Innovo

Introduction

Test Data Management (TDM) is essential in software development and testing, ensuring data used in non-production environments is secure, relevant, and compliant with regulations. With the increasing emphasis on data security and privacy, the need to use obfuscated data during testing and development has never been more critical.

Why Use Obfuscated Data?

1. Data Security: Obfuscation transforms sensitive data into a format unreadable to unauthorised users, minimising data breach risks during testing phases.
2. Compliance: Regulations such as GDPR, HIPAA, and CCPA mandate stringent data protection measures. Using actual data in test environments can lead to compliance violations. Obfuscated data helps organisations stay compliant by ensuring that sensitive information is not exposed.
3. Data Integrity: Testing with obfuscated data ensures that data integrity and quality are maintained, helping identify and resolve potential issues without compromising actual data.
4. Risk Mitigation: By using obfuscated data, organisations can reduce the risk of exposing personally identifiable information (PII) and other sensitive data, which could lead to legal and financial repercussions.

The Challenge

Managing and securing test data is complex and challenging. Even major banks, government agencies, and the largest healthcare providers struggle with this. The complexity arises from the vast amounts of data these organisations handle, the intricacies of ensuring data obfuscation without losing data integrity, and the continuous evolution of compliance regulations. The challenge is compounded by the need to automate these processes while maintaining high-security standards.

A Public Safety Concern

This challenge is not just a technical issue but a genuine public safety concern. Most members of the general public and even many in the industry are unaware of how insecure their data can be in test environments. Data breaches in these sectors can lead to significant financial loss, identity theft, and compromised personal information. The stakes are high, and the consequences of non-compliance and data breaches are severe.

Why Innovo?

Innovo is the leading service company in Australia for data securitisation and data uplift programmes. Our expertise in TDM and data obfuscation ensures your data is secure and compliant with the latest regulations. We offer cutting-edge solutions to automate data masking, subset data effectively, and monitor test environments continuously. Our commitment to data security and compliance makes us the best choice for organisations looking to protect sensitive information and mitigate risks associated with data breaches. Innovo partners closely with Enov8 as we believe this is the most comprehensive and cost-effective ROI solution available in the market.

Conclusion

Incorporating TDM and using obfuscated data in testing and development practices is essential for maintaining data security, ensuring compliance with regulations, and mitigating risks associated with data breaches. Organisations prioritising these practices will be better positioned to protect sensitive information and maintain trust with their customers.

Penalties for Non-Compliance with PII Data Regulations in Australia

Australia imposes severe penalties for non-compliance with PII data regulations, including substantial fines, legal actions, and significant reputational damage. Due to the sensitive nature of the data they handle, non-compliance can be particularly damaging for organisations such as banks and healthcare providers. These sectors are under stringent scrutiny to protect PII, and any breach could lead to loss of customer trust, financial losses, and operational disruptions.

For more detailed information, please refer to Australian legal and regulatory resources on data protection.

Pursuing the “Golden Path” in DevOps represents an aspirational journey towards achieving operational excellence. This metaphorical “Paved Road” epitomises a state of DevOps where development and operational processes coexist and thrive in a seamless, efficient, and highly automated ecosystem. The tangible outcomes of this ideal state are manifested through the rapid, reliable, and repeatable delivery of software, positioning organisations to pivot with agility in response to fluctuating market dynamics and the evolving needs of customers.

Embarking on this path is full of challenges, and it demands a strategic blend of cultural evolution, process refinement, technological enhancement, security fortification, and continuous measurement and improvement. Here’s a comprehensive exploration of each step necessary to navigate towards the “Golden Path.”

1. Cultural Transformation

The foundation of DevOps lies within its cultural paradigm – a philosophy predicated on collaboration, transparency, and shared responsibility. The shift towards this culture is often the most formidable hurdle, as it involves dismantling longstanding silos and fostering a milieu of open communication and continuous feedback among all stakeholders, including Development, Operations, Security, and Quality Assurance teams.

Parallel to this is the ethos of embracing a learning mindset. An environment that encourages continuous learning, experimentation, and adaptability is critical. Here, failure is not a setback but a stepping stone to knowledge, and adaptability is the currency of innovation.

2. Process Optimisation

The second cornerstone is streamlining processes through automation. By automating repetitive and manual tasks such as testing, deployments, and monitoring, organisations can drastically reduce human error and augment efficiency. Implementing Continuous Integration and Continuous Deployment (CI/CD) pipelines is central to this strategy. CI/CD facilitates frequent and smaller releases, which are inherently more manageable and can be more readily reverted if necessary.

Feedback loops are also integral to process optimisation. These mechanisms ensure that any issues are promptly identified and rectified, mitigating costs and preventing delays.

3. Technology Stack and Tools

A robust technology stack underpins the DevOps framework. It starts with version control systems, which are the bedrock for effective code change management and collaboration. Configuration management tools follow, ensuring consistency and reliability across different environments by managing server and application configurations.

Comprehensive monitoring and logging are non-negotiable in a mature DevOps environment. They provide visibility into application performance and system health, enabling proactive issue resolution and informed decision-making.

4. Security and Compliance

The incorporation of security practices throughout the DevOps pipeline, often referred to as DevSecOps is indispensable. “Shifting left” on security means embedding security considerations at the start of the software development lifecycle rather than as an afterthought. Compliance automation, or “Compliance as Code,” fortifies this approach by ensuring regulatory and industry standards are met within the CI/CD pipeline.

5. Measurement and Improvement

Metrics and Key Performance Indicators (KPIs) are crucial for tracking progress and identifying areas for enhancement. They provide insights into delivery speed, stability, and quality. The ethos of continuous improvement necessitates regular review and adaptation of processes, tools, and outcomes based on feedback and these metrics.

