Innovo

As any CIO, CTO, or technology-conscientious business leader is aware; digital transformation has been one of the chief driving forces behind organisational change for the last decade or more. In fact, you’re probably one of the 70% of organisations with a digital transformation strategy or are actively developing one. The drive to remain competitive and stay ahead has reached fever-pitch, with businesses spending $1.5 trillion in digital transformation in 2021.

However, as businesses go deeper and deeper down the rabbit hole, they are beginning to realise that simply investing in the technologies of the day is not enough. To get the maximum benefits from their efforts, businesses need to ensure these technologies are aligned with and explicitly enable their core objectives and future vision. This is where the concept of “business transformation” or “digital business transformation comes in.”

In this article, we’ll explore the different digital and business transformation concepts and how you can prepare your organisation for a total digital business transformation.

What is Digital Transformation?

Digital transformation is the integration of technologies into various areas of the business. Overall, the objective is to improve how you go about your daily operations, whether it’s being more productive, delivering more value to customers, or achieving smarter and more accurate decision-making.

Most business leaders today already realise the importance of digital transformation. It’s the key to continuous improvement, innovation, and competitiveness in an ever-evolving landscape. After all, the importance of digital transformation is hammered home in any business-IT-related seminar, workshop, keynote address, webinar, and podcast. From small, family-owned, brick-and-mortar businesses to border-defying enterprises, digital transformation is imperative for any business today.

When planning a digital transformation, businesses typically start with a “why” statement, such as:

• Reducing friction within or between business processes
• Eliminating hidden inefficiencies within specific operations
• Improving the customer experience
• Improving productivity or profits

Undoubtedly, technology is a crucial factor underpinning the digital transformation process. Newer technologies are better equipped to take advantage of new infrastructure developments (5G, for example), tackle new challenges, and build on the wisdom of learning from past mistakes. Newer technologies also tend to be more scalable, flexible, intelligent, secure, and capable of meeting the growing expectations of end-users.

Unfortunately, to their detriment, many only see digital transformation through the narrow lens of technology. That means the software and hardware solutions you employ to enhance or replace existing business practices. However, a true change that’s sustainable, long-lasting, and groundbreaking involves more than just installing (and successfully using) technologies. Taking this narrow approach leaves many of the potential benefits of digital transformation on the table.

True digital transformation goes far deeper than just the technologies involved. It requires fundamentally rethinking your relationship with technology, including your company culture, operating models, and how you approach and manage customer relations. It’s coming to terms with the fact that, increasingly, the technologies you use are becoming the business.

Unfortunately, the term “digital transformation” has become so enmeshed with this old way of thinking that perhaps, it’s time to adopt a new term that better encapsulates this rethink of the digital transformation process. That’s where the idea of “business transformation” comes in, which we’ll explore further below.

What is Business Transformation?

Business transformation is, in some ways, an umbrella term of which digital transformation is a crucial component. While digital transformation has conventionally been associated with constantly improving business technologies, business transformation takes a more holistic approach. It’s a “whole-of-business” approach that’s also concerned with ensuring positive outcomes, whether it’s being more competitive, efficient, or delivering more value to customers.

It just so happens that technology is one of the main enablers of these positive outcomes.

Acquiring and implementing technologies is one thing. However, ensuring they are aligned with your business strategy and measurable outcomes is another. Investing money, time, and effort in the most impressive technologies is pointless if it’s done in isolation from your business objectives.

No matter how savvy or well-informed your digital transformation attempts are, the process is typically expensive, and there will be a disruptive transition phase. So, any investment must bear tangible fruit that clearly satisfies your expectations.

This requires an ideological shift from looking at transforming traditional silos individually to leveraging transformation to the benefit of the company as a whole. Consequently, business transformation is not about addressing specific “why’s” or problem statements but realising wholesale business improvements in line with one particular business strategy. For example, becoming a more customer-centric firm, expanding into new or global markets, or switching to agile work methodologies.

