Hitachi Vantara: Custom, Persona-Based Industrial IoT

Hitachi Vantara: Custom, Persona-Based Industrial IoT

Hitachi Vantara’s Siddharth Verma and Andrew Mudford discuss the company’s Industrial IoT journey and the benefits of custom, persona-based solutions

With experience spanning more than 20 years each, both Siddharth Verma, General Manager Manufacturing Division and Andrew Mudford, Account Director, Hitachi Vantara both began their careers in 2000. Specialising in manufacturing, mining, and technology, these two executives reflect on Hitachi Vantara and its journey since they joined the company. 

“Hitachi Vantara is a subsidiary of Hitachi Ltd,” begins Verma, “with over 110 years of industrial expertise, and 60 years of IT experience.”

“Hitachi is a world leader in areas from manufacturing to automotive to power grids and more, but a lot of how we deliver value is through IT and helping our customers digitally transform their operations for data-driven outcomes,” adds Mudford. “Our particular division is tasked with solutions across the IT spectrum, and a big part of that is trying to empower Hitachi's vision around social innovation and the digital connection of our physical world.

“Like many companies, we continue to evolve as a business and the key thing for us is that we have strong leadership driving our agenda around the modern connections of people, places and things to discover new insights that drive innovation. We are focused on the core tenets of data, and how you leverage that data to provide insights and value to customers, whether that’s at the underlying IT infrastructure level or targeted insight for specific industries or verticals such as manufacturing or mining.”


Hitachi Vantara’s Industrial IoT Journey 

“Industrial IoT is a kind of ubiquitous term. It's a bit like big data, it means lots of different things to different people. At its most core for us, IIoT is about understanding what information or what data customers have access to, and how can you get insights from that?” explains Mudford.

“The biggest thing we've found is customers - depending on what particular part of manufacturing they are operating in - are all at different levels of their journey for digital transformation. There's some that are at the most basic level, which is, they just want to convert paper and manual processes to digital. Those practices have been operating in factories for a long, long time and just digitising those allows customers to be a lot more progressive and that's where we start. At the other end of the spectrum, we're dealing with mature customers, for example in automotive, who are looking for more advanced analytics and machine learning type techniques.

“We've been on this journey for a little while now, and there's still a long way to go. The industry as a whole is not that digitally mature yet and there are lots of people that can contribute to the progress. Some of them are going to be partners, some of them are going to be competitors, and hopefully all of them in some capacity or another, customers.”

Echoing Mudford’s comments, Verma says “Our biggest challenge is trying to bring forward the capabilities that are there and in a format that the client can actually understand and appreciate. Over time the options have grown. There are now too many options and vendors. A secondary challenge for us is to differentiate at every step from the competition as well as with what is and isn’t possible.”


Improving Manufacturing and Mining Operations with Industrial IoT

“Industrial IoT applications can help manufacturers across almost all their domains. It allows us to create a rich amount of contextual data of what each process is doing. What is the process contributing? What are the people contributing? And once you're able to see the data across the board, you start seeing potential of: what if I changed this product? What if I produce a few more of them? or what if I change this step? what if I do these shifts? With a digital twin, you can simulate these different scenarios and actually help them plan their manufacturing operations,” explains Verma.

“With IoT, you can start collecting quality data to help them automatically and more quickly detect a lot of the defects that were previously only visible by a person or a process at a later stage. It gives them a lot more insight into how a process can be done and on a faster scale. The quality is measured at a much higher speed and a much higher level. One of the biggest use cases in this is around maintenance failures. We can use IoT technologies to reduce catastrophic failure, which means we can predict failures in advance, and the maintenance schedules can be optimised to the way items are used, which will overall reduce the cost for the manufacturer and ensure they meet their commitments,” adds Verma.

Commenting on the benefits of Industrial IoT, Mudford explains that it ultimately depends on the digital maturity of the customer. “However, at the most principal level, we’re talking about yield and production. We’re talking about the ability to produce units faster and at a better price point.

“A lot of the hype around Industrial IoT is that it is a different operating model. In principle, however, I don’t think that it is. In principle, what we're really doing is we're trying to provide insights into the hands of operators to accelerate making decisions that they couldn't previously make. And that might be in the form of digitisation of planning activities, the automation of assets, or even something as simple as ensuring that operators have the insights to make the right product.”

