Biarri to bring a disruptive new technology to the industry which would:

  • Remove the need for large paper folders transported around in trolleys;
  • Improve the efficiency of staff content delivery;
  • Make home based delivery possible and
  • Create a treasure trove of digitally collected, consistent and high quality data to be analysed for deep treatment and progress insights

And it would be this final point which has the potential to not only revolutionise the disability care sector but all sectors.

But how? And why?

AI Driven Business Decisions

Like AEIOU, across the globe many businesses are in the final stages of a planned digital transformation or one brought on by COVID. Those businesses which have already completed this process are now looking for ways to leverage the data being collected by the new digital processes and turn it into value.

So what is the best way to do this?

By combining your data with intelligent analytical tools to help make better decisions.

Having good quality data in a consistent format, collected by digital channels, allows companies to apply powerful analytical tools to this information and use it to help understand:

  • What will the future look like? I.e. make reliable predictions
  • What is the best decision to make? I.e. optimise choices to maximise returns and organisational growth
The Biarri Workbench

The problem is that data driven, decision-making normally begins with the in-house development of low-tech tools to manually solve key business problems. As businesses grow, they must move their Excel sheets to the automation of core business processes via mathematical tools to enable better decision making. Why?

Replacing error prone, slow, manual and insecure processes with robust, fast, automated and secure AI tools enable new phases of growth.

By providing digital tools to make optimal decisions, front line staff can move from manual, repetitive and error prone tasks to high value scenario analysis and answer key questions for senior management around future states and optimal strategies. What does this achieve?

It increases the value output per employee via automation and outmaneuvers competitors with better decisions

The above activities are the core of an AI Driven Business Decisions and form part of an AI Driven Digital Transformation which you can read more about here.

AI Driven Value Creation

By using AI to create value, companies can begin the AI driven digital transformation journey as shown in the below image.

But how can a company climb this curve? The details of this transformation are represented in the following diagram.

With the early learning platform, AEIOU have built the foundation of their digital strategy and the logical next step in their transformation is ground-breaking. By digitally capturing the data on learning outcome improvements for children with autism, they can discover new methods that can transform the journey for some of society’s disadvantaged.

Even greater for AEIOU was that their digital platform, Little Steps, was ready as Australia went into lock down. They were able to leverage it to continue the challenging remote learning regime required to not interrupt the learning process for their children.

This wasn’t the first app Biarri had built to enable companies to thrive during the COVID challenge. Biarri has built over a hundred apps to help companies all along the journey of turning data into value.

What role does Biarri play in this transformation?

Biarri’s main value proposition is to help clients realise operational excellence in the way they run their business. The core of this is excellent, data driven decision making.

How do we do this?

Biarri catalyses AI driven business decisions by employing its cutting edge Workbench platform. The Workbench platform empowers Biarri’s customer base in the form of value-creating production tools. 

In the words of businesses we work with, the benefits of a data driven approach leveraging mathematics are that it:

  • Helps make better decisions
  • Improves efficiencies & saves time
  • Reduces cost
  • Improves a business’ core product / service delivery
  • Is easier to use than alternatives (e.g. better than Excel)
  • Allows real time and scenario planning abilities

In AEIOU’s case we built a digital platform with plug and play analytical capabilities. This could tap into automated and optimised rostering tools and lead a true AI driven digital transformation. In the words of their CFO:

The development process with Biarri has been a great success. The team went above and beyond to deliver on our requirements and were engaged, helpful and responsive in understanding the complex needs of our business. The challenge Biarri solved was complex, however, the entire process from development to operation was collaborative and professional and we look forward to continuing our partnership with them.

Matthew Walsh, CFO, AEIOU

Does this apply to me?

Biarri delivers solutions to a wide range of industries. The mathematics which powers our AI knows no boundaries and one powerful model can underpin the efficiency gains in profoundly different industries, from aviation through to the healthcare.

To discuss how you can leverage your data and turn it into value, with AI Driven Business Decisions, reach out with the form below.

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Worker Fatigue

Workforce Fatigue Management

It was around two years ago that Anita knew that she’d had enough. However, the ensuing two years had passed so quickly repeating the same task over and over again. 

