Data in Depth

In this episode, we talk with Mike Wertheim from Hayward Industries. Mike shares how Hayward is using data to boost the company's bottom line and outlines his team's top priorities for 2020.

3:41: 3 Ways Data Can Drive Profits
Mike: Data is important to everybody. For Hayward, we are a manufacturing company and it comes down to the bottom line. So, I'll give you 3 ideas of some things that make data very important to [us]. 

We are a big company in a mature market. The way to grow in that market is through acquisition. When you acquire a company and there's a different set of data, there's a lot of problems. 

The other thing is we have traditionally been a B2B company. And we're trying to compete in this age of online purchasing and there are so many channels that people buy their products from. To do that, we've really got to go deeper and reach out to the actual consumers when possible. 

The last thing is technology. IoT is a big thing, but we're trying to do more than just make the next great product. We're trying to gather the data that's going to help us make business decisions, grow business, and use those smart devices for our business intelligence.

6:13: Mergers, Acquisitions, and Master Data Management
Mike: I've been with the company 5 years and [during that time] we have acquired 5 different companies. That gives us a major focus on things like master data management, where we've got to all be talking the same language. 

9:47: B2B2C
Mike: We're so blind when it comes to selling our products through a distribution channel. So now in conjunction with our distributors, we are actually collecting data about the products that they sell to their customers. That data is so valuable. It's probably the number one thing that our executives are looking for.

15:16: How IoT is Driving Service and Product Development
Mike: We have a chemical monitoring system, a floating connected device. The consumers have an app where they can see what's going on and they can share that information with servicers. So servicers can see... "oh, you're having problems. Maybe I should come out and help you."  

The other thing we do is we sell chemicals in what you would think of as pods, like Tide pods. They're color-coded. So your connected device tells you, "Oh, you've got an issue. Please drop in 2 blue, 3 green and a red into your pool." So, we're connecting on the service side, and we're connecting on the consumable side. 

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On this episode of Data in Depth, we dig into how sophisticated data and analytics are transforming logistics and changing the way companies manage their supply chains. We talk with James Lumb, CEO of Zenkraft, who offers cutting-edge examples of how logistics data can be used to avoid waste, improve customer experience, and even improve your product line.

Chapter markers: 
4:48 - Supply Chain 360
6:05 - Internet of Things
6:54 - Product Improvement Feedback Loops
8:55 - The Power of Data Integration
9:57 - 10x ROI
12:03 - Customer Engagement Opportunities
13:10 - Artificial Intelligence and Data Sharing in Logistics
14:01 - Quoting Shipments in CPQ
15:34 - Win a Pair of Bose Headphones

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We want to say “THANK YOU” for subscribing and following the first season of Data in Depth. So we’re giving you the chance to win some great prizes. 

One lucky listener will snag a pair of Bose QuietComfort 35 wireless headphones! On top of that, we’re giving away other awesome swag including Yeti insulated coffee mugs!  

How to enter:

To be eligible to win, you must complete ALL of the following steps.

1. Subscribe on ANY of the following platforms:
   1. Apple Podcasts
   2. Stitcher
   3. Google Play
   4. Spotify
   5. Alexa/Tune In
2. Provide a review on Apple Podcasts or Stitcher;
3. Follow us on Twitter @DataInDepth; and
4. Tweet us letting us know when you’ve completed all the steps. Be sure to use the #DataInDepth hashtag and mention @DatainDepth. 

Enter by November 11, 2019. Full contest details >

In this episode, we talk with Tom Brennan from Rootstock. Tom discusses the pitfalls of 'FrankenCloud' (multiple cloud systems roughly connected). He also digs into the role of the data-driven CFO and shares how companies can move from a transactional to a strategic approach.

FrankenCloud - 3:45
Tom: People are adding more clouds, and we're in a 'FrankenCloud' stage where you've got multiple clouds and on-premise. You try to draw inferences about that customer and it's very difficult to do.

Andrew: I agree. I'd argue it's probably the number one problem that we see.

Managing Acquisitions and Mergers - 6:32
Andrew: These disparate systems are often the results of acquisitions. I often feel like there's not enough time, energy, or money that's being spent to think about that as a part of the acquisition strategy.

Tom: Yeah. You know, some companies will replace their ERP system wholesale and move everything to one cloud to solve the problem... [Or] they can put in another ERP system such as ours alongside Salesforce pretty easily. Because if they have Salesforce in place, they've already got a cloud stack, and they already know how to administer users, they know how to write reports, do workflow, use chatter... So adding another piece-system is not as intrusive as it would be otherwise, where you'd have to put in a brand new stack, new skillset, new everything. So if people want to get there incrementally, they can, they can add on an app like ours into their Salesforce environment.

Artificial Intelligence in ERP - 9:06
Tom: ... I think AI, in particular, provides the ability to triangulate all this information that we have about a customer and to predict what's going to go on. And so you'll be able to look easily — and especially when it's all in one platform —  across maybe outstanding opportunities for the customer, across quotes... And then look at service cases and activities in your call center. Then maybe look at shipments made or returns that have happened... things under warranty, uh, credits that have happened, where they are in their payment cycle, how good of a payer they are...

Early Warning Signs - 10:37
Tom: This is one way to get an early warning sign as to what's really going on. The customer may be ordering a lot of things, but returning a lot. There's a lot of credits on it after rebates and things like that. And they're not profitable. So you really need all of what's in ERP and all of what's in CRM to get that view.