Challenges

The journey to DevOps maturity is resource-intensive. It demands considerable investment in time and tools to cultivate and sustain the practices necessary for achieving the “Golden Path.” Moreover, developing or acquiring requisite skills within the team can be a formidable challenge, often necessitating extensive training and recruitment. Resistance to change is another significant barrier, with organisational inertia potentially stalling the adoption of DevOps practices and the cultural transformation that underpins it.

The quest for the “Golden Path” in DevOps is intricate and iterative. It requires unwavering commitment, strategic resource allocation, and the agility to adapt continuously. While the path is strewn with challenges, the pursuit is worthwhile. The rewards of enhanced agility, superior quality, and increased efficiency not only justify the efforts but also secure a competitive advantage, ensuring long-term success in a rapidly transforming technological landscape.

Automation is a central component of most organisations’ digital transformation strategy today. While stakeholders at all levels are eager to reap the benefits of automation, synchronising, collaborating, and managing automation across all parallel automation initiatives is a significant challenge. If that sounds familiar, then your next step should be utilising an automation hub to manage the automation pipeline.

The case for business automation

Most business leaders today recognise that business automation, in all of its many forms, is not just a buzzword. In fact, it’s a genuine and influential part of digital transformation that helps businesses be more agile, faster, profitable, and competitive.

For many businesses, robotic process automation (RPA) is the embodiment of the promise of automation. RPA is the process of building, implementing, and deploying software bots that emulate human actions to automate repetitive, manual processes. However, other types of more advanced automation, especially intelligent automation (IA), are also gaining ground.

Most businesses today recognise the potential of automation. At least 53% have already started their RPA journey, and if the current trend continues, RPA adoption will be near-universal within five years. It’s easy to see why top performers in the implementation of RPA have seen a 4x ROI from their RPA investments, while the average business has experienced a ~2x ROI. What’s more, RPA benefits are most commonly felt in challenging yet increasingly vital business areas, such as compliance (38%) and productivity (27%).

It’s no wonder the potential economic impact of knowledge work automation is expected to be $5-7 trillion by 2025.

RPA, and other forms of automation, are vital because they help businesses operate more efficiently and do less with more. It’s estimated that 10-25% of employees spend their time on repetitive computer tasks, while IT departments spend 30% of their time on basic, low-level tasks. As a concrete example, businesses typically pay $5- $25 for manual invoice processing.

That’s a lot of waste in terms of time, money, and human resources. Today, 70-80% of these mundane, rule-based processes can be automated with trivial ease. As you can see, the problem lies less with being able to implement RPA solutions than with identifying the myriad opportunities for automation and managing the automation journey.

The challenge of affecting digital transformation through automation

The main problem for organisations looking to implement automation as part of their digital transformation is how broad it is. Most organisations have tens, if not hundreds, of potential use cases for RPA or other forms of BPA. Some are confined to specific teams or departments, while others are organisation-wide. Others may pertain only to a single enterprise app, while others span an entire tech stack.

There are so many types of business automation that it’s hard to track them all. For example, marketing automation, HR automation, accounting automation, process automation, and manufacturing automation, to name a few.

With so many potential opportunities for automation, the immediate problem is how to find and define automation use cases. This can be particularly challenging in large organisations with complex employee and managerial hierarchies. Understandably, C-suite executives may not be savvy to the immediate automation needs of ground-level manufacturing staff, for example, and vice versa.

So, the first problem to solve is the ability to create automation requests from both a top-down and bottom-up approach.

However, even when you identify a specific use case for automation, that opens up a whole other can of worms:

Where do you begin to implement all of these automation processes? How do you track your progress across all automation processes? How do you make sure all the relevant stakeholders are involved? How do you ensure compliance and collaboration to implement them efficiently and with minimal disruption? And, more importantly, how do you determine whether a specific automation process was successful?

Depending on the organisation’s size, digital maturity, and internal automation expertise, the lack of oversight can be a significant stumbling block on the road to large-scale automation. Clearly, organisations need some platform to centralise and manage the entire automation journey.

What is an automation hub?

The goal of an automation hub is to help streamline and accelerate the adoption of process automation initiatives. It facilitates every step of the journey of adopting a new automated process, from ideation to planning to implementation to validation. It allows all stakeholders, including end users, automation experts, developers, and decision-makers, to collaborate on the automation process.

We’ll cover everything that an automation hub does in-depth below, but it broadly consists of three main facets:

• Collaborative process identification
• Automation pipeline management
• Process repository tools

In a way, these tools and features allow the automation of the automation adoption process. As the name suggests, it’s a one-stop, centralised, collaborative “hub” for managing all automation processes. It’s a single point of contact between all individuals involved in creating and using new automation initiatives. This includes business users (e.g., employees), developers, project managers, CoE (Center of Excellence) teams, and automation experts.

What does an automation hub do?

By looking at its actual capabilities, it may be easier to understand precisely what an automation hub does. While the range and depth of capabilities may differ from vendor to vendor and system to system, they generally offer the following essentials:

• Process Identification: Allows users (managers, employees, dedicated automation staff) to share ideas or requests for automation via a collaborative process.

• Pipeline Management: Map the entire roadmap and plan for a specific automation process. Define the expected cost, lead time, and benefits and track its progress in a single dashboard.

• Process & Documentation Bank: Store all documents and assets related to a specific automation process candidate in a single, centralised repository.

• Integration with Task Capture: Task capture tools streamline and improve communication between your automation experts and RPA developers. Automation or subject matter experts can specify best practices and suggestions as a process definition document or workflow diagram for developers to implement.

• Marketplace: Establish an organisation-wide marketplace of reusable components in a private repository. Users can create, store, find, and install components on an as-needed basis at any place, any time, anywhere.

• Gamified RPA Change Management: Support and motivate team members through the automation process using long-term engagement strategies. Clearly track progress and keep the focus on the next and most important milestones in the automation journey. Some gamification systems go as far as to allow you to implement points, badges, or ranking systems.

