While hyper-personalisation in manufacturing isn’t new, it is certainly in sharper focus thanks to new digital capabilities introduced by Industry 4.0. As a game-changing period in the manufacturing timeline, Industry 4.0 has introduced several advanced technologies such as artificial intelligence (AI), Industrial Internet of Things (IIoT), automation and big data in an attempt to optimise operations and streamline processes.
But what is hyper-personalisation and how can manufacturers leverage it to boost performance and productivity and improve the overall customer experience?
Personalisation has become an important step in helping customers feel like they’re heard and their needs are met. However, hyper-personalisation takes it to another level by using real-time customer data and AI to create highly customised and tailored products. This allows businesses to provide unparalleled customer experiences by giving customers what they want and need anytime and anywhere with predictive analytics.
We explore the potential of hyper-personalisation in manufacturing and how it will transform the sector.
3 benefits of hyper-personalisation for manufacturers
Enhanced customer experience
The main aim of hyper-personalisation is to improve and upgrade the overall customer experience, which translates to better customer relationships, customer lifetime value, brand loyalty and more. Many business leaders are already aware of the importance of customer experience, with 97% of them agreeing that customer experience management is vital for establishing customer loyalty and maintaining enduring relationships.
In manufacturing, this is where advanced AI, and predictive data analytics come into play – manufacturers can tap into the power of Industry 4.0 technologies and leverage these solutions to evolve their operations. By doing so, they can develop new processes to meet customer demands more accurately and foster closer customer relationships.
With the increased customisability and hyper-personalisation afforded by new technologies, manufacturers are equipped to deliver new experiences that give their customers a sense of autonomy, creating stronger emotional engagement. This emotional engagement has been shown to not just reinforce loyalty, but also increase the return rate for businesses, with such customers spending double the amount that disengaged customers do. Even if this personalisation costs more, the idea that production and configuration decisions are made by the customer gives them a stronger sense of ownership.
Increased manufacturing efficiency and flexibility with reduced waste
From the supply chain and logistics standpoint, IIoT connectivity solutions and devices like advanced digital sensors and intelligent machinery and systems have offered numerous benefits, including smart task automation, increased flexibility and clearer visibility of operations.
When we throw hyper-personalisation into the mix, production can become even more efficient as goods will be produced according to customer specifications and demands, mitigating the risk of overproduction and excess inventory. We are already seeing this in certain production lines in smaller microfactory setups that are more agile and can adapt to changing demands quickly.
Improved product quality that meets customers’ unique needs
There is also the potential for improving the quality of goods due to meeting precise customer requirements, resulting in greater customer satisfaction which also contributes to a positive customer experience.
Manufacturers will also have a clearer picture of the time needed for creating customised goods, allowing them to optimise their production schedules. In addition, predictive analytics enable smart forecasting to ensure that essential components or materials can be replaced efficiently, limiting waste and downtime.
The challenges of implementing hyper-personalisation in manufacturing
While there are clear benefits of hyper-personalisation, there are also pitfalls and challenges such as data concerns, difficulty in implementation and AI skills readiness.
Data concerns and security
IIoT and big data play a critical role in enabling hyper-personalisation. However, with the immense volume of data that is gathered and stored, companies must grapple with data quality and ensure that they have comprehensive analytical tools to translate data into actionable outcomes. This is not something that all organisations will find easy to do, especially if they do not have the right systems in place to interpret data accurately and consistently.
Another key issue is data privacy and security. Manufacturers must ensure they have sufficiently strong security measures to safeguard data, while also obtaining the required permissions before they can collect and use customer data in accordance with international regulations like the General Data Protection Regulation (GDPR).
Difficulty of implementation
Hyper-personalisation capabilities require the integration of several types of technologies working in tandem. This synergy between data analytics, automation systems and other IIoT tools can be complex to set up if the organisation is yet to undergo its digital transformation or must contend with old and legacy infrastructure that’s incompatible with these systems.
Additionally, digital transformation can be expensive for some companies. It’s been reported that the average cost of digital transformation can reach around US$27.5 million, while another report found that 80% of these projects were unsuccessful, costing companies an additional US$4.55 million. These costs are prohibitive enough to drive organisations away from committing to such big changes, especially if they don’t have a roadmap or transformation framework in place to guide their transformation journey.
Lack of skilled AI workers and training
Implementing hyper-personalisation requires a skilled workforce that is trained in data science, AI and advanced analytics. Many manufacturers may not have the workforce readiness or training programmes in place to facilitate this.
C-suites and leaders are also aware that AI skills are lacking and need to be addressed, with a recent report showing that only 20% of technology executives feel confident about their employees’ abilities in machine learning and AI. In another survey, 41% of respondents stated that a lack of AI skills is what’s stopping them from achieving further growth.
Is it just a trend?
There are certainly significant benefits from adopting hyper-personalisation as a manufacturing capabilityhttps://incit.org/en/thought-leadership/industry-5-0-what-is-it-and-how-does-it-relate-to-industry-4-0/. Manufacturers who can implement hyper-personalisation can look forward to positive outcomes in terms of increased productivity and improved customer experience.
To fully reap the rewards of hyper-personalisation, manufacturers must have the right Industry 4.0 technologies and platforms in place to assist them in their digital transformation. Transformation frameworks such as the Smart Industry Readiness Index (SIRI), with its accompanying tools like the Assessment Matrix and Prioritisation Matrix, are the perfect starting point for organisations to identify areas to bolster and weaknesses to improve. Learn more about how SIRI can help you organisation evolve its smart manufacturing capabilities so you can leverage hyper-personalisation.
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