The Data-Driven CFO - 12:18
Tom: [We've] been looking at how finance pros can move beyond doing the day-to-day transactional things and into a more strategic role. One of the critical underpinnings to making that move is data. These CFOs are "data masters." They're able to provide more insight as to what's going on as opposed to just saying, here's your P and L.

Links:

• Connect with Tom
• Learn more about Rootstock
• Brian Sommers on Frankensoft
• How to be an effective finance business partner: Insights for manufacturing CFOs
• How to get started with Cloud ERP

On this episode, we talk with Ben Cheng from Parsable. Ben delves into the world of the connected worker. He shares ideas for how we can capture the experiences and knowledge of people on the shop floor to develop shared best practices, anticipate future problems, and improve efficiency. Here are a few highlights: 

Shop Knowledge

Ben: During my years in planning, I was always very frustrated with the way that the shop floor workers were being asked to operate. The investment was continually going into our office workers, but we were never really spending money on automating or helping out our knowledge workers [in the shop], the guys that are actually doing the work and are responsible for throughput. We never really thought about how do we make their lives easier.

A New Role for Workers

Ben: I think the factory of the future is extremely exciting. If you fast forward all the way down to a complete lights out factory, in which there is virtually no humans whatsoever, right? What you actually find is it increases the value of the human even more because in the inopportune time that the factory goes down, then the human has to be involved. And you can only imagine the level of automation and the line speeds that are in place in a factory like that and how many units are getting produced. And it only puts more relevance on the human to fix it correctly, right the first time.

Andrew: Absolutely. This technology doesn't replace workers per se. It's more about empowering them to do different aspects of their job than they were previously asked to do. So, more manual work — robots and machines are capable of doing that. The workers of the future need to understand the data and all these streams [and to know] how the shop floor is optimized. Then make those decisions to ensure that development times and changeovers and things that you just described are working to full effect.

X Data

Ben: So there's this concept of “O” data and “X” data, right? O data is operational data. That's traditionally your ERP data, your IoT data. Basically it tells you what happened. But not why or how it happened. O data is just table stakes, right? It's your ticket to entry into this overall game. What’s really exciting now is X data. Which is experience-based data...What I’d really like to start seeing is capturing X data too. Which is really uncharted territory on the shop floor. Experience data is where I feel we're going to achieve a lot of return on investment.

Capturing and Sharing Worker Knowledge and Experience

Ben: So when we think about the personal knowledge and experiences of someone like “the gray beard” [in your shop]. He's the guy who can touch a machine and just from the vibration is able to diagnose the problem as well as repair it. So that's fantastic, but it's not scalable. Right? So how do you then capture that data and recycle it back to the new generation of workers?

Ben: [And then there’s] the company knowledge. What we always call the best practices. Shop procedures and such. And right now, that’s the last mile that’s often not digitized. 

Links: 

• Connect with Ben
• Connect with Parsable
• Going Digital? Prioritize Talent over Tech

In this episode, we talk with Shekar Hariharan, VP of Product Marketing at Jitterbit. Shekar highlights the crucial role data integrations and APIs play in driving innovation, efficiency, and agility in the manufacturing sector. 

2:57 - Digital Disruption
Shekar: Manufacturing, just like any other industry, is being impacted by digital disruption...there's data scattered across different systems, and… unless you connect these systems together, you have what you call data silos. 

3:58 - The Matrix
Andrew: I have this mental image of disparate databases housing lots of data, machines on the shop floor streaming lots of data, suppliers in your supply chain both upstream and downstream... and it just seems like the scene from the Matrix where you see all this data just flowing everywhere and you don't really know how to make sense of it. 

7:40 - Integration Use Cases
Shekar: So, let's break it down into the business goals of why a company would connect data. Streamlining product design and development could be one use case… a great example is retail, where a clothing that is in fashion today may not be six months from now. So, the way you handle that is to set up your systems to support agile manufacturing. So, a product is designed and that's pushed by the design team into production. The production team does a prototype. That goes into quality and testing and eventually into production and deployment, and then you get feedback from your customers on how they like it. That input comes from various channels like we talked about earlier... social, [and sales] and different data points. So just there, you have one use case where companies are trying to streamline their design and development through integration and how the data flows through different systems, from PLM to production, distribution, and back to the design team for continuous improvement. 

11:04 - IoT
Andrew: I think that's a good segue into the Internet of Things, and the blending of machines and humans. 

12:03 - Predictive Maintenance
Shekar: Yeah, absolutely. A great example would be a machine that is working 'round the clock because companies can’t afford downtime. And then, eventually, for you to do preventative maintenance, you need to know the cycle time, maybe other variables are of interest, like your temperature, your pressure... You need data to come in real time from these devices back to tracking systems so that way you can plan. 

13:30 - Proactive Service
Andrew: This is also giving manufacturers more power to provide additional services and support to the end customer. So, getting more into the predictive aspect of the business so that they can proactively go out and service or support things before a customer even knows that they may be experiencing downtime.

14:40 - Industry 4.0 Starts with Integration
Shekar: At Jitterbit, we surveyed hundreds of manufacturers globally, and the insight we got is only about 1/3 have a cohesive strategy to implement Industry 4.0. At the end of the day, if you want to get more ROI, if you want to deliver great customer experiences, digitize your processes, be agile enough to respond to changing market needs... if you want to do all of that, you have to have a strategy in place. And that strategy starts with integration.

Links: 

• From the shop floor to customer experience, data drives manufacturing
• Connect with Shekar