Data & analytics: the lifeblood of digital transformation
Digital transformation is “the most amazing challenge and opportunity that we have in industry today,” begins Francisco Betti, Head of Advanced Manufacturing and Production at the World Economic Forum (WEF).
“It’s a challenge because it's not easy to understand, to navigate your plants manufacturing, industry 4.0, digital transformation. But it’s an opportunity because we are seeing digital transformation becoming not just the enabler of the future for operations, but becoming the foundations that are allowing companies to develop and deliver new business models.
Digital transformation in manufacturing for manufacturers is at the heart of new value. We're seeing more and more companies that as they transform themselves through the merger of OT and IT they're really setting the foundations for the development of new products and for the development of new customer experiences, by topping up existing products with services or becoming services providers themselves.”
Data: the lifeblood of digital digital transformation
“Data is the lifeblood of digital transformation; however we need the analytics – such as algorithms, optimisation and simulation models – to generate insights and value,” comments Daniel Küpper, Managing Director and Partner, and Stephan Bloempott, Project Leader at Boston Consulting Group (BCG).
“Data is the main enabler of digital transformation,” agrees Betti, “when you look at the fourth industrial revolution more broadly, most of the new applications that we are seeing are powered and enabled by data. So in answer to the question: how important is data? I think it is key, but at the same time it’s the elephant in the room, we survey on a regular basis chief operating officers (COOs), and what we have realised is that there are very few companies that are really able to get new value out of the data they are collecting.”
While there have been large investments made in technology that helps to capture data, Betti notes that “there are several roadblocks when it comes to making sense out of that data. So this is why data applications are extremely exciting and important.” In agreement with Betti, Memia Fendri Project Specialist, Advanced Manufacturing, World Economic Forum (WEF) adds “all the applications from the fourth industrial revolution rely on data. So it really is the lifeblood of digital transformation, whether it's to increase efficiency, empower the workforce, to work more effectively or dissipate any future disruptions and mitigate risks.”
Data in manufacturing: the evolution of its use
“If we take a step back and we look at the pre COVID world, companies and manufacturing companies have been investing in data for quite some time now,” explains Francisco Betti, Head of Advanced Manufacturing and Production at the World Economic Forum (WEF). With trends such as the fourth industrial revolution, climate change, sustainability and geopolitical tensions, “forcing companies to find new ways to stay connected globally,” organisations are being pushed “to start exploring what data, data analytics, connectivity and cloud could deliver.” What started as a use case in a single production line within a specific facility, has evolved into the supply chain, “and now we are talking about this hyperscale ecosystem in which data is collected all the way through, so that there is a continuum data thread or digital thread to deliver new value.
“Now, what COVID-19 implemented is a massive acceleration of all those investments and efforts that companies hadn’t put in place before the crisis started. So if you look at the past 10 years there was a progressive increment, that suddenly COVID created a sort of tipping point in which a major acceleration started to take place. I don’t know of any company that we work with that is not massively invested in data analytics today as they look at how to build resilience, be more efficient, more productive and mitigate risks in a post pandemic situation.”
When it comes to data, Betti contemplates that “what is interesting is that the way in which companies operate is no longer as standalone entities, they're already part of broader ecosystems and those ecosystems are hyper-connected. What is flowing from one company to the other is what is flowing across an entire supply and value chain. These hyper-connected value networks are going to be the rule for the way in which companies will operate, and will be powered and enabled by data.”
When asked why hyper-connectivity is needed, Betti comments “it allows you to develop efficiencies, improve performance, increase productivity and reduce costs. At the same time it allows you to think beyond your operations, to think about how you are engaging with customers and delivering value. This concept of connected value chains and hyper-connected ecosystems in which companies operate I think will be key when it comes to the future of manufacturers and digital transformation.” Echoing Betti, Fendri adds, “ as we now think of more hyper-connected value networks and supply chains, there needs to be an end to end flow, and that is a flow of data and information. So that’s really at the heat of the digital transformation, manufacturing and supply system.”
Unlocking data’s value in manufacturing
Outlined in a white paper produced in collaboration between Boston Consulting Group (BCG) and the World Economic Forum (WEF) – – the two companies identify three core values that the manufacturing industry can gain from effectively using data and data analytics within its functions and operations.
The paper begins by saying that “manufacturing companies capture value from data
and analytics using different mechanisms,” such as creating transparency in complex problems, predicting future developments, and autonomous decision making. Those that are already successfully implementing cutting‑edge data‑and‑analytics applications and developed effective data ecosystems are unlocking value in three ways:
“A continuous improvement journey that helps companies gain efficiencies, reduce costs and optimise operations. Within that it's also about improving your speed to market,” comments Betti, who adds that “this is where value is sitting today, when it comes to the future of data, data analytics, data sharing and collaboration in manufacturing.”
Applications to improve productivity
Predictive quality, generative AI-driven product design, data-driven integrated sales and operations planning can help improve these [Küpper and Bloempott].
2. Enhanced customer experience
“The concept of improved or better customer experiences by leveraging data, whether it's data coming from your products and the life cycle of your products or data coming from the usage that your customers have given to those products,” continues Betti, “this is really helping companies go to market with new customer experiences, which is extremely exciting.”
Applications to enhance customer experience
Predictive quality, generative AI-driven product design, data-driven integrated sales and operations planning can help improve these [Küpper and Bloempott].
3. Positive impact on society and the environment
Betti identifies this as “the most important in the post COVID-19 crisis, in which we are talking about this concept of stakeholder capitalism.” Betti explains that “the need for companies to deliver value, not just for the shareholders, but for all stakeholders in society, meaning shareholders, workers, society, the environment, and all the different actors,” can be delivered with the help of data analytics. “If you look at how you can optimise material consumption through data analytics or how you can reduce CO2 emissions you optimise your processes. I think that there's a huge promise there within the broader framework of this concept of stakeholder capitalism.”
