Industry 4.0 Talk Track for DACH Region

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Industry 4.0

TALK TRACK

Industry 4.0 with JMP Pro® for the DACH Region

 

 

AUDIENCE: Prospects new to JMP. Manufacturing organizations that have no tradition and experience in data analysis and need to build expertise from scratch.  Mid- to senior-level managers just starting to think about the potential for more value to be gained from increased digitization, including capitalizing on new data sources and optimization of more automated processes. 

CRITICAL BUSINESS ISSUE:  With more data, assess the potential for new insights and value creation.  For example, some of the sensors may enhance the product, but the data the sensors collect may also be useful to enhance the user experience. What more can be done with the new data being generated as a result of Industry 4.0 investments?  Analysis is the means to ensure successful advances in taking manufacturing to the next level—analyze new and more data soures to create more value with applications like preventive maintenance, statistical process control, digital performance management, and more.  

GOAL:  Broaden analysis capabilities from inefficient and limited spreadsheet analysis to more visual and flexible analysis tools to deliver value far more quickly and easily.  Learn faster from more data and revolutionize ways of doing things to yield greater value. 

 

1. Defining the Problem

Customer Issue Description

1)     Leverage new data sources to ensure new insights and more value.  Where there are data, there is the potential for value.  New technologies, skills and ways of automating offer new opportunities to become more efficient and effective. 2)     Stay competitive/relevant. To protect our brand, stay competitive, and make the right investments, we need to take advantage of new technologies and capabilities to capture more data and capitalize on it.

 

Business Impacts of Not Addressing the Issue

·   The competition may surpass us and put us out of business. ·   Lack of investment in technologies and skills needed for Industry 4.0 could mean substantial opportunity costs, resulting in waste, higher costs, and sub-optimal decisions.     ·   Quality and time to market may suffer in light of the way competitors are evolving their businesses with Industry 4.0. ·   If we don’t embrace the opportunities Industry 4.0 brings, our talent pool may leave to keep skill sets current elsewhere. ·   Not having an Industry 4.0 strategy when competitors do may drive stock prices down. ·   Not increasing the flexibility and developing the variety in our products or services results in not meeting customer demand.

 

External Validation of the Business Impact

“.” I will ask Astrid Ruck for a quote but she’s on vacation this week -Quote from GE or Schott?

 

Challenges/Barriers to Addressing the Issue

·   Organizational culture. Changes will be required to capitalize on the value of digitizing manufacturing processes.  Different skills and more analytical skills will be needed (but we can help them start small). Task to develop the mind set within the company as a whole not for just a few experts. ·   Perceived cost. Organizations may fear what it will cost to invest in the tools, skills, and new processes needed to instrument and measure the things that will help them evolve their manufacturing processes.  ·   Data. Having the right data, dealing with more data (and maybe new types of data), getting data into the software, and getting data ready for analysis. ·   Not knowing where to start. Some organizations may not know what’s possible; they may not readily be able to identify a good starting point to uncover the potential for more value.

 

1. JMP’s Solution to the Problem

Our Approach and Value Proposition

Continuous learning and improvement requires systematically using data to determine more efficient and effective ways to get things done – and minimizing the associated cost, waste, and time.  Through smart instrumentation, the analysis of more and better data will deliver better processes, products, services and levels of organizational performance. JMP provides the full spectrum of analysis capabilities to help you capitalize on data, regardless of source. With JMP, you can: ·       Integrate disparate data sources for analysis quickly and easily. ·       Identify emerging issues more quickly, saving costs, time, and avoiding potential waste. ·       Identify improvement opportunities and uncover solutions more quickly, then communicate results visually. ·       Predict when routine maintenance is needed to prevent more costly repairs and predict other outcomes of interest. ·       Experiment to continuously learn and improve. ·       Manage and optimize processes over time. ·       Evaluate the measurement process, especially important for ensuring new instrumentation is effectively implemented and used for greater consistency of product. ·       Periodic evaluation of the measurement process will ensure less waste. ·       Use the “scientific approach” for predictable development and reduced time to market. ·       Use text analytics to find information hidden in unstructured text and relate it to other observations or measurements. ·       General Simulation allows what-if analysis and a means of dealing with uncertainty requiring little data. ·       Have the right analysis at hand whether the data are coming from repeated measurements, survival analysis, destructive degradation, time series or longitudinal studies.

