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F&F, the clothing branch of UK supermarket chain Tesco, faced the challenge of competing in the fast-paced fast-fashion industry while expanding internationally. To gain market share and ensure customer satisfaction, F&F needed to improve fit and quality control across various styles and suppliers. The company aimed to provide a consistent and reliable fit for customers who often do not have the time to try on clothes. Additionally, F&F needed to enhance communication and collaboration with suppliers to manage the complexities of global sourcing and production.

With an automated cutting solution in place, which was already more than 10 years old, Muebles Liz’s ‘just-in-time’ production was struggling to satisfy customer orders. In addition, their existing cutter was being used for fabric only, leaving nonwoven and other materials to be cut by hand. The main growth objectives were to improve product specifications both in terms of quality and price, and to be more competitive in the market. The main challenge was to meet demand, for which they were logging a lot of overtime hours from manual cutting labor. To overcome this challenge, the Muebles Liz team was looking to acquire a new automated cutting system. Working with Lectra experts it became clear that a new system was only one part of an overall solution and that Lectra’s expertise and know-how could bring even greater benefits. An in-depth analysis of the company’s current production processes formed the basis for a tailored action plan which enabled Muebles Liz to reduce operational costs by improving productivity through more efficient production processes.

For over 80 years, Johnson Controls has led the automotive trim cover industry by providing seating systems that differentiate vehicles and offer customers what they want most—style, comfort, and safety. However, as the trend in automotive interior personalization became more mainstream, the innovative automotive supplier recognized that producing the same volume of car sets as they had in the past while managing the proliferation of options for interiors—different fabrics, styles, and features—would be impossible with the die press system they had been using. Long changeover times, the cost of changing die boards midway through a program, and the inability to change the pattern in a die severely limited Johnson Controls’ production flexibility. In addition, high levels of fabric waste caused by the large buffer between pieces and end loss due to the fixed length of the die board, increased production costs. To improve its competitive position in a changing market and win new business required finding a solution that would allow them to deliver a wider variety of options, meet tight production schedules and reduce fabric costs. Johnson Controls’ executive team decided to undertake a highly strategic project to transform their fabric-cutting value chain by replacing all the die presses in their European plants with automated computer numerical control (CNC) cutting equipment.

Product releases were very carefully planned and typically launched every two months to minimize downtime. The effort took about 15 engineers and 36 hours on average to see the process through. It included informing customers about a release window that lasts as long as 4 hours, updating the application, database, and dependent artifacts after-hours, and staging and monitoring the release for about 12 hours prior to taking it live. The challenge was to find a way to deploy applications into staging and production environments without impacting end users, ensuring 24/7 service uptime, which is critical for healthcare operations.

Muhammed Shakir, the CEO/Founder of MS Learning & Consulting, faced significant delays in the development process due to the need for frequent redeploys. The application, which has a presentation layer and a web service layer, is hosted on Tomcat 7.x. The presentation layer is JQuery-based and interacts with Java components that make web service calls. The web service layer runs in a separate module and war file. Each time a change was made to a .java file in Eclipse, the context was reloaded, creating a new instance of WebAppClassLoader. This new instance did not contain the objects of class Class that held the bytecode of the classes used by the application, leading to a 'classloader hell' situation. This issue was exacerbated by the fact that Muhammed preferred a step-by-step coding and testing approach, which required frequent redeploys, further increasing the overhead and turnaround time.

NetworkedAssets, a software house specializing in telecoms, faced challenges in streamlining their development processes to enhance efficiency and productivity. The team, working as a distributed agile unit, used the scrum template with two-week iterations. Continuous Integration was crucial, and they used Hudson for building applications and running unit tests after each commit. Despite these measures, the application redeploy time was significant, typically around 4-5 minutes, 2-3 times an hour, which added up and impacted productivity. The application, developed in Eclipse and built with Maven, included multiple frameworks like Spring, Hibernate, and Apache Camel, and was deployed on Apache Tomcat. The team needed a solution to reduce the redeploy time and improve their development velocity.