So here she was again.

Anita is the workforce manager at a company which manages a large temporary, contracted, part time and/or casual workforce. They carry out a set of known tasks, some of which require qualifications, many of which don’t. In any given week, she will be juggling her Excel sheet and a phone to desperately contact replacements for people who call in sick that day while ensuring that any replacement doesn’t violate any of their strict fatigue requirements. 

Although fast paced, it’s not the type of fast paced that she had hoped for as most of it was trying to carry out tasks which can be easily automated. So why not automate?

The reality with Anita’s work is that it can be automated and there do exist tools which can do most of her job and actually make both her as well as her rostered employees’ lives better. Anita could spend less time manually carrying out error prone tasks and, simultaneously, her rostered employees could get the shifts they want – meaning less work for Anita having to offboard unhappy employees.

By automating the error prone and repetitive tasks, this would leave Anita more time to more accurately cost up rostering jobs, better manage her staff so the good people keep coming back and focus on more strategic aspects of rostering.

The dream state.

Biarri’s Workforce Fatigue Management Rostering Tool

Biarri’s Workforce rostering tool was built to solve problems exactly like Anita’s. It was designed for companies which have built their success off the back of flexible Excel sheets, however, have now outgrown them. The tool excels when the workforce has become too large or too variable and the rules too complex to efficiently allocate people to the required work in a way that keeps everyone happy.

This was a situation faced by one of Biarri’s partners, Field Mining Services. Their process was Excel driven like most companies in the region and required a lot of manual work and time intensive copy of data between spreadsheets. 

In addition, customer rules/regulations and reporting obligations were a major pain point, with countless hours spent working with Excel and Word to create reports manually. 

However, the real pain point arose when you had many users working in a single Excel spreadsheet causing significant errors and delays for the team who were trying to understand who made the change which broke everything.

These challenges triggered a roster to invoice overhaul which Biarri assisted to complete by configuring its workforce tool to make it optimally suited to FMS’ situation.

The team at Biarri were fantastic to work with. They really listened to the pain points of our business and delivered a fit solution.” – Field Mining Services

Workforce Fatigue Management Tool Capabilities

At its core Biarri’s Workforce tool is built to take the complexity out of rostering by allowing a powerful optimisation engine to do the high quality rostering for you. The engine automatically and dynamically creates compliant and desirable rosters. 

When creating the rosters, the engine takes into account fatigue and EBA requirements. The EBA and fatigue management capabilities are able to take into account things like enforced breaks after working certain periods depending on: 

  1. Location
  2. Type of work
  3. Time of work
  4. Length of work
  5. And more 

As well as many other similar rule types.

Biarri’s Workforce tool allows the bespoke configuration of a rich set of constraints suitable to any industry. When it comes to managing a highly flexible workforce (comprising many part timers, casuals and contractors), the engine can optimally look at options and do things like sharing employees across locations to improve flexibility. The benefits are:

  1. Smooth out demand, and the resulting work, to better distribute tasks to people who don’t have enough work to do in one location or too much in another
  2. Resolve skill mix requirements at a location where key skills are missing
  3. Reduce the amount of onboarding, hiring and redundancies of staff due to more flexible use of staff
  4. Create a better employee experience by creating the flexibility to cater to staff needs
  5. And more

The functional user interface allows the easy management of flexible and continually changing rosters for staff, for example, when employees call in sick.

As well as being capable of catering to complex work requirements, the tool employs modern web based technologies to integrate seamlessly via REST APIs into payroll and T&A tools. This means you can avoid complex integrations and replacements of existing tools. 

The Biarri Workforce Rostering Application integrates into any stack with predefined interfaces.

Typical Outcomes

So what are the benefits of using optimisation and automation to do your rostering? For customers like Field Mining Services it is:

  • Better workforce fatigue management
  • A complete understanding of the value chain from mine to port
  • Substantially increased compliance with site specific access rules including fatigue, D&As, and site specific qualifications.
  • Increased visibility of workforce fatigue across multiple job sites.
  • Significantly reduced overall administration effort
  • The ability to tackle the next phase of growth with certainty around one of the most challenging areas – staff and fatigue management
  • Transparency across all departments and a single source of truth.