Giving an example from the mining industry, Mudford continues, “we've put the insights in the hands of operators but in their core system of engagement, which from a change management perspective reduces the amount of time it takes for an operator or the business to take advantage of these activities. And if you look at the history of innovation, manufacturing has been an innovative industry for a long period of time, but generally, it's been in the form of engineers solving problems. When those groups of engineers solve problems, they then move on to the next one. After a period of time, those gains that were made start to erode. One of the benefits that we see from our approach to Industrial IoT is that we can basically embed those changes to ensure that they become sustainable and  that's the fundamental difference. As opposed to just throwing sensors or dashboards at people, it's about embedding sustainable change into the operations of a business.”


The Benefits of Custom Solutions and Developing Them on a Large Scale

“Customisation means different things to different people, but for us at Hitachi Vantara, it’s about being able to tailor a solution to a customer’s needs while using repeatable building blocks, and that’s where the productisation part of our business comes into it,” says Mudford.

“Sometimes you can have a solution bespoke to the customer's needs, but as the customer or the industry evolves, the tailored solution is too unique to evolve with them. We want to get the balance between solutions that are targeted to a specific customer, industry or problem but also can also be scaled and productized. This is our general philosophy and where we see the greatest amount of benefit.”

Adding to Mudford’s comments, Verma explains the two extremes of solutions and solving problems. “One is you deploy a custom solution which is built for a certain client, looking at their particularities and needs. These solutions tend to require a lot of system integrations and hence, become expensive in nature, and over time, very difficult to maintain. On the other extreme, you have a cookie-cutter solution business which is pure software. The idea is the companies will adjust themselves to the customer needs, resulting in a much larger shift on the company side. 

“What we have done at Hitachi Vantara is look at concepts that will enable us to build a solution that gives us economies of scale with lots of features, but that can be customised at any time. We are inspired by what we call mass customisation and the concept of itemisation which allows software frameworks to be highly monetised. This allows us to leverage a lot of features, but the cost is very low due to them being mass-produced.”


Industry-Specific Persona-Based Solutions and KPIs

When it comes to IoT tools and business intelligence tools, Verma explains that the focus is centered around the insights from the data that is coming out, with the data that actually gets used left to the end client or the manufacturer to decide what to do. Being one of the largest manufacturing companies in the world, Hitachi is fortunate to be able to think like the customers it serves. “The way we have built the solutions, they are designed backwards from a person who is working on the shop floor (quality manager, maintenance manager, health and safety manager), and that is what we call a persona-driven solution. We have built this expertise outside of the beta into a user interface that is easily understood and flexible.

“The data comes into an insights calculation and generate KPIs which feed into the dashboards and user interfaces and allow the health and safety officer or maintenance officer to access those KPIs or data points directly to change the way people do their job and benefit.”

When it comes to industry-specific KPIs (key performance indicators), Verma adds that these are important to the way that the manufacturing industry works. Working on a set of KPIs, allows manufacturers to be data-driven in their work, knowing if quality work is being produced.

“So, as I was saying before, industry-specific persona and the KPIs of a particular industry or sub-industry is quite important. Generally speaking, people in the industry talk about manufacturing as one holistic industry area. But when you start breaking it down, industries such as mining, medtech, food and beverage, agriculture, paints, chemicals, all are manufacturing, but when you start looking at them, they don't always adhere to the same KPIs. This is why the industries need their own specific KPIs, and we need to adhere to those KPIs rather than reinventing,” continues Verma.

Adding to Verma’s comments, Mudford says “This is an area we pride ourselves in. A lot of solutions are trying to be a one-size-fits-all solution. For us, with persona-based approaches, we can be very targeted when solving problems specific to those industries. For example, we can provide a solution to a manufacturer that specifically addresses the maintenance manager's needs. With a one lens approach we’re very strong, but where it becomes even more powerful is when we get into the sub-industry and can be even more targeted.

“Manufacturing is a very broad term and what's appropriate to a steel manufacturer is different to an automotive manufacturer, which is different to aerospace. And so, for us, we pride ourselves on driving personas, not only to the maintenance manager but the maintenance manager who is in steel manufacturing. And the advantage of that is we talk in their language and about things that resonate with them, but it also means that it's a faster time to value because that's ultimately what they're going to get measured on. They don't have the time or energy to do science projects, and this allows us to demonstrate relevant proof of value.”