Vaadin Ltd faced significant productivity challenges due to the time-consuming process of redeploying applications during development. The development team, consisting of over 60 developers, was building various UI and system applications for customer projects. The redeploy time varied from 20 seconds to over a minute, depending on the environment, which significantly slowed down the development process. This delay not only affected the number of redeploys per hour but also impacted the overall efficiency and focus of the developers. The need for a solution that could reduce redeploy times and maintain the state across class reloads was critical to improving productivity and developer satisfaction.

During the early days of the project, Jeff Margileth, the CTO, used the Eclipse IDE with Amazon Beanstalk to deploy the application to AWS servers. Each time he made changes to the app in his IDE, he’d push the changes through Amazon Beanstalk. However, this led to 1 - 2 minutes of downtime in production each time an update was pushed, and delayed rollout of app updates requested by customers to limit app downtime. His challenge was how OnBudget could push app updates rapidly in response to users’ needs, and as frequently as needed, without causing downtime.

Las Vegas needed a future-ready partner who could innovate alongside the Smart City and help it avoid traditional obsolescence issues. FlashParking immediately began bringing Brandy’s vision for smart parking to life by deploying 21st Century Parking technology in garages across the city. Nearly overnight these facilities could offer electronic validations, Bluetooth touchless access, over-the-air system updates. Not to mention widespread integrations -- from eParking reservations to two-way video support – available through the FlashParking platform. FlashParking was able to repeatedly integrate previously disconnected, disjointed systems to streamline processes and enhance the end-to-end parking experience for guests. An increase in rideshare traffic was intensifying traffic congestion in the urban core. With close to 23 million visitors a year, the city of Las Vegas was looking for a way to ease curbside congestion and ensure safe and convenient transportation availability. To solve the issue, innovation within the city’s existing transportation ecosystem was critical.

Visible Measures, a media company specializing in video and branded content, faced significant challenges with their on-premise Cloudera implementation. The massive volumes of data and the need for real-time performance outstripped the capacity of their 75-node cluster, becoming an increasing drain on limited internal operational resources. The company needed a solution that could handle their demanding customer base's performance requirements while supporting long-term growth without dedicating their operations staff to manage the Hadoop cluster.

MarketShare's integrated optimization and attribution product was initially operated on another Hadoop-as-a-Service platform. However, inefficiencies in the infrastructure and issues with reliability and availability were making the product unstable. The MarketShare executive team found themselves losing confidence in their Hadoop infrastructure. Significant predictability, reliability, and availability issues with the Hadoop cluster were constantly dogging product development efforts. As big data parallel workloads are often difficult to debug and tune, MarketShare executives often felt a lack of visibility and confidence in its Hadoop infrastructure.

Devicescape initially used Amazon Elastic MapReduce (EMR) to process the data generated daily by the Devicescape Service Platform (DSP). However, Amazon EMR provided inadequate support and performance, leading to recurring job failures and increased costs due to the need for costly on-demand and reserved instances. The frequent job failures and the need to rerun jobs multiple times reduced data accuracy and drove up expenses. Devicescape faced significant challenges in maintaining operational efficiency and meeting its Service Level Agreements (SLAs) due to these issues. The company needed a more reliable and cost-effective solution to handle its Hadoop infrastructure and improve its data processing capabilities.

Diebold’s Global Technology & Services organization needed to overcome existing roadblocks and growth inhibitors to maximize their team’s effectiveness. By automating and streamlining the deployment process, Diebold aimed to increase productivity and efficiency while reducing time-to-market constraints. The company’s commitment to innovation required a platform that could abstract developers away from infrastructure, allowing them to focus on the quality of new and existing applications that deliver business value. Additionally, Diebold needed to decide between public and private PaaS solutions, with a strong preference for private PaaS due to security and regulatory concerns.