Applications to have a positive impact on society and the environment
Data sharing for traceability along a supply network, or using algorithms to predict and improve energy efficiency [Küpper and Bloempott].
Six priorities to unlock the value of data in manufacturing
With the value to be had in harnessing data in manufacturing identified, BCG and WEF outline three organisational and three technological priorities for organisations to focus on in order to realise such value.
1. A clear data-to-value strategy and road map
“When you talk to many companies still today, not all of them have a clear view on what they can deliver, still there are only a few of them who have clear roadmaps, and have the buy in from the top management to make digital transformation a reality and be able to leverage data and analytics at scale, across the entire organisation. We often see companies being successful in transforming one specific facility, but I think that it's taking that to the next level and transforming that scale is the other challenge,” explains Betti.
“What we've noticed is that this really needs to be purpose driven,” adds Fendri, “you need to define what is the right application that you want to implement for your intended purpose and see how data plays a role in there, and that is often the main driver for success.”
2. Incentivise internal and external ecosystem partners
Within the BCG and WEF report, the two draw attention to the need to work in a collaborative way with your internal and external ecosystem. “You need an ecosystem,” comments Betti, “whether it's because you want to develop new applications and therefore need access to startups and innovations who may be working on the latest state of the art technology that can leverage data, or whether it's because you need data that you may not have, collaboration on that front can help a lot.” Betti goes on to explain that ecosystems can also help to scale up innovation, you need to be partnering with the broader ecosystem to open up your eyes, and be able to first, benchmark yourself but also come up with a new innovation strategy and develop the next generation of data-driven applications.”
3. Build capabilities to capture and use data
In order to build and maintain data and analytics applications, “companies need a new skill set that combines digital skills with sector‑specific manufacturing know‑how,” explain BCG and WEF. With technical infrastructure becoming increasingly complex, and more and more decisions are made by algorithms, “it becomes more important for companies to have the data science skills to build applications and understand the insights generated by these algorithms,” adds BCG and WEF.
By having the right combination of digital and manufacturing skills companies can translate insights into actions for factories and supply chains. When it comes to such capabilities, Fendri explains that “data collection is one thing, but there's also a lot of processing of the data, the cleansing of the data, and also being able to generate insights and make meaning out of this data. These capabilities really need to be in place either within the organisation or by partnering with experts.”
1. Implement an open platform to unlock data silos
With many applications requiring bidirectional data flows from different companies or different systems within a company, BCG and WEF explains the complexity in achieving this due to data often being stuck in silos. “A cloud‑hosted platform helps companies overcome this barrier by facilitating the sharing of data both within the company and across company boundaries with suppliers, customers and other ecosystem partners.” Complementing the report, Fendri adds “If we want to unlock data silos and we think of hyper-connected value networks, open platforms allow for this information flow either within a company's boundaries or across a company’s boundaries.”
2. Enable connectivity for low‑latency, high‑bandwidth data flows
In addition to many applications requiring bidirectional data flows, many also need uninterrupted, low latency, high-bandwidth data transfers, specifically continuous wireless connectivity is crucial for autonomous decision making. “Wireless connectivity allows companies to have highly flexible factories within which they can easily adjust the layout. It also makes it possible to constantly connect mobile assets and goods to a central platform, enabling an uninterrupted stream of data. In addition, wireless connectivity is a key enabler for the plug‑and‑play use of sensors and cameras, which can be used to upgrade older machines,” states the BCG and WEF. Emphasising the importance of connectivity, Betti adds, “connectivity across the entire organisation is not a negligible point. Connectivity remains a challenge for many global companies, especially when you have facilities in both developed and developing countries.”
3. Ensure data security and privacy
“Data data security and privacy is really the most important one,” says Fendri. “Preventing data breaches, knowing also how to protect sensitive data so that you don't lose competitive advantage, as well as preventing the misuse of data you need to be able to control the usage and prevent it from being used for purposes that you might not want.”
“You need to focus on privacy and security, you need a plan to future proof your manufacturing, supply systems and data ecosystems against cybercrime,” adds Betti, “I think that’s probably one of the concerns that people still have in mind.”
Data and data analytics: its future in manufacturing
Contemplating the future for the use of data and data analytics Betti starts by says “something that is interesting is that if you look at the future, and you look at the trends for climate change, geopolitical tensions etc they are intensifying, which means that crisis in the future, and likely going to happen more often. So, you know, leveraging data and analytics to future proof operations is a must have for every company in this war.”
Circling back to the pandemic and the effects it is having on industries and economies, Betti adds that “at a time in which we do not know how long this economic crisis that has come with the pandemic is going to last, I think that it is often easier to make the most out of the investments you have already done, rather than going for new capital investments or new equipment. But we are seeing in a post-crisis scenario investments on data analytics application solutions is one of the main things that took off because they did not require a massive investment. It actually was all about making the most or making more, directing new value out of data that was already available within facilities and across the supply chain.”
Looking beyond the post crisis scenario, Betti believes “there are still a lot of pain points that companies will need to address because new degrees of cross company collaboration of data sharing are going to be required. If we want to continue this evolution journey that started 10 years ago, that became a tipping point with COVID, companies can really go to the next level in the near future.”
Echoing Betti’s thoughts on the future, Fendri adds “after the COVID-19 crisis, we see the need for more visibility in the supply chain, understanding who the supplier of your supplier is and how they're being impacted by crisis or disruptions. The other element that we saw is that higher need to free up liquidity for future investments and here data can really help with increasing operational efficiencies and realise operational improvements making them more productive.”
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