One important facet of most automation hub systems is that they encourage and facilitate collaboration through every step of the process. Users can share automation requests or ideas, action them, and provide feedback through voting systems or open-ended feedback mechanisms. The automation hub also maintains a single source of truth for all assets and information related to the automation process so that everyone is on the same page.

What are the benefits of an automation hub?

Everyone involved in the use, implementation, deployment, or effects of automated processes stands to benefit from the use of automation hubs:

• Business users:
  • Discover, submit, and collaborate on automation ideas
  • Manage automation opportunities in one place
  • Share subject matter expertise to inform the automation process
  • Increase ROI with automation process prioritisation
  • Maximise the impact of internally developed automations
  • Leverage existing automations

• CoE (Center of Excellence) leaders:
  • Identify what to automate as well as why, when, and how to automate it
  • Manage automation process pipelines
  • Ensure that automation is successful according to pre-determined metrics
  • Prove the positive impact of automation to leadership

• Citizen developers:
  • Build automation with clear specifications in mind
  • Easily build and share personal time-saving automations
  • Ensure that you build CoE-approved automations
  • Easily kick off, manage, collaborate on, and deploy automation projects

The net result will be fewer headaches for your organisation when implementing automation initiatives. Not to mention deploying automation solutions that are fit for purpose and meet the objectives of your boots-on-the-ground employees and high-level decision-makers.

One of the greatest benefits of an Automation hub is the capability to store and re-use assets. Whilst this especially beneficial for multi stream test activities such as regression testing across multiple teams/projects, further benefit and efficiency gains can be obtained through the re-use of these assets in areas outside of traditional test activities.

These can include Robotic Process Automation (RPA), DevOps and environment operations, data generation and validation, and standards conformance validation to name some examples. The ability to store and re-use these assets can contribute to not only overall effort reduction but lead to significant cost savings as well as quality increase through standardisation. In addition, the storage of such assets can also enable greater velocity, in effect providing a mechanism enabling a ‘test on demand’ function.

The test automation tools market to date has been focussed on test automation in isolation, however with greater emphasis being placed on interoperability and re-use of assets to drive automation as an outcome, tools vendors are researching and developing mechanisms to enable holistic automation capabilities.

Traditionally this has been focussed at the integration layer, enabling diverse tools to ‘talk’ to each other, however UiPath (a recognised leader in RPA) has taken this further by focussing on Intelligent Automation as a whole of business enabler.

This has led to the market leading development of an integrated tool suite that enables Automation hubs to develop and share assets across activity streams – whether that is RPA, testing, or other forms of intelligent automation such as Intelligent Document Processing, Process mining and Task Capture. As UiPath state, ““Bill Gates used to talk at Microsoft about a computer in every home. I want a robot for every person.” Daniel Dines, CEO

Organisation Automation Potential

While the potential of implementing organisation-wide automation is nearly infinite, substantial obstacles exist. The best way to improve your chances of success is to rely on a proven digital transformation partner with experience in automation. This is especially true if you want to take automation to the next level by evolving toward intelligent automation.

If you are interested in learning more about our Intelligent Automation services, contact us for more information.

Businesses are always looking for ways to become more scalable, agile, productive, and competitive in a rapidly-evolving landscape. AI and automation have long been effective strategies to achieve those goals in the tech-savvy business playbook. However, treating them as separate entities limits their benefits to specific silos in the business. Businesses can achieve holistic improvements at every level by combining them and leveraging the power of intelligent business process automation. It’s no wonder that the Intelligent Process Automation market is expected to grow from $13.6 billion in 2022 to $25.9 billion in 2027.

Is automation part of digital transformation?

In short, yes. Automation is a core component of digital transformation. In fact, for many businesses, automation is the first and most vital component with the potential to impact everyday business operations positively. Automation also allows firms to extract more value from sophisticated digital transformation technologies, like AI, machine learning, and the cloud.

There are many different types of automation with varying degrees of sophistication. RPA (robotic process automation) is one of the most popular today. RPA automates repetitive and mundane tasks, such as invoice processing, onboarding, or data processing. Automating these processes is more efficient, frees employees to focus on strategic tasks, and eliminates errors.

RPA typically relies on “bots,” specialised software systems developed to solve specific human tasks. While it’s similar, RPA is distinct from BPA in several ways. BPA, or Business Process Automation, is another sub-field of automation that we’ll discuss further below.

Many other forms of automation are used in businesses today that permeate almost every department, task, or business process. For example, task automation, marketing automation, process automation, integration automation, AI automation, and more.

What are the main benefits of automation?

As mentioned, automation is a broad field. Different automation applications will lead to varying benefits for specific businesses, teams, departments, or stakeholders. However, in general, you can expect the following benefits from utilising automation:

• Lower operating costs
• Improved worker safety
• Smaller lead times
• Faster ROIs
• Increased productivity or output
• Improved quality of products and services
• Reduced employee burnout and higher happiness
• Maximising your employees’ potential
• Better adherence to governance and compliance
• Improved service reliability and consistency

In general, automation allows businesses to do more with less by eliminating the need for superfluous manual work. That means that employees have more time and energy to spend on strategic problem-solving and core business functions. Automated software systems can also execute certain tasks with greater speed, accuracy, and scalability than humans. For example, automated provisioning or manufacturing systems can run 24/7, not just within business hours.

What is business process automation?

Business process automation uses automation technology to complete business processes with minimal human intervention. It’s distinct from task or RPA automation because it’s not focused solely on a single task, team, or department. Business processes can span multiple departments through complex workflows that achieve a particular business goal.

For example, BPA can involve the end-to-end process of creating and releasing a new product. In this case, as soon as the product team comes up with a new idea, they can kick off a process that sends the idea to marketing or management for approval. From there, the system will automatically initiate a new development project and inform the relevant parties. The process can then go through a complex series of development -> test -> feedback -> rework according to the business’ production lifecycle.