In other industries we have also seen benefits with improved employee engagement and experience by being able to take into account employee preferences and desires and then automatically catering to these needs. This leads to employers becoming employers of choice and staff bringing their experience and good habits back to your organisation instead of another casual staff provider. 

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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.

Biarri’s tools are trusted by

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COVID Cases in Australia

Optimised Health Care Rostering as a Managed Service

Coronavirus cases in Australia
The Coronavirus Status in Australia as of March 16 2020

With the outbreak of the COVID-19 pandemic, the most important aspect of our health care systems has been put to the test – people. It has resulted in longer work hours for all, with leave blocked out for the next foreseeable future and put an enormous strain on an already strained system – both emotionally and financially.

When things are difficult like this, the best we can do is to leverage the best tools possible to get ahead of these situations. And it is not just N95 masks and ventilators that hospitals need to function properly. Even more important than this are good rosters.

The Importance of Good Health Care Rosters

As helpful as ventilators and N95 masks are, without great people around to use them, they are no use. However, having great people is only half the story. The other half is giving them the right amount of work to do so they don’t burn out or work too long hours. It has been shown that poorly rostered staff who:

  • Work at least 12 hours per day are associated with a 37% increased hazard rate and
  • Work at least 60 hours per week are associated with a 23% increased hazard rate

When it comes to Coronavirus, the numbers become even more frightening as the effects are worse than simply longer hours. A new study, published in the Journal of the American Medical Association, shows just how bad it can get.

The survey-based study examines the mental health outcomes of 1,257 health care workers attending to COVID-19 patients in 34 hospitals in China. The results put the negative effects of overworking in perspective. Significant numbers of people reported experiencing symptoms of depression (50 percent), anxiety (45 percent), insomnia (34 percent), and psychological distress (71.5 percent).

These statistics are threatening the health of not only our medical staff but also patients and so it is essential that we start developing better rosters immediately to reduce the overworking and also the mental burden.

However, there is a final issue just as important as the above which can also end up costing lives but is much easier to solve. The issue is simply about who does the rostering.

Biarri’s rostering tools are trusted by the following health care providers

Every Person Counts – Rostering Medical Staff

Although it may seem strange, in a typical emergency department it is often one of the consultants themselves who writes the rosters for the other consultants. In the time of a pandemic, we need every skilled person working and not having them spends days writing rosters for their colleagues.

In Biarri’s rostering work across many health departments, we have calculated that rostering an emergency department consumes around 20 days of clinician time per annum for each roster. In many emergency departments alone they can have four or five rosters covering:

  • interns,
  • residents,
  • registrars,
  • fellows and
  • consultants.

All these rosters add up to a lot of wasted days and in the times of COVID-19, by using optimised and automated rosters, we could save dozens of lives and provide more essential care to people who need it.

Optimised Health Care Rosters as a Managed Service

Based on the above benefits and the imperative of having all qualified doctors best utilising their skills, Biarri is offering its automated and optimised roster creation tools as a managed service. Out of demand from numerous hospitals and the need to provide the service quickly without any IT work whatsoever, Biarri is now offering hospitals access to its automated, dynamic and optimised roster generators for the next 6 months as a managed service. During April 2020, instead of acquiring a new tool and having to learn how to use it, Biarri will carry out this work on the behalf of the hospitals.

If this is of interest, please send an email to and we’ll get back to you immediately as to how we can help manage the creation of optimised and compliant rosters.

The Benefits of Optimised Rosters

The benefits of automated and optimised rosters are many, and we have detailed them elsewhere, but the most important features and benefits of Biarri’s optimised, dynamic rosters are:

  • Customisable to capture working rules and payroll requirements.
  • Make rosters more evenly distributed from a fatigue perspective (reduce burnout)
  • Rosters account for staff requests (RDO’s leave, availability times & specific shift requests).
  • Creates equitable rosters with required training and appropriate mixture of shift types.
  • Ensures the right mix of skills is on the floor always
  • Can generate preferred shift patterns with night shift blocks & weekend, day off grouping.
  • Minimum break rules based on type and time of shifts.
  • Demand driven shift generation rostering only those staff required.
  • In a health care setting, it typically takes 2 senior doctors up to 3 days to create a 10 week roster. With an automated and optimised rostering system, it can be done in under 30 minutes.

