Extracting value from data analytics in manufacturing

22nd August 20184 Minutes

In an article published in Raconteur’s “Future of Manufacturing’, John Mason discusses how manufacturing firms have turned to data analytics and artificial intelligence and asks how many are failing to reap the rewards. What is needed is a sharper business focus to achieve expected returns.

Aside from the high-tech and leading corporates, adoption of digital technologies in the manufacturing sector remains subdued, a consequence perhaps of not seeing widespread evidence of the tangible benefits. Achieving expected returns on investment from advanced analytics and AI is less a question of technology and more a business challenge.

Success stories among early adopters are well publicised and demonstrate the advantages to be gained when the power of data from multiple sources is harnessed through expert hands and into business execution.

More precision in research and development reduces costs and increases success, product lead times can be compressed, sales and service are optimised for overall value, goods can become services, supply chain efficiencies are maximised, defects are reduced and production assets can operate at their potential.

For many though, there are “missing links” that are preventing the expected value being realised from the potential a wealth of data, analytical skills and technology are offering.

Clarity of business priorities is the starting point and that requires executive level direction. Technology has provided the toolkit, but how it should be used to best effect cannot be delegated to the IT function. The increasing presence of chief digital officers on executive teams is one trend bridging the gap between the business agenda and the role of technology.

“Generating business insight is a critical business capability that unlocks new value yet sometimes seems to be forgotten among the increasing volume of information and analysis,” explains John Mason.

Advanced analytics enable businesses to combine multiple datasets to highlight new information. The same cross-functional thinking is required in the application of this information.

For example, optimising asset performance will require co-ordinated action across production, engineering, maintenance and third-party equipment suppliers to achieve the potential performance uplift that connectivity and predictive analytics can offer. Most importantly, the business and IT functions need to work much more closely, and find a common language.

Risks associated with data security are often cited as a brake on adoption. Having a robust governance framework that defines who owns what information and how it should be used is essential.

50%

initiatives don't deliver their cost of capital

67%

companies reported human and technical capabilities as a bottleneck

Arguably the least considered aspect of a technology-led investment in data and analytics is the practicality of turning insights into measurable results. Success requires organisations to have the capabilities to act on and implement changes. The ability to test, learn, adapt and adopt is needed at all levels, and information needs to be made available to those who are going to use it in a way that is practical. Implementing minimum viable products and adopting “fast-fail” approaches that can quickly demonstrate impact are not widely established practices in many organisations.

Operating models and processes need to be capable of accommodating evolving knowledge, and the perceived threat that time-served, experienced staff may feel need to be overcome. “The expectation that the whole organisation will automatically see the benefits is likely to be unfulfilled. Involvement and ownership are key, as they are for any sustainable business change to work,” says Mr Mason.

When the links are forged for businesses to generate genuine commercial insight and swiftly translate it into action, the potential advantage of analytics will be fully realised.

raconteur

This article originally featured in Raconteur, August 2018

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Infrastructure: back to the old Benchmarks?

10th August 201810 Minutes

Edem Eno-Amooquaye discusses why the Infrastructure & Utilities sectors should refer to established Manufacturing practices as benchmarks for approaches to optimise both productivity and capacity.

Evolving approaches, same issues?

The Infrastructure & Utilities sectors have moved on significantly from an era when Six Sigma and adopting the productivity improvement methodologies of organisations such as Motorola and GE signalled the leading edge of business change.

Infrastructure & Utilities organisations have evolved in the industries and approaches that they look to as benchmarks. In an environment that demands customer centricity, competition, digitisation and advanced capacity management, infrastructure owners now model their aspirations on phenomena such as the dynamic slot control methods of airlines and the real-time data management of logistics companies.

Questions arise when we consider whether the modern challenges being faced by the sectors are being framed in accordance with the solutions that we aspire to offer rather than there being a suitable acknowledgment of the boring facts. These facts are that along with the new challenges, the age-old issue of how to improve productivity remains. Organisations are ‘going digital’ in line with industry trends and customer user experience expectations but have not necessarily gained full control of the basics. In the UK for example, the economy has been shackled by consistently low productivity since the financial crisis and a significant shortfall to productivity levels on par with the other European G7 nations (France, Germany and Italy) has long been maintained. The reason for this shortfall is a source of ongoing debate but the optimum balance between factors that influence productivity such as process efficiency, labour practices, regulation and technology adoption is one that the UK’s G7 counterparts have come a lot closer to achieving.

Out with the new and in with the old?