BPA is also used in applications for HR and employee onboarding, marketing customer onboarding, and IT and technical support. Many of these processes rely on routing documents or approval steps through multiple steps in a pre-defined workflow. In turn, BPA can kick off and rely on multiple RPA systems that handle specific tasks along the way.

What are the benefits of business process automation?

The benefits of business process automation are similar to those of automation in general. However, there is a greater focus on standardising key business process that simplifies and streamlines complex internal workflows. The benefits may be harder to quantify directly because they improve the organisation’s overall efficiency instead of improving metrics for a specific task.

That being said, here are some of the key benefits of implementing business process automation:

• Saving time
• Increased profits
• Higher productivity
• Improved efficiency
• Minimising occurrence of errors
• Improved governance and compliance through standardisation
• Improved internal auditing
• Enhanced customer experiences
• Scalability

What is intelligence process automation?

Intelligent process automation (IPA) involves integrating multiple technologies to automate complete, end-to-end business processes. In some ways, it combines RPA and BPA with another distinct AI field, called intelligent automation (IA).

IA combines automation (RPA, BPA) with intelligence-based technologies, like AI and machine learning. Today, IA is also evolving to span cutting-edge AI fields, such as natural language processing and computer vision, to execute more sophisticated and specialised tasks. IPA goes one process further by applying IA to end-to-end business processes, as discussed above under BPA.

To see why intelligent business process automation is needed, let’s look at a typical invoice processing example. It’s easy to imagine a BPA workflow that eventually routes an incoming invoice through the relevant parties to authorise a payment. However, at some point, someone will still need to manually review the invoice for compliance and ensure it’s error-free.

An intelligent business process automation system would include an intelligence-driven system capable of automating the invoice checking process. So, a business would enjoy the benefits of both a conventional BPA solution as well as an AI solution.

In a way, IPA represents what’s currently the peak of combining intelligence with automation to improve business value. It brings together many different components, including:

• Artificial intelligence: Complex algorithms combined with machine learning to analyse data, predict outcomes and accelerate decision-making.
• Business process management: Automating workflows to improve efficiency, standardisation, flexibility, and scalability within an organisation.
• RPA: The use of specialised software tools to complete back-office tasks in an efficient and scalable way.

Applications for IA exist in nearly every industry or business. However, it’s currently being heavily implemented in fields such as automotive manufacturing, healthcare, and insurance.

What are the benefits of intelligent automation for businesses?

In some way, IPA has the potential to deliver the benefits of AI and automation at every level of the business. From mundane, repetitive back-office tasks to company-wide processes that involve logistics, everyday operations, production, and service delivery. With that in mind, here are the benefits of intelligent business process automation:

• Increased ROI: The combination of automation and IA allows businesses to scale production without negatively impacting quality or risk. Complex rule-based systems ensure compliance and accuracy, reducing the need for internal auditing of systems and processes. In short, this equals a higher yield while investing less time, money, and resources.
• Accurate decision-making: AI is maturing rapidly and is capable of increasingly complex decision-making in shorter timeframes and with less chance of error than humans. Combined with machine learning, AI systems can improve accuracy over time without manual intervention. The scalability of the cloud has the potential to exponentially increase businesses’ computing capabilities, allowing companies to get more value from their data faster. 
• Enhanced customer experiences: Endpoint AI can deliver the advantages of intelligent computing to customers and clients from close proximity. By bringing down lead times and increasing an organisation’s ability to analyse complex behavioural data, companies can also deliver more valuable and relevant products in less time.
• Compliance and governance: Due to regulatory pressures and heightened public awareness, businesses are under more pressure than ever to enforce proper compliance and governance, especially concerning sensitive data. However, it’s also becoming more important from a productivity standpoint as processes and technologies become more complex. AI has the ability to apply governance and compliance measures consistently without sacrificing efficiency.

According to a study by McKinsey, companies that implement IPA experience some pretty radical results:

• The ability to automate 50 to 70% of all tasks,
• Translating to annual run-rate cost efficiency by 30 to 35%,
• Reducing straight-through processing times by 50 to 60%,
• Leading to triple-digit returns on investments.

Conclusion

So, is intelligent automation necessary for digital transformation? Both the short and the long answer to this question is yes.

In one stroke, intelligent business process automation allows businesses to eliminate the inefficiencies associated with replicable, routine tasks as well as streamline and optimise their core business processes.

It’s quickly supplanting its predecessors, AI, RPA, BPA, and IA, as the way for businesses to revolutionise their operations by eliminating inefficiencies, attaining scalability and agility, driving customer value, and out-pacing their competitors.

The only catch is that implementing widespread IA at every level of business can be a real challenge. Many organisations don’t have the specialised AI expertise required to pull off this kind of digital transformation while addressing the business’ chief challenges and objectives.

Enlisting the assistance of an expert intelligent automation service provider, like Innovotech, will benefit a forward-looking business through accelerated uptake and a smooth implementation process. Not to mention consistent and goal-oriented outcomes thanks to the high-quality design & delivery solutions.

Regardless of what vertical or the scale businesses operate in, they are always looking for ways to be leaner and more efficient. The art of producing more from less is the key to unlocking innovation, agility, scalability, and the ability to provide more value from the same products and services.

Automation has long been a goal of businesses looking to save costs, increase productivity, and accelerate growth. Where past efforts have focused on industrial automation, we have now well and truly entered the age of intelligent automation.

Today, automation is not only imperative in low-level applications but also for a company’s overall high-level strategic goals. Intelligent automation enables businesses to achieve greater levels of excellence by improving their decision-making, speed-to-market, customer experiences, and the capabilities of their employees.

The five components of intelligent automation influence every facet of the business:

• Artificial Intelligence (AI)
• Robotic Process Automation (RPA)
• Business Process Management (BPM)
• Tools, and
• Data

Below, we’ll discuss precisely the five components of IA and how Intelligent Automation can help businesses adapt.