In 2010, JPMorgan Chase’s Distributed Technology Engineering and Architecture team, led by its former Global Head Ian Penny, realized that some significant and systemic problems were affecting JPMC and thousands of software developers. These problems resulted in productivity loss, inefficient infrastructure spend and lack of agility. Long lead times for application deployment due to infrastructure provisioning, and software stack build and verification. Inflexible capacity management that requires precise, upfront forecasting and has difficulty in meeting unexpected scaling needs. Lack of effective cost control with large up-front cost requirements and severe under-utilization of physical and virtual infrastructure. Redundant effort between development teams that cause developers to treat application architecture patterns, security configuration, high availability and common services, such as application caching as “one-off” engagements, rather than relying on standards. In reviewing the landscape of approaches and solutions for tackling these issues, Ian and his team noticed something interesting. They identified that many of the large public cloud computing providers had realized that they could revolutionize at-scale computing by leveraging software to define a new operating model with Platform as a Service (PaaS). PaaS enables more efficient use of infrastructure, large boosts in application management agility, reductions in friction and time to market and provides a foundation for developing next generation software applications. Given the scale and growth of JPMorgan Chase’s application portfolio, the bank came to the conclusion that it could reap significant time and money savings by modernizing their IT investments to operate as a Private PaaS that would directly address the identified inefficiencies.

Steve Hamann, VP of Technology at IntrinsiQ, led the organization in building a new cloud product offering from the ground up. Balancing time-to-market deadlines and regulatory compliance needs while leveraging the organization’s existing skills and assets was a complicated initiative. Hamann had to come up with an implementation plan to ensure that IntrinsiQ could execute on their technical vision without distracting the internal development team from focusing on their own technology. Given the mission-critical nature of software servicing oncology clinics, Hamann needed to identify a technology solution that placed emphasis on stability and quality while not compromising on value. After poring through numerous services and technology solutions, Hamann found only one company who could deliver the cloud value it promised: Apprenda.

The wearable device market represents one of the quickest growing segments of the Internet of Things (IoT). From wearable fitness trackers to medical and healthcare monitors, devices are becoming cheaper and more powerful, contributing to double-digit growth. All the while, providing end consumers with an increased amount of data on their health and wellness. Collecting consumer health and wellness data, and displaying it on a mobile device in a secure fashion is not an easy task. The ability to connect these wearable devices to a secure and scalable cloud is often beyond the scope of device manufacturers.

Fire and life safety manufacturers face the challenge of creating highly reliable products that incorporate the benefits of IoT while meeting cost and usability constraints. These products must work every time, as they are often a matter of life or death. The challenge is to offer innovative and reliable products that remain competitive and meet consumer product constraints.

The OEM was concerned about the privacy of the data generated by the connected water softeners and about how much data a dealer could and should obtain on their customers’ installed units. Because most of a home’s water supply flows through the water softener, the unit could collect data revealing information about the number of people in a household and their water usage patterns, perhaps even their vacation schedules. Concerned about this level of data, the OEM wanted to put in place controls that would allow an end customer to determine how much information their connected water softener shared with dealers on an ongoing basis. At the same time, the OEM did not want to hinder the dealers’ ability to be notified about certain events that would help detect or avoid problems with the installed units. The OEM wanted the dealer to have enough data to remotely troubleshoot or resolve issues.

When talking about connected buildings, HVAC is a must-have topic for any discussion. Accounting for about half of a commercial building’s energy usage, and as a leading contributor of occupant comfort, HVAC represents not only a massive opportunity for cost savings, but also the creation of a comfortable and efficient environment. However, the challenge for many property managers looking to cash in on this opportunity comes in architecting a cost-effective solution, both in regards to implementation and ongoing maintenance, that supports open communication across all systems and devices, provides insights into product usage, and more importantly, the flexibility and control to implement changes based on this data.

