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JDA & WMG, University of Warwick Study: Majority of European Manufacturers Are Only at the Early Stages of Dig

05-Dec-2018
JDA & WMG, University of Warwick Study: Majority of European Manufacturers Are Only at the Early Stages of Dig
The majority of European manufacturers are only at the early stages of their digital supply chain journey, according to a new report from JDA Software, Inc., and WMG, at the University of Warwick. The ‘Delivering the Digital Dividend’ report benchmarked the digital supply chain readiness of 179 European manufacturers, revealing that only 13 per cent currently have a ‘prescriptive’ supply chain (categorised as Level 3, out of a scale of 1-4, with 4 being a self-learning autonomous supply chain). However, the report does reveal that manufacturers are keen to digitally transform their supply chains, with almost one third (31 per cent) predicting they will have a prescriptive supply chain in place by 2023.

Manufacturers missing the mark when it comes to data
The report reveals that most manufacturers are yet to fully harness the potential of digital to compete through greater customer intimacy. Although manufacturers are moving towards greater supply chain segmentation and differentiation, the biggest primary strategic focus is on operational excellence (39 per cent), rather than product leadership (31 per cent) and customer intimacy (30 per cent). Data remains a key ingredient towards delivering both operational excellence and greater customer intimacy, but manufacturers are struggling to integrate and synthesise it effectively. The evidence suggests that manufacturers are only just beginning to embark on data collection from new sources.

Artificial intelligence (AI) is predicted to be the fastest-growing technology
Considering the data challenges facing manufacturers, it doesn’t come as a surprise that they are looking at new ways to come to terms with, and capitalise on, the exponential growth in data. AI adoption is predicted to grow three times faster than other areas of investment, such as sensor networks, Internet of Things (IoT) and robotics. Until now, however, only just over a quarter (28 per cent) have started to use AI.

S&OP struggles, but segmentation and network design are early responses to digital complexity
The report suggests that when it comes to Sales & Operations Planning (S&OP), manufacturers have underlying problems to address. S&OP was rated as having the lowest level of maturity (34 per cent) of the 11 key supply chain processes manufacturers were asked about. Only 21 per cent of manufacturers have the ambition to use S&OP to support end-to-end business optimisation by 2023, and 22 per cent said the same for supply chain optimisation. This indicates that manufacturers should continue to focus on evolving from S&OP to Integrated Business Planning (IBP), as strong processes will underpin digital agility.

Digital optimization means transitioning from a ‘node’ to a ‘network’ approach’, periodic to real-time decision frequency, and supply chains evolving from ‘one-size-fits-all’ to a market segment of one. The research reveals how manufacturers are responding:

  • A key enabler of supply chain segmentation, Allocation Planning and Order Promising, was identified by manufacturers as the process with the highest ambition to adopt digital technology, doubling over the next five years from 30 percent to 61 percent. Doing this will help manufacturers progress on their journey to a segment of one.
  • One fifth (20 per cent) of manufacturers believe that by 2023 their factory planning and scheduling will be able to respond in real-time. 
  • Almost two thirds (61 per cent) of manufacturers will have end-to-end network design by 2023, reflecting the fact that fulfillment complexity has risen rapidly in the digital era. However, in a digital world network design cannot be resolved in isolation: an end-to-end approach is required. 

“To maintain and enhance competitive advantage, organisations need to focus on three aspects of the supply chain digital transformation process,” said Professor Jan Godsell, Professor of Operations and Supply Chain Strategy, WMG, University of Warwick. First they must use digital technologies such as AI and Machine Learning to support core supply chain processes. Next, they should pave the way for end-to-end supply chain optimisation by adding a business process layer to their organisational structure. This will put them in a position to leverage functional excellence while also breaking down siloed areas. Finally, they should lay the groundwork for end-to-end business optimisation, using digital technology to break through the IBP impasse.”

“In practice, manufacturers can enable this to happen by creating ‘safe places’ to experiment with new digital technologies. They may even wish to consider the creation of a separate business entity for more radical experimentation with new digitally enabled business models.”

“This report lays bare a fundamental truth: many manufacturers are not as far along the journey to a digital supply chain as they should be. As a result, they are yet to fully harness the potential of digital to deliver greater customer intimacy,” said Hans-Georg Kaltenbrunner, vice president manufacturing industry strategy, EMEA at JDA. “However, if manufacturers put themselves in a position to better exploit their data, they will be able to evolve supply chains from ‘one-size-fits-all’ to a market segment size of one. Now is the time to begin experimenting with technologies such as AI and Machine Learning. The key is to make sure they can successfully ride the digital wave, finding the right balance between process excellence and digital readiness.”

Access the ”Delivering the Digital Dividend” report here!

*Methodology
To conduct the survey, the supply chain was broken down into 11 core processes, from which a mission-specific maturity grid was developed for each. Participants were asked to identify their current maturity levels and their ambitions for five years’ time, and from those parameters an overall aggregate score was calculated. This methodology enabled patterns in digital maturity to be identified in correlation with ambition and strategic gap analysis