MapR: the future of MapR and HPE for AtoBI

At AtoBI, we are always sure to stay ahead of the curve when it comes to the software programs best suited to the needs of our clients. One of our current software programs in use is MapR, a Data Platform used to gather AI and analytics dataware. There are many benefits to using MapR, and yet recently there has been some concern as to its future and how best to support its users. CEO of AtoBI, Elaine Graydon, attests to the efficiency and benefits of using MapR, and will continue to support MapR throughout these changes.

Firstly, let’s look at the benefits of using MapR.

No matter your underlying infrastructure for data, the MapR dataware can handle a multitude of different data types. Users gain access to the MapR Data Platform, which allows them to store, manage, process and analyse data no matter their source. This software includes complete data protection and disaster recovery, to give you confidence knowing your data is protected.

MapR and HPE

After MapR Australia closed on May 17th 2019, there was a lot of uncertainty around customer support, expansion licensing and new purchases. Before this, MapR had announced they would be closing their corporate headquarters due to funding issues. This caused some upset for users, and the time between this occurrence and August 4th left MapR clients up in the air. However there is good news, as on August 4th Hewlett Packard Enterprise (HPE) acquired MapR signaling a positive change. AtoBI customers can be confident that MapR will continue to function and thrive. With support from MapR/HPE and us here at AtoBI, there is no better time to start using this dataware and make the most of your data capabilities.

We are pleased and excited to continue to bring this amazing toolset to our customers, a toolset we know will continue to provide outcome requirements. MapR will now continue to be innovated to match customer requirements, and we are confident in the future of MapR for Australians.

Want to know more about our work with MapR? Contact us online or email us at info@atobi.com.au to get in touch regarding MapR. AtoBI are industry experts in business solutions, and together with AI technology we can help you improve efficiency in all areas of your business.

Value of Data and Explosion of Data Volumes

As the business world delves deeper into the possibilities of technology, there is no doubting the power and importance of data. When it comes to increasing your sales profitability, it can be difficult to know which steps are best to ensure that your people are making the most of the avalanche of data now available to them. Businesses must manage data from a myriad of sources – and it is important to know which channels are worth your time. With a landscape that is growing more complicated every day to increase efficiencies, manage costs while continuing to show profitability, there is one vital resource which businesses are not taking full advantage of.

This resource is offline data. The power of offline data is that it allows you to see behind the scenes of what is really driving your decisions, as well as giving you the confidence to know your data is whole before then using it to develop important strategies.

Did you know that large amounts of customer activity happen offline, including 90% of retail sales? This means that sales and marketers are missing huge amounts of data, data which could make or break growth strategies and decisions.

Data onboarding allows you to combine your offline data with your online data, allowing you to use both types of data with a complete understanding of what’s going on. In doing this, you are able to create targeted, personalised communication for customers, and in a time where customers need individual validation this is a smart decision. Data onboarding take the offline data and then links to the relevant data in the digital world, resulting in far more relevant strategy.

Having incomplete data is a real concern for businesses and markets alike, and it’s easy to become overwhelmed. At AtoBI, we are able to ensure you are making the most of all of your data, offline and online. You can be confident that our team will give you all the information you need to make the right decisions for your business, putting you one step ahead. For more information, visit our website or contact us at info@atobi.com.au

What You Need To Know About AI

Artificial Intelligence is now everywhere. From a Science-Fiction concept to an widespread technology, it often comes with clichés and misconceptions (Yup, we’ve all seen how it ended in 2001 Space Odyssey, The Matrix or Terminator…)

More and more organisations of all sizes and industries are trying to understand how they can leverage AI and get aboard the hype train. But from a buzzword to an actual solution delivering strong value, their are a few things to keep in mind before taking the leap.

Artificial Intelligence projects can fail if they are not led for a really, really good reason. This might seem obvious, but having witnessed the significant impact they have on an organisation, the business case must be ambitious though pragmatic, focusing on tangible business outcomes. Also, and as sexy as AI can be, is it the most adapted technology to solve that specific business case?

There are many compelling use cases in all industries and departments, from Sales to Finance, Marketing, Health & Safety, Logistics… and more which create competitive advantage and massive savings. This Gartner paper also encompasses good practice when building your business case.

Until future systems can embrace human-like top-down decision-making, current Artificial Intelligence technologies relies on data. A lot of data. It must combine quantity with quality, needs to be clean, comprehensive and avoid siloed information, biais or partial data (limited history, demographics…)

If it is sometimes challenging to figure out what data you will need for your algorithms to learn and deliver efficiently, working backwards from the problem you are looking to solve can help determine where to start.