So reach out to us now to get your team focusing on what they were trained to do and not struggling to produce sub-optimal rosters leading to possible staff burn out, depression and anxiety issues.

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AI Driven Digital Transformation

Part 2

Part 1 is here.

Finding an AI Suitable Business Problem

About a year ago, I began working on one of my most difficult projects for the Victorian Government. It was a project that quickly looked like it would end in a consulting train wreck and possibly cost me my career.

The project began with our team sitting around a desk with the client and being handed multiple data sets. We were then told to “do some AI with it”. Not only that but we were given four weeks to produce something of value that wasn’t obvious to the client.

Given the time frames, we got straight into the task but approached it a bit differently given we knew we were missing a key part of the project – the business problem.

The first two weeks passed quickly with us tackling both cleaning and preparing the data but most importantly, one of us was spending a significant amount of time with the client trying to understand their current challenges and link these challenges back to their data and then request more data as we realised what was missing.

By taking an agile approach and having a highly collaborative team (with the design thinking part working closely with the analytics part of our team), we were able to navigate a challenging project and “do some AI” with the data set.

We discovered a business problem which we could share valuable insights on and quantify people’s intuitions, which helped the client as it killed the HiPPO[1] and replaced it with facts.

Quantifying gut feelings then led to several clear actions for the client to take which improved their service delivery, i.e. their core value proposition. We will see below why this is important and how it can determine the difference between failure and success of AI driven digital transformations.

Although not recommended, this approach to analytics succeeded but how should you approach such a challenge if given the choice?

Via the Business Problem

Someone once asked me,

“How do I understand the value of a data transformation? I mean, how can I know what it’s worth?”

The answer to this question is simple – on its own, a data transformation is worth nothing.

To be valuable, any data driven activity needs to solve a business problem. That is, why are we joining this data or building a massive data warehouse? What is the point of this analysis?

Most importantly, what action will be taken based on this analysis?

These questions lead us to the answers of the final questions we had in the previous post [Link here].

This idea of analytics leading to action is so important that at Bunnings the internal analytics team has three tenets to their analytics work with the third part being the most important:

  1. Aggregate
  2. Analyse
  3. Act

More than just creating a data warehouse, the purpose of analytics work is to derive insights and then do something based on that. Bunnings may have refined its approach over years but what should you do now?

The Right Way to do Analytics

There are many recommendations as to how to approach the challenge of deriving value from analytics. One was proposed by Gartner and looked at a company’s analytics maturity – however, this was wrong.

According to Gartner, a company’s AI capabilities are measured on 4 levels:

With each of the levels answering the following question:

  1. Descriptive: What happened?
  2. Diagnostic: Why did it happen?
  3. Predictive: What will happen?
  4. Prescriptive: What should I do?

As we saw in the Victorian Government example above, what counts is to have a business problem to solve and then to find a more efficient, digital way to solve this problem – not analytics maturity for the sake of analytics maturity. Once we have the business problem, and if we are new to the analytics space, we can use the Gartner model not to go too deep too fast and risk derailing the effort.

Finding the Right Business Problem

So we now agree that we need a valuable business problem to solve. Best is a corporate challenge burning across a P&L or balance sheet right now. Problems people currently face are ones they want solve – now.

However, how do we find the ones suitable to ignite an AI driven digital transformation?

The suitable challenges can be found at the core of the business. The challenges conducive to leading to something big are ones that form part of the chain of delivery of a business’ key services – the challenge itself doesn’t need to be big, it can be small but still have a big outcome!

For example, an amazing Australian success story, which successfully carried out an AI driven digital transformation, was by a company once called Aerocare.

Aerocare was founded in 1992 to provide ground services to airlines and airports. If you’ve ever looked out a window after landing at an Australian airport and see a team unloading your baggage from the aircraft, you are most likely looking at former Aerocare employees.

Aerocare’s value proposition is the cost-efficient delivery of people and equipment to quickly and professionally load and unload aircraft. Their value chain begins with forecasting airline service requirements at airports and ends with the unloading and then reloading of the plane on the day and time of the arrival of the plane (even if different to the plan).

