Audio version of the article
Every digital transformation strategy must address front-end development, internal systems, and corporate culture. Here are tips from Panasonic at CES 2020.
TechRepublic’s Editor in Chief Bill Detwiler talked to , president of Panasonic System Solutions Company of North America, at CES 2020 about new technologies the company is releasing. The following is an edited transcript of their conversation.
Faisal Pandit: I think if we recall from last year’s conversation [CES 2019], the digital transformation story within Panasonic is all about changing the narrative, changing the conversations we have with our customers. We’ve been primarily a device-focused business for many years, so it’s about taking that conversation to the next level of seeing how we can bundle software and services on top of some of these devices, to bring new value to our customers. The device is essentially one element of that ecosystem, and there’s other business needs that need to be solved. That’s what IoT and the emerging trends have done in various marketplaces, with tremendous amount of disruption, where people want to look at data that get captured through these devices in a holistic manner, and be able to analyze that and draw some meaningful conclusions that can have an impact on the business. At a very broader level, it’s a change in the narrative. It’s about having those conversations, understanding their pain points, and being able to deliver solutions.
Now, the second element of the digital transformation process being, because of our expertise and experience within a lot of market segments, customers are coming to us, outside of the device conversation, and really trying to get our guidance and our advice on other new types of business problems that they’re seeing. I’ll give you a couple of examples. We have a strong presence in the law enforcement space, a huge market share from our ruggedized laptops and ruggedized devices point of view. Now, our law enforcement customers are having conversations about their challenges. One at the top of the list, is distracted driving that causes a lot of pain to them: collisions, and potential impact, to the loss of life of officers and things like that.
We’re trying to work with them on solving some of those problems. How do we change that? How do we take ownership of the ecosystem in the car, and turn it into more of a smart vehicle, where we’re managing all aspects of reducing the level of distraction that an officer has today? How do we reduce or enhance the connectivity of an officer with his or her base through the device that they walk with? Those are some of the kinds of conversations we’re having. In our food retail space, the focus has gone away from POS [point of sale] being at the sort of the center of the quick-service restaurant, to multiple entry points into a restaurant: The kiosk, how do we manage the backend of the kitchen, how do we do we do predictive-demand analysis to make sure that we have the right quantity of food cooked at the right time?
These are some game-changing conversations taking place, and Panasonic is well-positioned and well situated because of our relationships, because of our existing technology, and the expertise we have in other businesses that we can bring that process across industry boundaries. I’ll give you an example of that: The backend of the QSR, quick-service restaurant, is essentially a little manufacturing operation. As you may know, Panasonic has got tremendous knowledge and expertise in the manufacturing space. We’re able to bring some of those best practices, and help customers develop lean practices and lean operations in the backend of the kitchen. Who would have imagined that we would be able to translate manufacturing expertise into the kitchen? There are some amazing changes from that aspect, but what I just spoke of so far, is really one element of digital transformation.
When people talk about digital transformation today they get too caught up in the data. I’ve got to capture data, I’ve got to create this big data in mind, and then figure out engines to mine it, and then do something with it. But, in a digital transmission, especially a larger hardware-oriented company, the front-end portfolio development is one element. The second element is also an internal digital transformation. Are your internal systems agile enough to cater to the needs of the front lines? For instance, when you’re in a device hardware or a product-oriented model, your timelines are different. You have a focus on product specs, pricing, inventory management, and things like that. You can deliver new products over a six-month, year-long lifecycle.
But when you’re talking about software and services, your business model changes. Most customers want a SaaS mode. Most software fixes are required overnight, not in months. So you have to make sure your internal operations are aligned with what you’re trying to do on the front lines. If you don’t do that, if you don’t invest in the right CRM systems, if you don’t invest in the right enterprise-level IT solutions internally that bring that agility to your model, what we see is a gap between what you’re trying to deliver on the front end, and the internal aspects.
The third element is the culture. And culture gets ignored quite a bit because people think that we’ll introduce these new products, and somehow then tie it organization rally around it. It just doesn’t work like that. You have a new generational workforce. Your people are not–and I can speak to our organization–who are well-versed in the hardware conversation. How do you train them into speaking the new language? So the internal cultural aspects need to be changed as well.