In short, while technology is a key (and some would say indispensable) driver of digital business transformation, it should not be its primary motivation. The main motivating factor should always be the positive business outcomes you want to achieve.

Hardware and software, as well as the security, best practices, and compliance-related standards that govern them, are evolving at a relentless pace. To stay ahead, this forces businesses to be more agile, constantly thinking about innovation and positive change instead of maintaining the status quo. This involves a shift in attitude towards change, from viewing it as a scary and disruptive force to one of optimism and constant improvement.

To do this, companies must get comfortable with experimenting and failing, often and quickly. If you can do this without skipping a beat or wallowing in your failures, you’ll be able to quickly iterate through different models and pick the best one to take your digital transformation forward.

This has led many businesses to adopt agile business models or frameworks. While agile methodologies were initially developed in the context of software development, companies across many verticals have realised their usefulness. After all, most businesses today interface with customers through digital products or services.

The “start small and build” approach, combined with rapid and cheap iterations, makes the entire process more manageable. This is particularly true for businesses that are relatively new to digital transformation or managing their own portfolio of digital products and services.

Small-scale, attainable objectives help ensure that efforts align with success criteria and the transformation roadmap. It also makes it possible to clearly showcase results to business stakeholders and more readily acquire additional guidance.

As a final point in its favour, approaching change from the business transformation perspective will help you become more resilient and receptive to change. If adequately embraced, it will instill the necessary people and culture change for a complete business digital transformation.

How to Approach the Digital Business Transformation Process

Understandably, planning and launching a business transformation campaign can seem daunting. To help pave the way to success, you first must ensure that your project has the necessary drive behind it. This means preparing your most important asset, your people, and your mindset for the change process:

• People & culture change: Ground-level employees, and even customers, need to see the positive impact changes will have on their lives. Business transformation should generate excitement and hope instead of fear and insecurity. At the same time, employees might need time, guidance, training, and resources to adapt to new working models, like agile frameworks.
• Stakeholder commitment, leadership, and involvement: Stakeholders at all levels need to feel included and invested in the transformation process. There should also be top-down support and leadership to ensure the necessary guidance and resources is always on hand. Everyone needs to understand the “whys,” “how’s,” “when,” and “what’s” so they feel included in the journey and not left behind by it.
• Determining actual baselining: You can only validate achieving measurable outcomes if you have a benchmark to measure the success of your efforts. This is another area where technology has an important role to play. By using mechanisms like process & task mining, you can quantify the improvements in your business workflows by comparing and analysing performance across the transformation journey.
• Experiment and adapt: As with all medium-to-long-term business strategy-related undertakings, you rarely lay the golden egg on your first try. It would help if you approached business transformation from a humble and receptive standing. Lessons will be learned, and you need to incorporate newfound wisdom into the rest of your journey. This means not rigorously sticking to a methodology or framework and forcing it if it looks like it’s not working but changing things up when it seems like there are better routes to where you want to go.

 Amongst a limited group of organisations that understand and have developed technology solutions to support Digital Business Transformation is UiPath; providing a raft of technology capabilities that are focused on addressing business challenges and are aligned to the ways in which organisations operate

Conclusion

If you need more convincing, look at your peers. 56% of businesses prioritise digital transformation, and spending in this field is expected to quadruple to $6.8 trillion by 2023, with 87% of leaders envisioning digital transformation to disrupt their industry. This means you must start thinking about digital transformation today to avoid falling victim to disruptive forces.

However, up to 70% of digital transformations still fail simply because organisations lack the proper experience, ambition, and know-how to realise their ambitions. This is where it pays to work with a seasoned partner like Innovo that can guide you on your intelligent automation, tooling and business focused digital transformation journey.

Contact us today to see how our digital transformation services in Australia can help you realise your vision.

Automation and AI are two of the most common buzzwords that come up regarding the digital transformation and modernisation of organisations. However, it’s often hard to equate what high-level explanations of these technologies mean regarding how it affects your day-to-day operations.