If we examine the value chain and look at where an AI driven digital transformation can have the greatest impact, it is anything that improves Aerocare’s delivery of services. Aerocare also understood this, so they quickly identified a bottleneck in the Excel based rostering of people to deliver their services at gates and planes.

As the number of Excel tabs began pilling up and choking calculations – leading to weeklong rostering activities, the AI driven digital transformation opportunity had arisen. No unnecessary data warehouses for the sake of it, whatever was to be done would lead to change.

So Aerocare realised they needed to replace the current Excel based processes with AI tools to automate the roster creation and delivery.

This meant little or no change management – just better rosters. People followed their previous processes but with better tools. Like our health client, we’d found a part of their service delivery which could be easily replaced with AI tools. This then fundamentally transformed the way they delivered their services without changing the way the company did business as well as avoiding the risks associated with a large digital transformation.

Very quickly this led to more efficient allocation of resources, more competitive bids for service provision at airports and significant company growth. The result for Aerocare?

In 2017, the global ground handling giant Swissport acquired Aerocare for an undisclosed sum of money.

Why Did This Approach Work?

In 2015, MIT Sloan review published an article which incidentally revealed why the Aerocare approach to AI driven digital transformation worked. They stated:

“[M]aturing digital businesses are focused on integrating digital technologies, such as social, mobile, analytics and cloud, in the service of transforming how their businesses work. Less-mature digital businesses are focused on solving discrete business problems with individual digital technologies.”

The Aerocare solution seemed to solve a discrete business problem, however, it was one that transformed how the business worked, as intended in the first part of the MIT Sloan quote.

So we don’t have to look to uproot an entire organisation – we just need to find that part of the service delivery that is currently being done on a regular basis with:

1. Paper based tables; or

2. Excel sheets; or

3. Complicated, manual database queries.

Assume some general delivery of services or products as shown in the following diagram:

Then if any of the bullet points in the white boxes are being carried out using one of the above three manual methods then each could be tackled independently and easily via an AI tool. Once we’ve found the part of the service delivery in the above stylised diagram which is like 1, 2 or 3 above, then it is time for AI driven digital transformation.

Turning Data into Value – AI driven digital transformation

The answer to the success of the transformation question seems simple but it is only so in hindsight:

Find the key part of your service delivery that is not automated. This can most likely be recognized by the usage of Excel or regular, manual database queries.

Then replace this part of the service delivery with AI tools. The value is clear and immediate so let’s make clear what we’re doing:

Replace error prone, slow, manual and insecure processes with robust, fast, automated and secure AI techniques.

This now can resolve our question we posed earlier:

“How do I understand the value of a data transformation? I mean, how can I know what it’s worth?”

By choosing a business problem associated with your service delivery, it then becomes clear and easy to identify the value of the improvement as the change will directly improve the bottom line. It will improve the way your business operates and the value of the business. AI driven digital transformations allow one thing above all – more profitable and faster scalability via better decisions and automation.

Not only does this show us how we turn the siloed piles of data into value (we don’t touch them unless necessary), a McKinsey study showed that digital transformations that use some form of artificial intelligence, are almost 50% more likely to be successful. AI is one of the greatest factors that differentiates companies with successful digital transformations from those that aren’t.

So where does your Excel bottleneck exist? What part of your business can you transform with an AI driven digital transformation?

Reach out to us below to find out how and discover more companies embracing AI.

[1] Highest Paid Person’s Opinion

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AI driven digital transformation

Your AI Driven Digital Transformation

Part 1

Even in the world’s best operating theatres, patient outcomes depend on more than the surgeon or their equipment.

Currently in hospitals around Australia, when and even whether you see a surgeon isn’t due to a medical expert but a booking clerk. To understand how this works, the following diagram outlines the current process in most hospitals:

After a hospital receives and approves your Request for Admission, to book you into an operating theatre, a booking clerk will often begin by recording your potential booking date in a notepad or Excel sheet. Only after reviewing hundreds of other patients will the clerk finally secure you a spot in the hospital software booking tool, once they are confident the proposed time is the best outcome available – that they can find.