It’s a three-pronged approach. You build an external portfolio for your products and services. You drive internal operations, more agile operations. And number three is building a culture, a high-performance culture that aligns, that kind of supports all these changes, both internally and externally.
Five years ago, what we would have done is landed at a customer’s location, and rolled out our products, catalog of products. “I think, Mr. Customer, this is what you need, and this will fit in here and there and we’re done.” I think that’s a recipe for disaster because you’re not really delivering a right solution when you do that. You’re covering aspects of it. What we do today is really an in-depth conversation around, what is the pain point?
And many times, customers may not really understand the depth of the pain points that they have, so it requires a full-blown analysis. For instance, in our industrial automation business, what we do is, we spent at least four to five days with our manufacturing customers, trying to do workshops, trying to get a sense of what the pain points are. It’s a very common requirement nowadays for full-blown factory-wide or enterprise-wide, end-to-end product traceability. They want a routing of the product flow, and controls, and things like that. In a conversation like that, the easy approach is, “Here’s my system, here’s a traceability system, let’s figure out and roll it out.” But if you do that, you’re going to miss 50 to 60% of the requirements.
So what we do is, we spend say a few days understanding the needs, conducting a workshop, having conversations with multiple individuals. Based on that, we come back and say, “Here’s how we see the problem statement, here’s the scope.” And then accordingly, we’ll put a solution in place. Sometimes it’s everything comes from us, or sometimes we will identify partners who can bring their capabilities and we can work together in a collaborative manner.
There’s a lot of communication that needs to be done. You need to make sure you have honest, open conversations. You can’t go up there and throw fluff at people and hope that it sticks. It doesn’t stick. You need to stand up there and say, “Look, this is why we need to change. And this is exactly what we have done. This is why we need to change. If we don’t change, here’s where we will be three to five years from now, and here’s what it means for your future, our future as an entity. And then, here’s what we’re going to do. It will not have any impact on, we’re not here to cut jobs, we’re not driving automation just to reduce costs.”
And once you start doing things and demonstrating to people that yes, the automation aspect was there to help us improve the business, help us scale our business without incurring costs, or help us respond to market needs, people start buying in. If you’re just expecting to stand up there and hope that people believe you, I think that’s a recipe for disaster, because again, you’re not going to get the buy-in. And getting people’s buy-in is extremely important. And we have seen after many, many conversations and after a demonstration of our intent, of our true intent, we’ve seen people coming out and giving suggestions, and offering suggestions, getting excited, because some of the new tools and technologies that we bring to the table, guess what? You’re learning some new stuff. You are developing your career and you’re developing your skillset, which you normally wouldn’t.
I would add technologies and people. So on the front end, you still have data analytics, AI [artificial intelligence], and things of that nature, which are really key enablers. But the people element is also going to become important. People who have expertise in certain market segments. Because the challenge with data is, how do you read it? How do you process it? You have the generic data scientists can give you a statistical view or a more theoretical view of some things. But if you don’t have the business expertise or the knowledge, or the industry know-how, you’re unable to translate that theory into practical best practices. So we’re investing a lot in developing specialties, in terms of people, talent, specialties across market segments that we want to be strong in, in the coming years. That’s one element.
The second element from a frontline, from the first element of our transformation, the portfolio development is, we’re also putting a lot of emphasis on AI and ML [machine learning]. We have data acquisition, data management capabilities, but AI and ML is going to be a big, big focus going forward. And again, it needs to be coupled with industry expertise. Because if you don’t couple with industry expertise, you’re still going to get a very theoretical model, which may not be well received.
On the internal side, there’s a lot of focus on robotic process automation, RPA. And building that capability is another focus we have within our organization on where do we deploy bots, what’s the right model, and what’s the right processes where bots would be a good fit? And, going back to the cultural, the third element, it’s all about education. It’s all about we’re creating market awareness tools and technologies to people at an individual level, to arm them to be more agile and responsive to the new needs.
This article has been published from the source link without modifications to the text. Only the headline has been changed.