In today’s digitized economy, the ability to use data represents a real and essential competitive advantage. To get to a future state of mature analytical competency, there’s real work to be done in integrating the data you have already. This is a strategic goal for the entire company and, when addressed properly, will lead you to develop experience and a data infrastructure that unlocks every next step. HBR

In other words, walk before you run and get a good understanding of your data first: Conduct an audit of what data you have and where it sits, making sure you have easy access to all relevant information.

As mentioned earlier, AI, Machine Learning (ML), Robotic Process Automation (RPA) are subject to many misconceptions. Amongst the most common ones are:

  • AI is a physical entity – Yes, some people still think of AI as a Terminator-like robot. Well, HAL 9000 would almost seem like a more accurate description…
  • AI can think like a human-being – Replicating the complexity and flexibility of a human brain is way beyond existing AI technologies. “The biggest misconception around AI is that people think we’re close to it.” Prof. Gary Marcus, NYU
  • AI can learn on their own – You have to teach them how to learn and improve, tweaking their algorithms constantly and feeding them with data
  • AI is alsways objective AI can have massive biais too
  • AI will take your job – It doesn’t replace jobs, it makes them more strategic, according to many serious studies
  • AI can use and figure out your messy data – As seen above, you need to figure it out first.

Education is key, not only to raise awareness around what AI will bring to the business at an operational level, but also to get executives onboard, promote data literacy and manage their expectations. Support from the top-management is critical to drive change, get access to all data, overcome political hurdles and lead with vision.

Driving AI projects is everything but a one-off process. The best performing organisations have in-house experts and developers constantly improving models and algorithms, making sure they are updated on a frequent basis and adapting to the latest requirements and information.

Project Management methodologies also need to be adapted to this iterative approach, ensuring constant alignment with Business Outcomes and continuous improvement: Scrum, Agile

We have seen how strategic your data is, especially when it comes to AI. Data governance gives you a real competitive advantage, as it will directly impact the quality of your predictions and algorithms. An efficient data governance strategy must cover:

  • Security – Managing access to data
  • Integrity – Making sure the data is accurate
  • Loss prevention & backup – Mitigating data loss/corruption risks and protecting privacy, especially when it comes to sensitive information
  • Lineage – Keeping full transparency for everyone to understand where the information comes from and how it’s been processed, avoiding the “black box” effect
  • Completeness – Avoiding biais and partial views
  • Ethics – This is sometimes overlooked but we cannot emphasize enough how critical this is, in business as in our everyday life.

Automating Sales Tasks

Sales reps face the constant battle of time management, and when it comes to completing those make-or-break tasks, finding the time can be difficult. By implementing a sales automation process, your business can maximise efficiency. In both a professional and personal sense, AI-powered software and tools are becoming a normal way to save time. Not only do companies with a sales automation process have a 53% conversion rate, they also have a 3.1% increase in annual revenue. Automating sales tasks is a budget friendly way to reduce your operating costs by up to 90%, according to a recent study.

There are a few sales tasks in particular which can benefit from automation, such as reporting, email personalisation and pipeline management.

When it comes to reporting, by automating your reporting process you free up valuable time to spend improving your business in other areas. As a sales manager, it can be frustrating when you’re scouring through out-of-date information to pull together a report. By automating this process, you can have confidence that your data is always up to date and relevant.

By personalising your email content, your audience will feel that you understand them, increasing your engagement rates. Personalising the first and last 10% of your emails seems to be the most effective strategy, and you can gather this data using a customers purchasing history, their personal information like age and gender, as well as tracking their awareness of your product.

The best way to monitor your leads is by automating your pipeline management system, which removes the urgency of manual tracking and ensures that quality leads aren’t lost. Automated sales processes allow you to generate leads with more accuracy, increasing your retention rate. Your lead prioritization and distribution can also be improved with automation. Sales automation helps your employees function at their best. A good sales automation system is easy to use, functional and effective. At AtoBI, our team can help you achieve the highest level of efficiency using data. Contact us today to find out more about what setting up a sales automation process can do for you. 

4 Key Factors to run a successful Business Intelligence/AI project (or how to make failure constructive)

Because there’s no better way to start than a quote from one of the most iconic athletes of the decade, as Lebron James once said:

“You can’t be afraid to fail. It’s the only way you succeed. You’re not gonna succeed all the time and I know that.”

In the age of unprecedented information growth and data-driven businesses, it appears most Business Intelligence (BI), Artificial intelligence (AI), Corporate Performance Management (CPM) and other data-related projects will fail, or won’t fully reach their objectives.

Keeping in mind failure is a risk one can only mitigate, the question is:

How can organisations maximise their chance of success when selecting and implementing technology, and in the unfortunate event it goes south, how can they leverage failure to later generate higher value?