This intractable game played by booking clerks is a gigantic puzzle placing thousands of patients with varying operation lengths and medical needs into a limited number of booking slots. Simultaneously the clerk needs to pay attention to the severity of the condition, the maximum permitted length of time until the guaranteed operation, other pre-operative complications and much more. It is a difficult problem with a range of constraints and variables making it very difficult for even the best booking clerk to optimise. 

It is also one of the greatest success stories of AI driven digital transformation.

Improving patient outcomes does not require complex change management, more human resources or redesigning the extant booking processes – just let AI take care of the ordering and optimisation of which surgery slots are given to which patients. This relieves experienced medical and clerical staff of the laborious and complex allocation process and leaves them free to focus on the quality control functions of reviewing, amending and approving an already optimised schedule.  

This type of improvement is a welcome one, as patient waitlists across Australian hospitals remain a source of patient dissatisfaction and are only set to get worse with an aging population.

So what can be achieved with such a seemingly straight forward upgrade to a booking process?  In the current health care system, even a 1-2% improvement would be revolutionary.

Biarri has been fortunate to have recently rolled out such a tool at a large health provider in Australia and in this case, the results so far have shown double digit improvements in operating theatre utilisation – double digits.

This is a step change improvement that shows the true potential of intelligently integrated AI tools. We estimate that it will lead to a reduction in the cost to treat a patient by around $200 / patient. With hundreds of thousands of patients going through the Australian medical system alone, this will save tens of millions of dollars.

What this AI driven digital transformation shows is that we can reduce our waitlist faster than ever, with the same number of resources. It is the gigantic puzzle of allocating people to surgical slots that is causing people to miss lifesaving surgery and it is a task perfectly suited to AI – and it exists in all industries.

In this set of articles, we’ll discover how to achieve this type of transformation in any organisation. This first article sets the scene and the second article will reveal how to create the value.

But before we discuss AI driven digital transformations, what is a digital transformation in the first place? And what change does AI make to it?

Digital Transformations

Digital transformations are about using digital technologies to create new or modify existing business operations, e.g. the day-to-day processes to provide a service, customer experience or a transaction.

When people speak about it, a digital transformation is often used in the sense of replacing one simple digital technology such as Excel with a large scale, holistic software system (often cloud based), especially in an enterprise with thousands or tens of thousands of employees.

The first digital transformation to typically occur in an enterprise is the implementation of a back office tool to manage finances (general ledger managing the cash going in and out, receivables, invoices, etc.), management accounting (budgeting, costing, etc.), procurement and more.

These capabilities are often rolled up into what is called an Enterprise Resource Planning (ERP) tool. Other major digital transformations, which often happen separately to ERPs but can be a part of it, are implementations of CRM tools which go beyond just the storing of customer data and create triggers and actions based on the characteristics of the customers’ behaviours – a first step on the journey to AI.

And the AI part?

Artificial Intelligence in industry typically refers to a set of mathematical techniques that allow one to make predictions or prescribe what actions to take. In the modern sense it often involves lots of data and applying analytical techniques to this data to answer questions like:

  • How many sales can I expect tomorrow?
  • Where should I best locate my products to meet this demand?
  • How can I route my vehicles to make sure those products are in those locations in time?

AI and digital transformations should go hand in hand because whatever the digital transformation looks like, it always leads to one thing – lots of data. So what can we do with this data to create value via AI?

Data – A Curse or a Boon?

Let’s shift gears for a moment and assume you now have begun your digital transformation and the data is flowing. You look at your data sets and a sinking feeling sets in.

After carefully gathering requirements, making sure you used the right mix of cloud technologies and then digitising the processes with the right tools, you realise your next big challenge:

The data from each system sits in its own silo.

As the complexity of this task sweeps over you, your boss bursts through your door, breaking your train of thought, and barks at you:

You’ve got all this data, now what? How do you start creating value? And I’d like to know by the end of today.

It dawns on you that this is the whole promise of the digital transformation that you bought into – a holistic view of your operations. Given what your boss has now demanded of you, how can you create value quickly?

Do we need to combine all this data now?

