Skipping strategic alignment and collaboration in integration projects can lead to cost blowouts, misaligned outcomes, and solutions that fail to support business objectives. Successfully transforming a vision into a functioning prototype requires aligning behaviours, cross-functional collaboration, and a strong link between business goals and technical delivery. This guide outlines a practical, phased approach to integration design and build so that each decision contributes to a solution with measurable operational value.
Michael Coorey
The success of digital transformation hinges on how effectively systems talk to each other. However, translating business objectives into technical solutions often becomes a stumbling block for many Australian organisations. According to the Australian Bureau of Statistics, between June 2021 and June 2023, 46% of businesses indicated a growing emphasis on adopting new technologies and processes to enhance operations. However, this also suggests that over half of Australian companies have yet to fully engage in innovation activities, potentially missing out on the benefits of integrated digital systems. These figures underscore that we're halfway there in transforming integration opportunities and challenges to maximise sales capabilities.
Imagine an online retailer trying to manage stock without real-time inventory updates. Customers place orders expecting a smooth experience, only to find that items are out of stock, leading to frustration and lost sales. In an age where convenience and reliability dictate customer loyalty, businesses that fail to provide accurate, real-time updates risk more than just a single lost transaction—they risk permanently driving customers to competitors.
The adoption of data integration tools has surged recently as businesses across Australia increasingly recognise their value. According to 2024 market research by IBISWorld, revenue for Australia's data processing and cloud hosting industry is expected to climb 9.3% through the end of 2024-25, reaching $3.8 billion. Data integration has quickly become integral to linking systems, consolidating information, and powering insights for smarter decision-making. So, it begs the question, why would a company ever consider outsourcing this vital function?
Sometimes, it’s hard to see the forest for the trees. The popularity of business applications for almost every function and cloud service is growing exponentially worldwide. According to Allied Market Research, the global integration platform as a service market was valued at $3.4 billion in 2021 and is projected to reach $37.9 billion by 2031, an increase of 27.5%.
Does your organisation have a multi-cloud strategy?
Multi-cloud has become the norm for many Australian businesses, with Oracle reporting in February 2023 that 93% of Australian enterprises used multiple cloud environments. Many organisations use a multi-cloud strategy to back up data and reduce downtime. In this blog, I’ll focus on a slightly different angle: adopting a multi-cloud strategy to avoid vendor lock-in and use best-of-breed solutions.
Adopting a multi-cloud strategy enables your company to build a composable infrastructure by using the best features of different cloud providers. A composable enterprise uses modular components to build its tech stack, rather than use a few monolithic applications. It’s an approach that, when done properly, fosters flexible operations and optimises costs.
As of March 2023, the CSIRO found that 68% of Australian businesses had adopted AI and 23% planned to implement it within 12 months. In December last year, the Australian Government announced a $17 million initiative to help SMEs adopt artificial intelligence (AI). The initiative aims to kickstart Australian SMEs towards leveraging AI's benefits and competitive advantages.
However, adopting AI requires more than just financial backing. The Government's initiative acknowledges this by emphasising that it will support SMEs in adopting AI responsibly and efficiently.
Before 'switching on' AI in your business, you need a clear AI business strategy that aligns adoption with the business goals. Critical to this strategy is a strong focus on data integration. Why? Because AI needs comprehensive and reliable information for it to produce reliable results. (Remember the old saying, ‘Garbage in, garbage out’). The best way to ensure that is to automate data flow between systems and into the AI service. Effectively using AI depends on access to well-organised, clean business information to produce reliable insights. Without consistent data sources, your organisation will struggle to get the results you were hoping for in your AI experimentation.
Cloud adoption has steadily risen in recent years, with many of us experiencing first-hand the flexibility and agility required to accommodate hybrid workforces and changing business needs. Australian enterprises continue investing in cloud computing. A Gartner survey reveals that 62% of Australian CIOs plan to boost their cloud spending this year, with goals to improve operational costs and efficiencies. What are the trends influencing cloud adoption?
Do you know how much data your organisation accumulates every day?
Australian businesses accumulate significant amounts of data across sales, marketing, customer service, social media and finances. According to BCG, the volume of data generated by organisations globally doubled between 2018 and 2021. For too many companies, this data remains stuck in siloed systems and unused for decision-making.
Australian Mergers and Acquisitions (M&As) saw a record high in 2021, with the deals announced exceeding the average of the preceding five years. By comparison, 2022 appeared to be a slower year, but a survey by PwC found that 58% of CEOs were not planning to delay deals despite concerns over economic challenges.
For companies completing an M&A, addressing integration challenges must be high on the priority list. An M&A is more than acquiring customers and services; you also acquire the data and processes that support the business. Legacy systems or data silos likely already exist. If these remain unaddressed when merging, they could generate more problems that impact how the new business serves customers, delivers services or completes processes.
In M&A, I often see five data integration challenges arise. Have you accounted for these?
