For many years, the advanced use of data for business advantage has been the province of the enterprise market. The mid-market has simply lacked the resources, capacity, and understanding of the technology to access such high-end technical innovation.
That is changing now, and the mid-market is starting to realise the value of these data applications and embrace it in kind. A recent nbn™ commissioned IDG Pulse survey found that more than 20 per cent of survey respondents were looking to invest either in AI or data and analytics solutions. Why is this technology of such interest? As noted by the Organisation for Economic Cooperation and Development (OECD): “SMEs [Small and Medium Enterprises] can execute predictive analytics to lower their exposure to risks, automate business forecasts with real-time data, or increase efficiency in asset management. Enhanced prediction capability also allows for greater market segmentation and opens new opportunities for SMEs to innovate.”
Real-time data can be leveraged by mid-market businesses, with the resources they have access to right now, to improve customer service by gaining better insights and predicting customer behaviour. For instance, it can be used to assist in finding the best candidates to hire, or automate repetitive tasks so that human employees can re-focus their energies on higher-value projects. AI “employee” applications are giving SMEs new options for customer support to handle the highly repeatable enquiries, and thus improve the customer experience.
Other SMEs can use “streaming data” for real-time feedback and insights. For example, real-time data analysis is increasingly used in security applications to catch threats before humans are even aware of them, strengthening the SME against cyber-attack. Retail and other physical spaces can monitor the movement and behaviour of their customers in real time, with research into micro-moments suggesting that businesses that can respond to their customer’s immediate needs and interests can boost the value of that customer.
Finally, real-time monitoring has applications in customer interaction, too. With businesses needing to be online and on social media, being able to monitor how customers are interacting with their brand in real-time is incredibly useful in being able to identify and respond to problems before they can go viral.
There are also plenty of vertical-focused applications that are enhanced by real-time data analysis. Warehouses and online retailers can drive maximum efficiency into the supply chain when inventory levels can be monitored in real time. Any organisation that handles financial transactions can detect fraud instantly when the data loop is instantaneous. A company managing a space (for example, a car park or people gathering area), can use the real-time monitoring of the space to help keep crowds moving, or share accurate information on space availability for vehicles.
In totality, data and AI is a competitive advantage. As noted by McKinsey, “Leaders who embed AI and analytics enterprise-wide will be in a stronger position to tap deeper into the value waiting to be unlocked. They’ll also be ahead of others in addressing the near-term challenges that the pandemic has raised.”
One of the biggest challenges to AI adoption for mid-market enterprises has been network infrastructure. As noted in the OECD report, “since both software-as-a-service (SaaS) and Machine Learning-as-a-Service (MLaaS) are cloud-based [platforms on which data applications and AI run], SMEs need an access to a minimum speed and quality internet connection.”
For real-time data applications to work effectively, there is a need for organisations to take applications online, and leverage cloud solutions to process the data and collect/store it from multiple sources for analysis. With wholesale plans such as business nbn™ Enterprise Ethernet, Australian mid-market businesses can access the same network foundations that large enterprises may use, in turn giving them the opportunity to work with the same data foundations. The challenge that many SMEs face, then, is no longer access to the technology, but rather it’s the strategic understanding of how to approach data and execute on a real-time data environment.
Delivering AI opportunities to the mid-market
For all the potential that real-time data offers SMEs, Deloitte research shows that Australia lags behind other places in the world in terms of how businesses are using these technologies. To use AI as one example, as noted by CIO, “early adopters of AI in Australia were less ambitious about the potential impact of AI on their businesses, viewing it more as a means to ‘catch-up/keep on par’, rather than ‘widen lead/leapfrog ahead’. Deloitte reports only 22 per cent of Australian companies in the second group, compared with 55 per cent for China, 47 per cent for Germany, 44 and 37 per cent respectively for the UK and US.”
These findings speak to the lack of understanding of how transformative real-time data applications can be. A whitepaper by business nbn™, for example, highlighted the ways in which data analytics can result in a more efficient supply chain, the life blood of many sectors in Australia.
“Widespread access to fast broadband via the nbn™ network, combined with the growing availability of cloud-based tools, are putting this technology within reach of more small- to medium-sized businesses,” the report notes. The report also highlights how a robust data practice can improve:
- Remote access
- Customer insights
- Demand forecasting
- Workplace safety
- Customer experience
- Manual processes
It’s not just network speed that unlocks the value of real-time data applications for the mid-market, however. The unique challenges presented by individual technologies requires a network that can offer businesses:*^
- The ability to scale as their needs grow: data accumulates quickly when it is being analysed in real time, and businesses will find that they need to add capacity as they start to derive results from their investments into data.
- Priority data options to service providers for mission-critical applications: low latency can lead to better results when working with real-time data applications, and priority data helps to reduce latency.
- Symmetrical speeds up and down: for cloud-based data applications, the upload speeds are as critical as download, and business nbn™ options include symmetrical data speeds. nbn itself uses predictive analytics and AI on its own network as part of its 24/7 proactive monitoring strategy to spot faults on the network before they occur and impact internet service providers and end-users.
There is no sector that doesn’t benefit from the ability to derive real-time data insights, as data powers everything from supply chain management to marketing, accounting, customer management, sales, and production. With business nbn™ being committed to providing eligible Australian businesses with access to fast, business-grade broadband solutions, it is the mid-market that stands to gain a lot, as data solutions and analysis become increasingly available within their resourcing means.
Discover business nbn™ and the benefits it may bring to your AI applications.
* business nbn™ is not available on the nbn™ fixed wireless network. Not all providers offer plans based on the full range of wholesale business nbn™ products, product features and services, availability of which depends on an end customer’s access technology and area. Ask your preferred provider if they offer plans based on these products, product features and services in your area.
^ End customer experiences may vary. End customer experience may vary depending on factors such as their nbn™ access technology, internet provider, plan and equipment. Satellite end customers may also experience latency.