What is Intelligent Automation?

Not to be confused with artificial intelligence (AI), intelligent automation (IA) combines cutting-edge technologies to automate low-level tasks within a business context.

However, IA relies heavily on AI-based technologies, such as Machine Learning, Natural Language Processing, Structured Data Interaction, Intelligent document processing, and RPA. Because it relies on AI, IA is also sometimes called cognitive intelligence.

Businesses across various industries benefit from intelligent automation, including banking, finance, insurance, utilities, and more. IA is a vital thread of a larger digital transformation strategy for many businesses today.

IA systems can be as simple as intelligent chatbots or as complex as provisioning engines that commission/de-commission virtual environments on-the-fly based on real-time workload data.

Note that we’re focusing on Intelligent Automation here as a distinct discipline from robotic process automation (RPA) or hyper-automation. We’ll cover the details of how they differ in-depth in future articles.

For now, it’s enough to know that RPA is a sub-field of IA, alongside artificial intelligence and machine learning. Hyper-automation, on the other hand, is concerned with automating as many business and IT processes as possible. So, IA can be used to achieve hyper-automation of a company.

Hyper-automation holistically tackles the challenge of automation by also looking at it from a human and business process perspective, while IA is concerned chiefly with the implementation of automation technologies.

What are the Benefits of Intelligent Automation?

When intelligent automation is appropriately implemented, its benefits are felt across every area and level of the business. At its core, intelligent automation empowers your human resources with smart technologies and agile processes to make faster and more informed decisions.

• Reduce operational costs: According to KPMG, IA can help financial organisations cut costs by as much as 75%. Roland Berger found that companies implementing IA could save up to 40% annually and reduce the time spent on processes by 40-70%. IA technologies help optimise processes so that they can be scaled for smaller teams or more clients.
• Save time: Optimised and automated processes require less manual human interaction to function. RPA can also be used to completely automate specific repetitive, back-office tasks to free up employees to solve more strategic problems.
• Reduce the impact of human error: Repetitive, high-volume tasks create prime conditions for human errors to pop up. Human error is also especially prevalent in production and invoicing, two critical areas. Automated, rule-based processes eliminate human error risk while strictly enforcing built-in governance and compliance measures.
• Maximising the value of business data: IBM estimates that bad data costs individual businesses $9.7 million annually, costing the economy $3 trillion in total. IA has the potential to help companies to improve how they collect, process, store, reconcile, and analyse their data.
• Improving customer experience: Collectively, IA technologies enhance customer experiences by improving speed to market and allowing businesses to improve their products and services by better understanding their customers. High customer satisfaction means higher retention rates which means growth.

With a longer-term strategy in place, IA also holds potential benefits for employee morale, innovation, fraud monitoring and detection, and even cybersecurity.

The Five Components of Intelligent Automation

Now that we have a grasp on the role that IA plays in modern-day business let’s look at the nuts and bolts. Each company may (and should) have a tailored intelligent automation strategy that prioritises components based on their unique circumstances. However, these are the core five elements that make up a holistic approach to intelligent automation:

Artificial Intelligence

Businesses want to make better decisions, based on more information, within less time and with high accuracy. There is no better candidate to achieve that goal than through the use of Artificial Intelligence or AI. You can think of artificial intelligence as the brain and beating heart behind intelligent automation.

So, in this context, AI is concerned with tasks that are cognitive in nature, such as Optical Character Recognition (OCR), Natural Language Processing (NLP), Machine Learning (ML), and Intelligent Character Recognition (ICR)

AI is the cornerstone of scaling and extracting the maximum value from intelligent automation in a business. By combining complex algorithms with machine learning, companies can efficiently analyse structured and unstructured data at previously impossible scales.

As AI matures, it will be used to process data in increasingly complex and efficient ways. The result is more valuable, actionable, and timely access to information decision-makers can use. This is often what’s referred to as the AI “decision engine.”

Over time, this allows businesses to develop a knowledge base that can be a valuable resource for understanding past events and making future predictions. And, to produce formulas for accelerating the decision-making process even further.

AI is also not a one-trick pony but can be utilised within individual processes, teams, departments, or an entire organisation. AI not only has the potential to revolutionise business processes but also to improve the quality of life and productivity of employees and the value provided via customer experiences.

Robotic Process Automation (RPA)

If AI is the mind, then robotic process automation, or RPA, is the body. Unlike AI that’s primarily concerned with cognitive processes, RPA is involved with the automation of repetitive, rule-based processes. At a low-level, RPA bots are adept at mimicking human interaction.

RPA mostly takes the form of software robots, or bots, that are capable of carrying out back-office tasks. Think of high-volume, time-consuming processes that require little critical thinking. For example, data scraping, compliance reporting, customer order processing, claims administration, or scheduling systems.

To see why RPA is necessary, you only need to know that 50% of companies spend up to $25 per manually processed invoice. And that sales reps spend up to 64% of their time on non-revenue generating tasks.

The more cognitively demanding tasks are for humans or AI. However, they can be combined with AI or human resources to considerably scale up the completion of more complex tasks.

The main goal is to free up employees from having to deal with tasks that don’t require human-level intelligence. So, employees can use their time and decision-making capabilities where needed most. For example, where there’s a need for strategy, creativity, and innovation.

Because of the relative simplicity of these bots and the operations they are tasked with, they can be implemented relatively quickly and easily. RPA can also rapidly be scaled across projects, processes, or teams.

As a result, the ROI for implementing RPA can be quite high. According to the institute for RPA, businesses stand to enjoy immediate cost savings of between 25-50%. It’s no wonder that 20% of organisations adopted RPA by 2021.

Business Process Management (BPM)

In an effort to save cost, time, and effort, businesses are moving toward adopting the principles of Lean Programming. This involves an in-depth process of re-examining all business processes as well as their sub-routines and tasks. Not to mention how, when, and why humans are involved with various business processes.