To make matters worse, there’s now a new buzzword that businesses need to get familiar with: Intelligent Automation, or IA. It’s no wonder that these technologies are often misunderstood or referred to interchangeably.

While automation aims to make our processes faster and more efficient, AI aims to make them smarter and more valuable. Intelligent Automation is the latest revolution that promises the best of both worlds if organisations can get it right.

What is Automated Intelligence?

Intelligent Automation (IA) is the use of automation technologies, such as artificial intelligence (AI), business process management BPM, and robotic process automation (RPA), to achieve end-to-end business process automation and accelerate digital transformation. The goal is to streamline and scale decision-making within the organisation by freeing up resources and eliminating operation efficiencies.

Simply put, it’s the use of cutting-edge technologies to solve low-level business problems. For example, Machine Learning, Natural Language Processing, Structured Data Interaction, Intelligent document processing, and RPA. Due to its reliance on intelligence-based technologies, IA is also sometimes called cognitive automation.

Typically, five components come together to enable Automated Intelligence:

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

Organisations use IA in a wide range of applications where speed, accuracy, and scalability are of the essence.

Benefits of Automated Intelligence?

• Reduce operational costs: According to KPMG, organisations can reduce costs by up to 75% by implementing IA. Roland Berger estimated that organisations could reduce operating costs by 40%.
• Save time: IA frees humans from managing time-consuming and repetitive processes, especially back office tasks. It can reduce the time spent on processes by 40-70%.
• Reduce the impact of human error: A high volume of repetitive tasks creates the perfect recipe for human error. Automated, rule-based processes are much less error-prone, especially regarding governance and compliance measures.
• Maximizing the value of business data: Bad data costs businesses as much as $9.7 billion and the economy $3 trillion annually. IA helps companies collect, process, store, reconcile, and analyse data at scale to higher standards.
• Improving customer experience: By accelerating speed-to-market and data quality, IA helps businesses deliver improved and more valuable customer experiences. In turn, this increases growth and revenue.

What is Artificial Intelligence (AI)?

A simple definition of AI would be a collection of technologies that work together to mimic human intelligence. We typically think of AI in terms of being able to mimic human behaviour.

However, the vast majority of AI systems used by businesses today are deployed to solve specific problems. Such tools are tasked with solving complex problems that would typically require human-level intelligence. The general intelligence needed to mimic human behaviour is not necessarily efficient or desirable in these circumstances.

In theory, there are three things an AI should be able to do:

• Analyze data and identify patterns
• Learn from its previous actions or experiences
• Self-select responses or strategies based on desirable/non-desirable outcomes.

That’s why AI often goes hand-in-hand with machine learning. Machine learning defines the ability of computers/machines to learn to solve a problem without being explicitly programmed to.

AI is generally divided into three categories:

• Artificial narrow intelligence (ANI) – AI that’s designed to specialise in a specific task or field.
• Artificial general intelligence (AGI) – AI that can adapt and showcase expertise in various situations, like humans.
• Artificial superintelligence (ASI) – AI that can master a vast range of specialised disciplines, exceeding human capabilities.

Benefits of AI

As you can see, the benefits of AI deliver many of the same benefits as intelligent automation. AI helps businesses achieve these improvements from a different angle:

• Enhances decision-making: Thanks to machine learning, AI can surpass human decision-making in specialised areas. AI systems can coordinate data delivery, analyse trends, develop data consistency, provide forecasts, and quantify uncertainties to make accurate decisions.
• Completes tasks faster: By leveraging the processing power of modern computers, the idea is that AI can learn to tackle complex problems in much less time than a human would. It can also scale problem-solving by multi-tasking complex processes.
• Improve customer experiences: For example, chatbots combining AI with Natural Language Processing (NLP) can give customers human-like advice or guidance without waiting for a live operator. Endpoint AI can also give customers access to advanced computing fast and on-demand.
• Minimizing errors: The more complex the problem, the more likely errors will occur. AI minimises errors thanks to fewer data processing mistakes and greater efficiency.