1- Engage with all key stakeholders

All data-driven projects, from BI to AI & Machine Learning (ML) aim at breaking silos of information within the business, consolidating data from various sources, building a 360° view across all systems, providing more context to support business-driven decisions. However, this is often seen through the technology lens and organisations also often need to break silos of communication. This can only be achieved with the support of senior management.

The Human factor is obviously critical for success/failure and must start from the very beginning. Engaging with all parties can be compared to an internal sales process:

Create win-win relationships

The first question that needs to be answered is: “What’s in for me?

You want the Sales team to stop using spreadsheets for their monthly forecast because it’s error-prone, inefficient , and forces the Finance department to spend hours in manual data processing? Well, it’s only going to work if you also understand how it can provide value to them: helping negotiate better deals, answering customers’ questions faster, making more commissions… and balance with the perceived cost of change.

The Finance team needs a flexible budgeting tool because the planning solution managed by IT is too complex for ad-hoc analysis, what-if scenarios and instant queries (especially in times like monthly re-forecast or closing)? How can it be implemented with the support and in conjunction with IT, complementing their effort & investment rather than running under-the-radar, parallel processes?

Many Artificial Intelligence projects failed because they couldn’t link operational and strategic outcomes, provide clear value & ROI to front-line managers and employees.

Identify roles & responsibilities

Mapping key stakeholders, influencers, decision-makers, supporters, detractors… is vital not only to get the project started, but also to keep everyone engaged and accountable for the project outcome. I have seen projects where everyone from IT, Sales, Finance departments, both at operational and management levels were extremely engaged and excited at kick-off, but two months into the project failed to deliver due to the lack of clear responsibilities and accountability.

Common personas in successful projects are:

  • The Champion(s), who will get their hands dirty and learn how to translate the business needs into a technical language by mastering the technology. They will be the main interface between the organisation and the technology vendor/partner.
  • The Enabler(s), who will create bridges between all stakeholders, keep them engaged and mobilise resources throughout the project.
  • The General(s), accountable for the project outcome at a top-management level with the authority to make decisions and keep a strategic focus.
  • The Engineer(s), in charge of keeping the project compliant to the company’s IT standards & policy and providing the technical infrastructure.
  • The Customer(s), (I am referring to internal customers here: the end-users) who must provide consistent feedback and communicate back on how the project is adding value (or not) at an operational level. Their voice is not always audible or heard but determines the long-term success of any implementation.

2- Define clear outcomes

This can be a tricky step, because the impact of a BI/CPM/AI… roll-out is not always easy to quantify, i.e. “You don’t know what you don’t know”.

Measuring success is comparing the difference between where you were, where you are now and where you are planning to be.

It all starts with a purpose

Projects start with challenges to overcome. Artificial Intelligence and Machine Learning initiatives have a purpose because they will help increase customer satisfaction by 25%, automate the reconciliation process so the finance team can support the CFO with more frequent & in-depth reports, reduce risks of hospital acquired complications by half, lower inventory costs… Not because it can beat a human at Go or looks good on a resume.

Some organisations adopted AI and ML for the wrong reasons, or failed because they lacked to clearly articulate the use case correctly.

Like a new high-tech spaceship, BI, CPM or AI technologies only have a meaning when you know your destination and what the steps are to get there.

A double-edged approach

Success can be measured in both quantitative and qualitative measures. Automating the budgeting process might not increase productivity by an expected 20% ratio or dramatically change the outcome from what it was in the past, however, will help your Finance team spend more time on providing better-quality recommendations, prevent them from calling sick or burning out and improve employee retention. Providing high-tech, fancy instant visualisations and nice-looking dashboards, but less flexible than old Excel spreadsheets might actually bring low value to the end-users.

Short term outcomes and low-hanging fruit is tempting, but must also serve long term goals (Some companies still invest in legacy tools to solve immediate issues, which can hinder long-term initiatives) We can also measure value and set priorities by factoring Risk, Cost, Complexity…

Defining clearly your criteria to measure business outcomes and adjusting them constantly is your compass to success (or failure, which, in this case, will help you learn and adapt).


 3- A project is not a one-off

Implementing a new BI platform is like learning a new language: you can only improve and realise how much value you can get out of it. Don’t think it will be over anytime soon: it does not end with the delivery of the initial scope but must build new habits, initiate new projects and raise further questions.