Through this process, the performance, as well as the positive and negative contributors to said performance, are identified. The processes are then stripped of any redundancies or inefficiencies, and unnecessary human participation is replaced with AI or RPA. So, in the era of IA, business process management is also often referred to as “workflow automation” or “business process automation.”

The end goal is to limit time spent on non-value-adding activities and improve the efficiency and accuracy of essential processes. That’s especially true for processes involved in production or service delivery.

Aside from making employees more efficient, optimised business processes can also improve customer-facing experiences and increase the speed of business.

It’s estimated that inefficiencies cost companies between 20-30% of their annual revenue each year. So, this is one area that can yield massive results.

Tools

Companies look to specific technology solutions to solve challenges or address inefficiencies. Third-party tooling can offer cost-effective and high-ROI solutions on an as-needed basis.

That is particularly true as SaaS platforms and endpoint software are becoming increasingly advanced in terms of AI, machine learning, and automation.

However, companies must be careful about what tools they adopt and how they integrate them into their operations. Unconsciously adopting tools without thinking of the whole picture can leave independent teams operating disjointedly.

The company’s overall technology ecosystem can become siloed according to specific business functions. That can lead to company-wide visibility, data sharing, and collaboration problems. At some point, an overall technology strategy will be needed to ensure you maintain coherence across all your teams, systems, and processes.

That being said, tooling can result in some quick wins for businesses looking to make inroads into intelligent automation.

Data

Data is playing an increasingly important role in the success of organisations. It determines a business’ ability to strategise, make snap decisions, adjust to emerging trends, and offer value to its customers.

In fact, statistics show that data-driven businesses are 23x more likely to retain customers and increase their profits by up to 8%. What’s more, it has the potential to help companies to grow by better understanding their customers.

It’s no exaggeration to say that for many businesses, their data IS the business.

In the lifecycle of intelligent automation, data is what feeds all the other components. It’s used, consumed and processed using RPA and AI software. It’s also internal data regarding performance and other metrics that drive the acquisition of tooling as well as the optimisation of business processes.

As such, data collection tends to be constant and large-scale. Compliance and governance measures also need to be in place to ensure the data supply chain is transparent, trustworthy, and accessible. Automation and intelligent data handling are required to ensure businesses can extract value from their data efficiently, accurately, and within reasonable timeframes.

This creates a loop where AI, smart/predictive analytics, and automation can be used to scale data operations. At the same time, the enhanced data can be used to further AI systems through machine learning and further optimise business operations.

Conclusion

While we can talk about the individual components of intelligent automation as distinct concepts, they all have the same overarching goal. That is to help businesses foster greater efficiency, consistency, and productivity while saving costs and time and freeing up a company’s cognitive resources to focus on more strategic challenges.

As an immediate and short-term goal, IA will help businesses achieve bottom-line and top-line growth. Going forward, IA will also play a pivotal role in companies being able to outmaneuver competitors or industry disruptors.

If you haven’t done so, the best time to assess your business’ IA maturity and develop your own IA strategy is now.

Sydney start-up Innovo has won a race against time to enable 21 small Australian banks to become compliant with the country’s new Open Banking rules.

The DevOps and digital development specialist was tasked with bringing the institutions in line with regulations of the Australian Competition and Consumer Commission’s (ACCC) Consumer Data Right (CDR) rules before the deadline of 1 November.

Essentially, the rules cover the sharing of product reference data between banks in a standardised format to facilitate better product comparisons, according to the ACCC.

The 21 banks banded together to enlist Innovo after discovering the software platform provided for building out CDR capabilities was lacking a robust testing system to prove regulatory compliance.

For each individual bank to develop their own testing solution, it would be expensive, time-consuming, and potentially add risks.

Having missed the Phase One deadline of 1 July, the 21 banks had just four months to build their own testing software in order to meet the second phase deadline of 1 November.

Speaking to ARN, Innovo director Harold Bult explained that the challenge was to create a “smart solution” that would allow all the banks to test the platform independently, avoiding the time-consuming and manual processes that had hampered the Big Four banks in their initial testing phase last year.

“We used the test cases that the ACCC has put on their website and built them into an automated test solution that gives the banks the ability to run those tests in a relatively short time window,” he said.

In total, more than 90 people, mostly based off-shore, worked on the project, providing coding and development of the scripts.

The software solution is hosted on Amazon Web Services’ (AWS) EC2 and uses AWS Control Tower to manage multiple accounts.

Future operations will utilise additional AWS native services, leveraging both the cloud provider and the capabilities of AWS Premier Consulting partner Blazeclan.

Although the testing task may have seemed easier when completed with the first few banks, the Innovo team soon ran into difficulties when bringing the rest on board.

“In theory, everyone was thinking if it works for the two early adopters, then it will also work for the rest,” Bult said. “But it seemed a bit more complex than that, mostly from a coding perspective.

“We saw that the code is quite stable across the banks but needed to resolve varying configuration. Each bank has slightly different specific customisations in their environment.”

Bank of Victoria was one of the institutions to recently cross over the line and complete a successful test ahead of the November deadline.

Speaking to ARN, Bank of Victoria CIO Scott Wall explained that while the legislation of data sharing will be a “massive cost” to the company, the completion of the testing will enable them to start reaping some of the benefits.

“Now we can receive that data, which will probably be next year,” he said. “Then we can start developing new products and services ourselves.”

“Innovo was an untested partner for us,” he added. “But we signed up with them as they had a very clear-cut project plan, and they’ve certainly delivered. We’re very positive about that relationship and it was very collaborative.”

According to Innovo managing director Nick Finlayson, the testing solution will now be made available on AWS’ Marketplace, with potential for customers from across utilities to telecommunications to leverage it for their own CDR needs.