Is a large, expensive data warehouse the first step to the answer?

By choosing the right analytics battle, as we saw with our health client that the solution to the previous questions can be quite simple and deliver enormous benefits but many stumbling stones lie ahead of you – the first of them being your migration to the cloud.

Data Lake

Creating a Lack of Value

The trend to migrate to the cloud is currently one of the biggest tech trends of the last three years. With over 85% of enterprises now having a multi-cloud strategy, there seems to be no stopping its inexorable steamrolling of anyone expressing a different opinion.

However, as cloud migrations are creating a crowded sky, more than one in three cloud migrations are failing – even when we try and measure it against any metrics of your liking such as:

  • Reducing costs;
  • Improved staff productivity; or
  • Increased revenue

At the same time, around forty percent of global information workers are circumventing IT policies to try and maintain their productivity. The icing on the computational cake is that the productivity of employees is experiencing a gradual decline due to the complexity of current IT strategies and policies. So as you add your new layer of “cloud efficiency” on top of the existing IT systems, you recognise there is a risk that things may not turn out as planned.

So where is this taking your digital transformation agenda?

A 2017 Dynatrace study revealed that:

IT complexity and performance challenges are killing digital transformation initiatives, and causing organizations significant digital performance problems as often as once every five days.

The digital transformation to the cloud may be harder than people anticipate but what about the analytics/BI part of the transformation? Surely once you’ve sorted out the digital transformation challenges, the rest flows from there, right?

Not always.

A Logicalis survey recently showed that typically 60% of CIOs rate their organization as 3 / 5 or less when it comes to deriving value from BI and analytics work.

In fact, those who have derived value are few and far between and many would like to do something about that: less than 20% of CIOs say their organisations are using AI. Like your company, they’ve probably built the data warehouse in the cloud but they are still yet to derive insights and take actions from it.

What is going wrong?

With 66% of CIOs wanting to see AI adopted in their organization in the next 3 years, it is not a lack of will. Digital transformations have been praised as the next industrial revolution that is supposed to lead to untold benefits and chart busting efficiency gains. So where are they?

In the next part we will find the surprisingly simple way to achieve the promised gains without reinventing your business. By focusing on an AI driven digital transformation, you will increase the chances of success of your digital transformation and quickly show some early wins.

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Better Digital Experiences

The State of AI in Marketing

As Artificial Intelligence (AI) permeates almost every part of every business, it is important to stop and review how AI can help you do your job better.

One field that has been dramatically affected is marketing and so it was timely that WP Engine has now brought out a survey with Smoothmedia and Vanson Bourne to reveal how the marketing landscape is being disrupted by AI.

The Results

As part of the panel of experts interviewed for the report, Biarri has been provided exclusive access to the report here.

Biarri’s key contribution to this important research was revealing the way data is best used and managed to deliver practical results to marketing departments without setting false expectations and over promising things that AI cannot deliver.

Download the report to discover what trends are changing the way marketers exploit AI to achieve results such as:

  • 42.5% of businesses seeing a visible increase in sales with AI
  • 37.5% increase in customer satisfaction
  • 29% increase in website visitors

Positive results such as these have led to around 32% of businesses planning to increase their AI budgets by more than 50% over the coming period. So we expect to see a separation in the market of those businesses which pull ahead of their competitors with AI and those who see their market share eaten away by AI driven experiences.

The key is using AI to deliver better digital experiences which leads to more relevant and personalised content. However, a question which many marketers must ask themselves is will this personal data be used for unethical purposes? The answer from the research was clear: 57.6% of survey respondents said they believe AI will ultimately have a positive impact on the world.

Biarri and AI in Marketing

Biarri’s team has a depth of experience in delivering retail and marketing AI solutions around:

  • optimal channel management,
  • market mix modelling,
  • pricing optimisation,
  • life-time value modelling,
  • anomalous behaviour,
  • churn modelling

and much more. Reach out to us now to find out how you can leverage AI to improve your marketing performance. We have conducted our own analysis to be able to show you the pathways to fast value with AI tools.

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Join us at the Biarri Applied Mathematics Conference at UQ

Biarri Applied Maths Conference

Join us this year at the BAM2019 conference to find out how to make better decisions with maths.