It would be too simplistic a next-step to infer that these age-old issues can be addressed by the age-old solutions, but this does not mean that the basics should be neglected. Perhaps the Infrastructure and Utilities sectors should consider reverting to a more traditional industry benchmarks source and its associated approach to productivity – Manufacturing.

Leading organisations look to continuously improve performance, driven by a philosophy that there is always hidden capacity or cash to be found by addressing the inefficiencies that have crept in over-time and become accepted. In a recent example of this Curzon Consulting looked at the fundamental components of availability, performance and quality to assess how Overall Equipment Effectiveness (OEE) can be adapted from its Manufacturing roots and used in the Water industry. This analysis identified considerable opportunities to increase OEE from today’s current levels and optimise capacity in waste water treatment businesses. Utilities companies have historically built waste water treatment plants in response to the need to deal with waste in specific locations but without a full strategic understanding of demand in an area, let alone a real concern for how to operate most efficiently or the potential for commercial opportunities. The application of OEE offers benefits to waste water treatment businesses that include reduced downtime and maintenance costs, better management of the equipment life cycle, labour efficiencies, increased productivity through improved visibility into operations, increased productivity by identifying bottlenecks, and, increased profitability. This time around, the application of OEE encourages Utilities organisations to look beyond straightforward process improvement to understand the impact that other functions are having on the ability of Operations or Capital Delivery teams to maximise their effective use of capacity. This should be considered within the context of a totex world for infrastructure and utilities organisations where end-2-end asset management, efficiency of decision making across lifecycle phases and relationships (often with alliance partners) between Engineering, Design, Operations, Project Management and Commercial functions are now paramount.

An even more provocative assertion from the Manufacturing industry acknowledges the competition driven and regulatory need for enhanced customer centricity but challenges whether businesses should pursue this at any cost. In a Manufacturing context this questions things such as excessive warehouse costs due to stockpiling of goods under the guise of mitigating against the risk of high demand products being unavailable but in fact being a buffer to mask ineffective supply chains. Parallels can be drawn with the digital platforms that many Utilities organisations are developing. The associated business cases promise the benefits of improved customer service performance against a backdrop of new metrics that will either incentivise or penalise companies, e.g. the Water industries new measure of developer experience (DMEX). These embrace the industry theme of digitisation but may retain inefficiencies as they build and hard code layers of old working habits and excessive touch point (process steps that would be labelled as ‘waste’ according to the age-old solutions). While the value of the human touch in customer interaction can never be underestimated the industry must be careful not to regress and allow productivity to be perceived as something that contradicts effective customer service. Further, digitisation is not an end in itself. Wasteful processes on digital platforms are still wasteful processes. Productivity improvements in the infrastructure asset lifecycle and the Lean design of associated system enabled processes should be considered as critical.

So, where to look for the good news?

Real encouragement and evidence of new direction is provided by Transport Infrastructure organisations. Whilst the European Railway with its objective of interoperability and technical compatibility of infrastructure and systems may appear to have struggled to make meaningful progress, key stakeholders in the Rail sector have observed the plans for intelligent supply chain networks and automation in the Manufacturing industry and realise that embracing the Industrial Internet of Things (IIoT) as the approach to technology driven change in a similar manner will be key to transforming the concept of a digital railway into reality. As timely evidence of this, Network Rail has recently announced its Digital Rail Strategy which is headlined by the commitment that all new trains and signalling will utilise advanced technology from 2019. Not to be left out, Utilities companies are also getting on to the front foot. Disparate remote asset monitoring technologies and business specific customer portals are now being firmly placed within strategies for full lifecycle digital asset data models, integrated systems and artificial intelligence led analytics. This demonstrates that the Manufacturing sector’s evolving approach to technology adoption, a key productivity driver, has remained as a crucial, actionable benchmark for the Infrastructure & Utilities sectors.

The infrastructure and utilities sectors must refer to established Manufacturing practices as they have in the past as benchmarks for approaches to optimise both productivity and capacity. In an exciting age of digitisation and customer centricity it will be important to maintain the necessary focus on the principles of productivity and operational effectiveness that underpin efficient business. In terms of the new industry challenges being addressed, rather than waiting to take instruction from the current Manufacturing practices being developed and established, the manner in which progressive Infrastructure & Utilities sector organisations are embracing IIoT and also seeking both inspiration and direction from various other industries indicates that in the not too distant future the sector may itself become a more strongly recognised source of benchmarks for digitisation, connectivity and other future ways of working.

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