As of 1 November, all 21 banks have now passed the testing stage and can go live with their CDR capabilities, Finlayson told ARN.

“We shared the knowledge openly and did what was right for open banking and the CDR industry,” he added. “We spent over $1 million to build the solution just in development costs and yet we shared that, and each bank paid less than 10 percent of that to get the product and full compliance. We ensured they all got across the line. It was a true vendor and industry partnership.”

Eleanor Dickinson (ARN)

Sydney, 28^th April 2021 – Blazeclan and Innovo, two leaders in consulting, technology services and digital transformation have formed a strategic alliance to take on the Australian IT services sector. With a core focus on delivering best-of-breed cloud enablement, technology integration and testing with a competitive pricing model, the partnership aims to usurp competitors in the sector.

The burgeoning cloud adoption market in Australia is powering businesses to add an extra $9.4 billion dollars to the economy with 45% of businesses in Australia using paid cloud technology. Enterprises increasingly need advanced digitisation to ensure their operations and competitiveness in a post-pandemic world, something that is facilitated by cloud technology.

The strategic alliance is spearheaded by ex-Capgemini heavyweights; Amit Bassi (Managing Director of Blazeclan ANZ), Nick Finlayson (Executive Director of Innovo Technology) and Paul Thorley (Chair of the Blazeclan/Innovo Strategic Alliance) who saw an opportunity to challenge the industry and take key market share from the major systems integrators.

“Australia’s adoption of cloud technology and services has been relatively slow compared to the rest of Asia Pacific. We’ve found that current cloud service providers are slow to implement, exorbitantly costly and miss the mark on building cloud cybersecurity resiliency,” says Nick Finlayson.

With a number of joint major customers including ANZ Bank, ACCC and Latitude Financial, the strategic alliance has proven to offer a different outcome to the status quo.

“Cloud services are defining new business models, facilitating a more innovative and dynamic way of driving digital experience, and are unlocking the next wave of modernisation,” comments Amit Bassi.

“We saw a huge opportunity to offer an end-to-end cloud enabled digital transformation service that starts from strategy through to agile delivery using the same one local team. This, in turn allows the customer to shift to a more dynamic and responsive way of running their business. We do this in a bespoke way, with one localised onshore team that is supported by an offshore team to take on enterprise sized projects, with a 24/7 operations.”

The strategic alliance will draw on the engineering manpower of over 500 technical experts located in Sydney, Melbourne, Auckland and Pune. Through the alliance, the team will also  tap into the collective expertise of subject matter experts in France, Belgium, North America and Canada to deliver advisory, engineering, assurance and managed services for digital, cloud and data platforms.

At their disposal will also be extensive partnerships and expertise on AWS, Google Cloud Platform (GCP) and Azure that will support enterprise customers to build a cloud solution that adheres to data sovereignty compliances in the respective countries.

“Getting fast access to best-of-breed cloud solutions from the likes of AWS – of which Blazeclan is one of Asia Pacific’s most successful consulting partner – is a must-have for our customers,” comments Paul Thorley.

“We’re thrilled to, once again, be leading with a powerhouse alliance and cloud services offering that enables our customers to power to new heights.” He concludes.

Over the last six months, and with the challenges of activities during the covid period notwithstanding, Innovo has experienced a marked uptick in our client partners drive to innovate and reap the benefits of Digital Transformation and Cloud Migration.

Through these activities, we have identified that there are significant benefits in a focus on one of the key pillars of Digital Transformation – Tech Simplification.

The majority of businesses we have been fortunate to assist with have common challenges associated with their current state technology ecosystems; primarily related to overly complex IT systems and ecosystems that have developed organically over time:

• multiple variations
• multiple configurations
• complex customisations beyond configuration
• loss of technical knowledge and IP of time
• multiple ‘like’ application sharing redundant/common functionality (e.g. communication, collaboration etc)
• end of life technologies

The reason behind this increase in technical complexity are many and varied, but the common elements usually are related to:

• a result of decisions around shifting business priorities
• immediate need vs strategic view
• governance or budget compromises
• changes (customisation etc) to meet specific business needs and outcomes
• increasing integration size as more applications and systems are implemented
• lack of structure decommission analysis and implementation paths

Interestingly, complexity awareness within an organisation is usually greatest with IT streams, noting that there is little business awareness of these complex issues. However, once the business responsible areas of an organisation to become aware (for multiple reasons), these organisations generally look to Digital Transformation as a mechanism to try to stay relevant usually via:

• new technology acquisition (increasing cost effect and complexity), or
• look to simplify across people, process & tools (technical simplification and cost reduction)
• Note: at Innovo we see that both elements mentioned above can be valid when approached holistically, with a strong IT simplification strategy and related plans in place

Speaking specifically to technical simplification, the key goals are to reduce cost, increase agility, reduces complexity, and enable ease of change. When considering tech simplification, several elements need to be considered:

Identify the Tech simplification drivers for your organisation, and develop plans accordingly:

• Increase focus on business and client outcomes
• Minimise change impacts
• Increase transparency of technology complexity and technical debt, across whole or organisation
• Increase productivity
• Reduce duplication/multi redundancy costs (e.g. identifying and reducing the number of collaboration/communication tools/systems etc)
• Improve BI/analytics and metrics measurement
• Improve agility & innovation
• Minimise costs across operations, change events, personnel, technology costs

Once you have identified what your goals and drivers are, what should you do?:

• Baseline your current technical ecosystem – undertake a baselining assessment, utilising well understood and structured techniques and methods. e.g. 6R assessment (Rehost, Re platform, Refactor/Rearchitect, Repurchase, Retire, Retain)

• Focus on a top-down driven, future goals and vision centric, holistic approach:
  • Organisational strategy, people/process/technology, invest in more than technology (e.g. focus on capability increase across people/process/technology)
  • Make simplification a mantra, enable processes whereby simplification is a key consideration for all future change decisions
  • Beware of inherent bias – asking the people who are invested in a specific technology or process to suddenly adapt and change can be problematic, leverage partners/independents
• Baseline TCO, apply ROI for all considerations:
  • Be mindful of cost out first’ vs ‘strategic enablement’ – sometimes need to increase initial spending/increase ROI term is required to meet your future vision
  • Be mindful of existing contractual relationship, in particular, multi-year with termination/penalty clauses…identify these up front!
• Focus on transformation as a journey, not a one-off. Build-in continuous evaluation
• Drive collaboration & culture, do not just focus on technical change in isolation

At Innovo, we take great pride in having assisted our client partners in achieving their Digital Transformation, and specifically their technical simplification goals. We would invite any organisation that is interested in knowing more about this subject and interested in embarking on this journey to reach out to us to organise a time to discuss.