Walk before you run

We all know Apollo 11, but landing on the moon was only made possible because of previous Gemini, Mercury and Apollo missions’ successes, and tragic failures too. (If you like space and lessons of persistence, the Soviet Venera program also speaks for itself…)

Back to the good old motto “Think Big, Start Small, Deliver Quickly”, it is not about technology anymore, it’s about managing change, driving transformation across all parts of the business step by step. And rather than “change” which is a one-time concept, we should switch to a more accurate one: “permanent adaptation”.

It also means no failure is permanent, and not achieving success in the first place does not imply you can’t achieve your goals in the next phase. Preparing for failure is:

  • Taking acceptable risks
  • Monitoring and documenting your journey
  • Learning and adapting from your experience

Don’t be dependent

The relationships between internal and external stakeholders is also a journey. I like to relate it to the dependency cycle of Katherine Symor, later adapted by Vincent Lenhard, where relationships tend to constantly evolve from:

  • A dependence stage: The traditional, old-school BI approach where the business depends on IT or an external third party to provide them with analysis.
  • A counter-dependence stage: Finance, Sales… running their own parallel spreadsheets in reaction to the lack of flexibility and autonomy, without complying to IT processes (Excel)
  • An independence stage: Both processes co-existing separately with no synergy, but it is inefficient and the risk is that this doesn’t meet corporate expectations. Silos still persist.
  • An interdependence stage: IT and the business collaborating and leveraging each-others’ efforts (Self-service BI)
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This means the way you manage internal stakeholders must change over time, but also how you engage with third-parties (vendors, partners, consultants…) from pure technology experts to trusted advisors who know your business/industry and provide value at another level without unhealthy dependence (technical, IP, commercial…).

4- Keep an open mind

Selecting a solution is not a 100% rational process (we’re just humans after all). But it can get close to it.

We could list all cognitive bias we are subject to (Have a look, it’s very insightful and see if you can relate), but let’s focus on the ones we encounter often in a BI/CPM or AI project:

What worked somewhere else might not work here

Starting with the Law of the instrument: “An over-reliance on a familiar tool or methods, ignoring or under-valuing alternative approaches. – If all you have is a hammer, everything looks like a nail.”

What worked in another environment, even very similar, might not always be applicable to the current one. Keeping an open mind means considering alternative solutions with a scientific approach and keeping out from personal bias.

Try before you buy

Would you buy a car without trying it first? (You might, but it’s taking an unnecessary risk)

Technologies are more and more flexible, agile and easy to use. Most vendors offer a trial version and there is no better way to gauge potential value by running a proof of concept.

Not only it will provide a better look and feel of the final outcome, but it is also a good way to evaluate the quality of your interactions with the vendor or partner. The difference between a POC and a full project is merely the size of its scope.

If you need assistance navigating through Data Management, Business intelligence, Corporate Performance Management or AI & ML solutions, please feel free to reach out to us!

Written by Olivier Bastard – Account Executive at AtoBI
Get in touch with Olivier

Patient Experience(PX) is the Strategic Difference in Healthcare Today – are you ready?

In the era of customer centric service, Healthcare organisations must be patient centric. Patient Experience (PX) is now the defining strategic differentiator in Healthcare.

Our world is now heavily focused on convenience and time. This has laid the groundwork for rising customer expectations when it comes to healthcare. The days of patients making appointments that result in weeks of waiting and long waits once they get to their appointment is behind us. To become Patient Centric, Healthcare organisations must first start by defining their PX vision, which must be aligned with the company’s overall strategic goals and objectives. Next, they need to understand who their customers are, which is where a value based care program and a PX measurement framework come into play.

AtoBI are leaders in providing solutions for the Healthcare Industry in Australia. Below are the key questions that Healthcare organisations need to ask themselves to ensure that they are ready to provide a great Patient Experience. These questions will act as a guide to assess your readiness to be Patient Centric.

  • Are you using quantitative and qualitative methods when researching PX?
  • How are you sharing your findings?
  • Do you have a PX vision?
  • Are you defining and refining experiences based on your vision and research-based understanding of patients?
  • Are you providing employees with resources that help them deliver excellent experiences?
  • Are you tracking and analysing the quality of experiences?
  • How are you linking metrics to your organisation’s overall metrics?
  • How are you communicating with internal stakeholders?
  • How do you measure the quality of clinical outcome?
  • How are you creating a system of shared values and behaviors that focus employees on delivering great experiences?

Overwhelmed by these questions? Did you discover that these questions were a challenge for your organisation to answer?

PX vision starts from the top but must be embraced and championed by the entire organisation. This requires a significant culture shift, which will establish a firm foundation for your organisation’s efforts toward a great patient experience. AtoBI as leaders in Healthcare Solutions can help you through this process from the very beginning to implementation. Contact AtoBI today to start your Patient Experience journey info@atobi.com.au.