 

Differentiating Capabilities

·   Comprehensive. JMP has a wide variety of analytic capabilities, since using multiple methods is powerful. As a practitioner, we allow you to have more confidence that you've struck a balance with modeling errors. Within any one modeling technique, JMP provides the right way to make use of the data while balancing the risks. ·   Dynamic visualization. Rich and interactive visualization tools in JMP make statistical discovery easier and more effective, leading to innovation.  Many of the visualizations are innovations in the graphical exploration of data. ·   Cost of ownership. JMP is less expensive than other commercial analysis software. We support analysis from the simple to the complex, including specialized analytical needs like those for reliability and quality engineers, and data miners with a single product that can add value throughout an entire organization.  ·   Compelling graphics. Analysts’ most important job is communicating with and getting buy-in from stakeholders to effect change. JMP presents information in ways that make it easy for decision makers to understand and take action. ·   Ease of use. With JMP’s interactive, intuitive design, you can easily load, explore and analyze your data and “see” results quickly, so you can quickly move to the next step on the path of value creation. ·   Design. Everything that’s done in JMP you can do with pen and paper.  Software is important.  JMP is as much about the way we do things as what we do – it’s the interplay between the user and the software that generates the value.  The world is full of software, some of it good and some less so.  JMP is designed to make the user productive.  ·   Extensibility. You can use JMP as it is and be productive, but you can also make a custom JMP application and tailor them to users’ needs. We provide a greater level of customization and automation compared to any other software (even though they may appear equivalent on the surface). JMP is integrated with SAS, R, Matlab and Excel, so you can enjoy visual discovery in JMP along with other tools already in your analytic workbench. ·   Training and Support. You don’t just buy a piece of Software. You get access to a wealth of training material both for self-paced learning and for guided education. You become a member of one of the most vibrant analytical communities in the world.

 

Case Study

Cree [or something with GE or Rolls Royce?]

Situation:  To produce energy-efficient, environmentally friendly LEDs in an optimal manufacturing process.

Solution:  JMP allows Cree’s production teams to visualize and communicate issues in the process, collect data on those issues, apply models, study the effects of interactions and demonstrate improvement.

Results:  JMP enabled Cree’s sustaining engineering team to pinpoint and eliminate a defect in the manufacturing process.

“I prefer JMP because it’s so powerful in visualizing your data. It allows you to generate the types of control charts, graphs and displays that then allow you to understand that data.”  -Ed Hutchins, Sustaining Engineering Manager, Cree

 

 

 

1. Sales Cycle Guidance

Prospecting Criteria
Value creation: ·   Organizations that seek efficiencies in their processes and in their products and services—those who have made investments in further digitization of manufacturing processes and those who are looking to start. ·   Manufacturers who seek to learn more quickly from data to reveal opportunities. ·   Companies looking to extend their product or service offerings (3D printing, maintenance, etc.) ·   Organizations that are analytically averse but have the vague expectation that they need to cope with digitalization and don’t know how. Become more innovative: ·  Manufacturers who want to be more competitive/innovative with their products and services and how they offer them. ·  Manufacturers who want to exploit their mass production capabilities to deliver customized products. ·   Manufacturers who want to gain better and faster insights with more data. ·   Organizations that want to develop the mind set of their workforce to become more data-fluent and analytical (e.g., the Netflix story)
Staying competitive
·   Manufacturers whose engineers face challenges with more complex products and services. There may be concerns that quality and reliability may be adversely affected. ·   Manufacturers with expensive or time-sensitive materials where the cost of quality is important to manage. ·   Forward-thinking organizations that want to get a better handle on managing processes that are growing in complexity. ·   Many manufacturers face competition that is global and stiff. If they are not on the cutting edge, they may fail.

 

 

Conversation Starters

·   What functional group are you in and how does your group fit in your organization?  (Determine the relevance of analytics to the organization and to them as an individual.) ·   What is your role, how do you fit in and what’s your background?  (Get them to talk about their offerings. Even if you already know, have them explain their product portfolio and what they do.) ·   What is your primary goal?  What kinds of things are you trying to understand better? ·   What investments have you made in Industry 4.0 technologies, skills, etc.? ·   Are people accountable?  It takes time, effort, training, money to achieve to create value from new data sources; JMP accelerates time to insight / value. ·   When the rubber hits the road, what’s really important? What are people in your organization paying attention to and why?  ·   Tell me a little about the kind of data you have. Are you collecting data at all? ·   How do you identify trends and patterns? What outcomes are you trying to predict? ·   How important is it to quantify uncertainty? If you’re faced with a decision between doing two things (for example, either investing in a building or hiring someone else), how do you determine what to do?  ·   How do you know you’re staying ahead of the competition? How do you assess how well you’re doing?  ·   How do you monitor quality today? ·   Describe your solution. ·   What type of analysis do you do?  What type of analysis are you looking to do? ·   Are the processes and products you’re monitoring growing in complexity? ·   Do you have a good handle on all the sources of variation in your processes?

 

Sales Cycle Tips

·   If competing software products are already in use, there may be a way for JMP to displace them, but it may require going to multiple departments, involving more senior managers, and possibly IT.  Cost of ownership is a big play here; we can support expansion of JMP to other departments, eliminating need to support multiple vendors. Big cost savings for IT. ·   Focus on organizations that have no tradition and experience in analytics. Look for doubt and uncertainty. Offer all our training and support abilities and the safety net of our helpful community.

 

 

Industry40TalkTrack.docx