With the prevalence of available agile methods and techniques, increasing numbers of organisations are looking to adopt agility into their work practices – a trend that has been increasing over the last several years, and as reported in publications including the World Quality Report.

With this, there are obvious and apparent challenges being observed, not least of which is the apparent increase in hybridisation approaches – a confluency of waterfall whole of organisation with incremental introduction of agile practices. Whilst this may appear to be a ‘best way forward’ approach to transition, in particular for larger organisations, without careful planning and executive-level (i.e. top-down) stakeholder commitment to whole of business change, what you can end up with is the worst of both worlds.

One major area of concern that Innovo consistent observes is the prevalence of misconceptions around agility and perceived benefits. Agile, for better or worse, has now become a marketable (and therefor a marketing and selling) term, with corresponding issues with the substance of what is actually being offered. The term ‘Agile’ has almost become a doctrinarian term, sparking arguments between methods and models in absence of underlying analysis of best fit and needs for an organisation.

The lack of in-depth understanding of Agile, and the prevalent misconceptions on what Agile is, does, and delivers, can lead to significant impacts.

Putting aside the minutiae of process activities, Agile at its heart needs to be thought of as a different approach to delivering organisational outcomes. A few points to note include:

· You still need to plan and document – planning is critical to Agile; the primary difference in the Agile approach is for less ‘up-front’ plans and documents, and increased focus on incremental

· Agile is not inherently “faster” than other methods per se – however, you can obtain an increased velocity through its utilisation of continuous communication & feedback loops…in effect being more efficient

· Agile can be utilised for more than just I.T.

· A major mindset change is required in adjusting from traditional top-down command & control structures to that of Agile self-organisation…getting the balance right on this is critical for Agile success

· Get help. Really! When considering embarking on Agile you need to be aware of the effects this will have for the whole of your organisation. This needs to be planned just like any major transformational exercise and having partners who have undertaken this before successfully can make all the difference to the level of Agile adoption success.

Sydney, June 10^th   Innovo Technology Solutions, a testing and software development consultancy, has today announced its exclusive release of their CDR Conformance Platform (CCP) in advance of the Product Reference Data go-live implementation of the Australian CDR rules and standards. The tool, a fully automated conformance platform allows banks and Third-Party Providers (TPPs) to quickly verify its APIs and other requirements are Open Banking and CDR compliant with the published rules and standards as defined by ACCC, Data61 and the Australian legislation. Innovo’s platform facilitates fast-tracking the launch of open banking services for both Product Reference Data (PRD) and Consumer data. For all ADIs, PRD is mandated to go-live in 3 phases commencing 1 November 2020.  Consumer data is scheduled to go-live in 2 phases commencing  1 July 2021.

With an architecture that supports both Data Holders and Data Recipients via its virtual banking module, test harness, api library and conformance reporting module, CCP can be configured to support Open Banking and other industry verticals when mandated in future legislation.

CCP enables automation and customisation of the end to end testing process, thereby creating a conformance validation for current and future scopes, regulations and standards.  Complete with its conformance reporting , and dashboards, the platform coupled with the Innovo service affords banks a cost effective and significant accelerator to meeting its compliance obligations.

The Innovo CCP supports conformance validation in-line with the ACCC rules for Consumer Data Rights and Open banking . Legislated in 2018, the Consumer Data Right is designed to give consumers the right to safely access data about them, held by businesses, and direct this information be transferred to trusted third parties of their choice. It will first be adopted in financial services where it is known as open banking.

The Innovo team is at work already incorporating additional industry verticals and evolving standards into the API library, including upcoming legislation  to include the Telco, Utility and Healthcare sectors. Fully customisable and user-friendly, the tool enables technology teams to quickly test APIs in-line with CDR legislation, specific needs, and business requirements.

“Simply put, any organisation who participates in the Open Banking ecosystem is obliged to comply and must prove that they meet the standards” comments Nick Finlayson, founder of Innovo.

“Realising and assuring ongoing industry compliance can be costly and time consuming. Harnessing the power of the Innovo CCP platform, we will enable stakeholders to deliver proof of compliance quickly and cost-effectively for the present and future requirements.  This is a significant enablement tool for banks and participating 3^rd Parties  to meet accreditation criteria under the ACCC mandates. ”

With a team of over 50 technology specialists across Australia and overseas, the Innovo team has facilitated major advances in software development and testing across multiple verticals. The team develops and incorporates the latest and most innovative technology in their projects, leveraging its DevOps methodology and agile practises.

ABOUT INNOVO TECHNOLOGY SOLUTIONS:

Innovo has increased its presence in the software development and testing industry across Australia and New Zealand since early 2015 with a focus on providing best-of-breed technology delivered by expert Testing, DevOps and IT consultancy professionals. Innovo’s people bring deep sector-focused knowledge to client projects, to help them mitigate risks, lower total cost of operations and open up revenue streams out of their technology investments. Innovo’s agile methodologies and technology partnerships can connect customers to provide on-demand technology solutions with deep expertise and trusted delivery.

www.innovotech.com