It’s only been one year and it’s back on again by popular demand: the Biarri Applied Mathematics conference – BAM 2019. This event has been heralded as the top applied maths conference in Australia. You’ll find out how you can apply maths at all levels in an organisation and academia to make better decisions. The who’s who in mathematics and industry are coming. Have you got your tickets yet?

Get your tickets here now.

Over 230 tickets have been sold with only a few remaining. The best part? The tickets are FREE.

Why come?

Strategy, innovation, operational success and a good bottom line all rely on one thing – good decisions.

At BAM2019 you will learn how people are harnessing the power of well-known optimisation, machine learning, artificial intelligence and cloud based techniques to scale automated, powerful and objective decision support tools to help us break out of decision paralysis.

It will showcase some of Australia’s best real life examples of the use of mathematics to drive amazing business outcomes by making better decisions at scale.

Join us at BAM2019 on the 20th of November 2019 to discover the new simplicity of now.

Get tickets here.

Check out the BAM2019 website.

BAM 2019 logo

BAM2019 is on!

Join us at the most fun maths conference of the year

Strategy, innovation, operational success and a good bottom line all rely on one thing – good decisions. Not only that but fast, data driven decisions too. As time runs out, the data sets are multiplying creating the paradoxical situation of making decisions harder.  But there is one easy decision this year – attend BAM 2019

The Biarri Applied Mathematics conference – BAM 2019 – is the top maths conference in Australia and due to popular demand we’re holding it again this year. There are a limit of 250 spots of which are number are already gone. So grab your tickets now so you don’t end up on the waiting list like dozens of people did last time. The best part? The tickets are free.

Get your tickets here now.

Why come?

This year’s event will again see industry leaders from Australia’s top companies as well as top researchers from UQ and other universities presenting their latest insights on making better decisions. This year we’ve decided to change the format and have the whole event happen on one day on the 20th November, at the beautifully accommodating St Leo’s college at UQ.

You’ll discover expert discussions, see maths in action at the demo table, rub shoulders with thought leaders and talk to your peers in an intimate environment.

Time to decide: automating solutions to your business challenges

The theme of this year’s BAM is making better decisions. At the event, you will learn how mathematics is powering the best decisions making tools on the market.

Not only that but you’ll discover how by harnessing the power of well-known optimisation, machine learning, artificial intelligence and cloud based techniques we can scale automated, powerful and objective decision support tools to help us break out of the decision paralysis facing so many companies today. It will show you how to data into value.

You’ll learn:

  • How can you use maths in your job to make better decisions?
  • How can you use maths to save costs and be more efficient?
  • What is the pathway to better decision making with maths?

At BAM2019 you’ll discover the answers to these questions and much more so get your tickets here now.

Check out the BAM website here.

Rostering workforce

New Workforce Rostering Feature – Leave Management Calendar

Biarri has now released the first new feature as part of the wider demand from our customers around management enhancements. Specifically, the web-based calendar view of roster requests is now available as a potentially more intuitive alternative to the existing table view. For those who have seen the mockups of this screen it should look familiar.
The screen is very similar in look and feel to the rostering Gantt, with the items in the Gantt instead representing roster requests per person/date. Some included features are:

  • View customisable time ranges and periods.
  • Toggle additional employee data (group and roster pattern) in the fixed columns.
  • Right click on an employee name to view their profile in a new tab.
  • Standard filtering, sorting and colouring options to customise the view and drill down into the data that interests you. This applies to both the employees and requests in the view (similar to the rostering view with employees and shifts).
  • Total unavailable/available KPIs per day calculated from requests on that day. Note that these numbers are calculated using the filtered employees and requests – e.g if you want to filter for only annual leave requests, the KPIs will only show total number of people with annual leave requests per day.
  • Hover over requests so see their key details in a popup menu.
  • Click on requests to open up the standard screen which allows you to action the request (add to roster, approve or reject).

We are still working on other additional request management features – specifically to allow rostered users to more intuitively interact with their requests, as well as have a view of other employees requests.

Stay tuned here for further updates. To learn more about our workforce tool, check out our blog post on it here.

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