The Difference Between Automated Intelligence and AI FAQ

You probably still have several questions surrounding automation, AI, and IA. Here are some answers to the most frequently asked questions regarding the subject:

What is RPA? Is it the simplest form of automation?

If you’ve done some reading on the subject, you’ve probably also seen RPA. RPA, or robotic processing automation, is software used to create what are essentially software-based robots or bots. They are used to automate simple software tasks and mimic human actions at a basic level.

RPA bots tend to focus on carrying out repetitive, rule-based tasks. An RPA bot typically specialises in carrying out specific tasks using specific technologies.

In most ways, Intelligent Automation is a combination of RPA and AI. AI allows RPA bots to execute more complex processes while using the same ability to carry out human-like actions.

What are automation services?

Also called “service orchestration,” service automation involves coordinating multiple processes to produce the desired result without human action. Service automation is more complex than task automation, as a service can consist of various tasks working in tandem. However, it’s less advanced than intelligent automation because it doesn’t require advanced decision-making.

Still, automated services are nearly ubiquitously used by businesses today to streamline and simplify many everyday activities.

Examples of automated services:

• Submitting a repair request via a digital portal.
• Booking a conference room or event space in advance.
• Ride-sharing or food delivery services.
• Online streaming platforms, such as Netflix.
• Automated AirBnB check-ins/check-outs.

Is artificial intelligence part of automation?

No, a system can be automated without using artificial intelligence. However, as mentioned, AI is one of the core components of automated intelligence and can be considered a pre-condition for it.

Intelligent Automation combines the best aspects of automation with those of AI. It gives automated processes the ability to “think” and “learn” to improve their accuracy, efficiency, and value continuously.

“Intelligence” is the operative word that connects AI with IA. Without AI, automation is limited to only the most low-level, mundane tasks. Intelligent automation, on the other hand, leverages the power of AI to solve higher-order problems at scale.

What are examples of AI?

Here are some of the most common examples of how AI is being implemented today:

• AI-powered media analysis: AI can be used to automatically determine the contents of an image, video, audio, or other media file. It can then automatically tag, sort the media or create metadata regarding it. For example, detecting media that may contain adult content to block it from being uploaded to your site.
• Medical diagnosis: Specialized AI systems can help doctors diagnose patients by analysing symptoms, blood samples, CT scans, MRIs, etc.
• Autonomous driving: Self-driving or completely driverless cars are powered by AI systems that can navigate a car based on environmental sensors, GPS information, etc.
• Fraud: AI is increasingly used in banking and financial services to detect fraud. AI can assess transaction data and compare it to past fraud data to flag suspicious behaviour.
• Insurance: Assessing risk and calculating rates based on it demands extremely complex calculations dependent on many data points. This is the type of computational exercise AI excels at.
• Engineering: AI can use past models to validate designs before they are built and tested. For example, specialised AI systems can use information from wind tunnel tests to assess the aerodynamics of a new aeroplane design.

What are intelligent automation examples?

• Manufacturing: Speed up production by automating repetitive tasks and avoiding human error in daily processes.
• Insurance: Insurers can use IA to calculate payments, make predictions used to calculate rates, and maintain governance and compliance. IA allows them to use the analyses done by AI to execute these operations at scale for multiple contracts simultaneously. Firms can use this to create automated document generation workflows.
• Data capture: Intelligent automation can speed up capturing, organising, storing, and assessing huge amounts of data. For example, you can automatically extract remittance and payment data from submitted documents and integrate it into your financial systems.
• Customer communication management: IA tools can generate personalised and customised content and send it to individual customers. The system can ensure that the right people get the correct information at the right time.

Conclusion

In summary, while IA and AI are two separate disciplines, they are tightly coupled. In some ways, IA is simply techniques and technologies that can be used to scale AI’s decision-making powers to operate under high-volume conditions.

Combining automation and AI can empower businesses by freeing their workforce to deal with strategic challenges. At the same time, it will increase productivity, speed-to-market, and efficiency while reducing costs, time spent on processes, and the risk of human error.

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.