Companies are currently on a huge crusade to find ways to make digital transformation for their business.
This is because the nature of business has changed and technology is creating a whole new playing field for companies.
I recently read an article on enterpriseinnovation.net that showed how this can be achieved.
The article points out that Singapore manufacturing output increased 5.9% in March 2018 on a year-on-year basis, resulting in a rise in output and a certain degree of excitement among economists and manufacturers. Yet, the majority of Singapore businesses are still a long way from competing with the world’s production powerhouses, such as China.
One of the secrets to long-term success and reaching full production capacity can be found in incorporating innovative technology into production methods. Recent findings show that Singapore businesses seem to be profiting from their investments in digital transformation and 67% say such investments have already proven the value.
The article added that, digital transformation can be an incredibly complex process. With that in mind, here are five key steps companies need to take to prepare for a successful digital transformation journey.
The article points out that companies should start by assessing your overall business goals and ask what objectives your business wants to achieve in the short, medium, and long-term. Then ask what technology will help achieve those goals.
For example, it might be that your primary focus is to expand into new markets quickly, in which case it might be sensible to hold off on that AI investment you’ve been planning, and instead make sure you have a solid cloud infrastructure that can support your mission-critical processes from multiple locations.
The article adds that digital transformation means different things to different businesses and certainly, heavy spending alone is not going to guarantee success.
The Aberdeen Group has identified three digitalisation technologies that have the potential to impact operations–the Internet of Things (IoT) because of its ability to provide operational intelligence, the cloud for its scalability, and big data analytics, which can transform data into predictive and actionable insights.
The article points out that there’s no one size fits all approach. According to global research, 19% of manufacturers are planning to invest in inventory management, 18 % cloud, big data and customer relationship management, and 17% are planning a mobile technology implementation.
There are multiple options, and businesses must ensure that they are investing in the technologies that are right for them. While one business may see immediate benefits from implementing cloud infrastructure, a manufacturer operating out of just one facility might want to look at other options first. For example, they might instead see more immediate ROI from keeping data on-premises, but implementing an ERP solution that uses big data to track orders against stock and supply chain information in real-time. However, if they choose right, their ERP technology should be flexible enough to accommodate growth and an eventual move into the cloud.
The article points out that after you’ve identified how digital transformation can support your business goals, now is the time to bring stakeholders on board because successful digital transformation strategies change how businesses work. They impact people’s jobs, how they complete tasks, and also how they work together.
However, staff from the boardroom and beyond need to feel they have a personal and professional stake in the changes being made. Helping them understand the reason for the business’s investment will make it easier to overcome any potential resistance to new processes. This is particularly important when digital technologies are being implemented to automate tasks that are otherwise completed by staff members, or when it might not be immediately obvious how an investment will deliver ROI.
The article points out that businesses today are collecting more data than ever, but simply amassing vast amounts of information as a result of digital transformation, is not enough. The key lies in being able to use insights effectively, to guide change or identify new revenue streams.
The latest data analytics suites can provide businesses with crucial information about customer trends and predictions, or information about how products are performing. Some businesses are already using this sort of data, to turn insights into action.
The article adds that fabricated metals manufacturer Cladtek Singapore is just one example of a business that is effectively using technology to improve the customer experience and build growth. As Paul Montague, director of Cladtek Group, explained, “With realtime financial data and full visibility into the organisation, our management team is now better placed to make sound decisions and achieve sustainable growth. We are also more confident in meeting the global demands of our customers.”
The article points out that companies need to understand that digital transformation is a journey that is never complete. New technologies are being launched all of the time—from robots that complete tasks on the production line quicker than humans, to machines that can fix equipment problems without intervention. All of these bring with them multiple possibilities for Singapore manufacturers.
It’s important to therefore constantly adapt your digital transformation strategy to new possibilities, reassess your journey, and question your rate of digital change — does it match up to your customer expectations? How does it stack up against your business goals? If these change, perhaps your technology should too.
The article adds that adapting to the digital world can be a challenging undertaking, however there are plenty of online resources that can help you along the journey. An international study by Epicor shows that 2 in 5 industry professionals agree that digital transformation will offer them strong opportunities for growth in the future — proving that the benefits at stake outweigh the costs.
Innovative enterprise resource planning solutions (ERP) solutions, combined with Industry 4.0 developments, are already helping to automate production lines, streamline supply chains, and provide the intelligent data manufacturers need to react quickly to changing consumer demands. For Singapore businesses to take a place among the world’s production leaders, deploying advanced technology to drive manufacturing efficiency is going to be the way forward.
The above steps can be effective ways to build your business. But are they effectively using data analytics? According to a recent blog post I read, Big Data doesn’t necessarily lead to good data analytics.
In the high-tech area, data mining and big data are the buzzwords and catchphrases being widely used, primarily reflecting the information age we currently live in. Indeed, we are living in exponential times, the amount of data generated by people these days is staggering.
The first commercial text was sent in 1992 and today the number of text messages sent and received everyday exceeds the total population of the planet.
The blog post pointed out that it’s also estimated that 2.3 trillion gigabytes of data are created each day and the amount of new technical information is doubling every two years, with 43 trillion gigabytes of data expected to be created by 2020. More recently, Japan has successfully tested a fibre optic cable that pushes 14 trillion bits per second down a single strand of fibre – that is 2,660 CD’s or 210 million phone calls every second.
This showcases how data science is emerging as an attractive field of study and many students are venturing into big data. From traffic patterns, music downloads to web history and medical records, all these data is recorded, stored and analysed to enable the technology and services that the world relies on every day.
The blog post added that by 2015, it was estimated that 4.4 million IT jobs would be created globally to support big data. Thus, businesses today are collecting massive volumes of both structured and unstructured data to give them competitive advantage over their competitors.
The blog post pointed out at in many enterprise scenarios, this end-result is more imagined than real. It’s true that big data is inherently disruptive in nature, but just like how twitter emerged from a hackathon originally intended to send standard text messages to multiple users catapulting to providing news and social networking services that is destabilizing everything from news and information to unpopular governments today doesn’t mean that this is the trend for all businesses.
In his book ‘‘Numbersense’’, Kaiser Fung, a professional statistician and adjunct statistics professor at New York University, correctly emphasises on data analysis over big data mining.
The blog post added that the careful observation of data and good questions generated from careful observations, not the size of it – the ability to process, store and make sense out of the data. He gives the example where some years ago the Gates Foundation made a mistake of assuming that smaller schools are better for student achievement which was later proven to be untrue.