Water softeners work by removing impurities—iron, minerals, animal waste, herbicides, pesticides, other chemicals—that water collects as it travels from its pure rain or snow form to where it enters a home. Once in place, the water treatment systems require periodic “recharging” with replacement filtering agents, a process that needs to be performed by authorized dealers. Other than recharging, however, traditional water softeners have operated in an “out of sight, out of mind” manner. No one involved in water softeners—manufacturers, dealers, end users—have been able to monitor or control much about their operation.

Lighting is one of the major uses of electrical power on a daily basis around the world. Statistically speaking, between 20 and 50 percent of the total energy consumed in homes and offices is used for lighting. What most people don’t realize is that over 90 percent of the lighting energy expense used for most buildings and homes is wasted due to over-illumination. In addition, in commercial applications such as office buildings, it can often be difficult, without human involvement, to monitor which bulbs may be burned out and need replacement, causing an unbalanced lighting situation.

Ayla Networks faced significant challenges with its traditional CMS, WordPress. The architecture and content structure of WordPress did not align well with the website’s format, making it difficult and time-consuming to navigate, locate pages, or find assets. Employees lacked a staging environment to preview content before it went live, making publishing a nightmare. The need for technical assistance from a skilled developer for even the simplest updates became a costly bottleneck. As the business expanded and the demand for content increased, the process proved inefficient, not scalable, and too expensive. Ayla Networks needed a robust content management platform that was simple enough for the marketing team to manage content without IT dependency. After trying Contentstack, they chose it for its technology and industry expertise.

As soon as Sylvie Shimizu started her new role as Webmaster at Elastic, she knew the content management system needed an overhaul. The existing process with WordPress was clumsy, slow and had a tendency to crash. There was no functional staging area and the production site ran on a completely different system, so once edits were complete, all the steps had to be repeated on the production server. Because Elastic had two domains, that meant Shimizu had to effectively perform each step four times every time she needed to publish content. With just three months to merge the .com and .org sites, Shimizu was already under a tight deadline. With any system other than Contentstack, this process would have easily taken six to nine months to complete. Additionally, the company was looking to move away from using the web production agency that had been responsible for its themes and updates in the past. The agency was slow to make necessary changes and their developers weren’t experienced enough to make the process run smoothly. Elastic had to wait anywhere from a few days to several weeks for changes, and were often told the features and integrations they wanted were impossible, which Shimizu knew wasn’t true. She had experience using a variety of different content management systems over the years and had discovered Contentstack previously. She knew it could scale with the company’s needs, that its implementation would be lightning fast, and that it was intuitive enough for content managers to jump in without any training sessions.

APHA horse shows consist of judging a variety of horses in 30 different disciplines. The APHA rulebook for exhibitors and judges is a lengthy publication consisting of text and photos leaving much room for personal interpretation. This can result in inconsistent judging and frustration for show managers, judges, and exhibitors. Today’s shows draw from a wider audience and may consist of the American Paint Horse, American Quarter Horse, and non-registered horses regardless of breed - all competing and judged on their performance in a specific skill/discipline. This represents a change from the tradition where separate shows were held for each breed, so the standards for the skills/disciplines were judged differently. Exhibitors coming to APHA horse shows need to understand the APHA standards in order to be successful. Finally, horse show rules and standards are subject to change annually, so it’s critical that updated standards, rules, and guidelines are delivered in the most efficient way possible. Prior methods of republishing and distributing documents and DVDs was expensive and inexact. Exhibitors didn’t always have the correct “version” of the standards to work from.

Serving a large crowd at Sporting Kansas City poses two training challenges: rapid onboarding of a primarily seasonal staff and training non-profit organization (NPO) members who come from diverse backgrounds and skill sets. The previous training methods, which included PowerPoint presentations and live instructors, were ineffective as they led to disengagement and a decline in the number of trained individuals over time. This resulted in a negative impact on the fan experience. Additionally, the hectic pace of game days made on-the-job training impractical, necessitating a more efficient training solution.

The Ken Blanchard Companies recognized that the traditional classroom-training model for learning was evolving and new efficient and cost-effective models were needed for delivering leadership content to a wider audience. They knew by utilizing scalable cloud-based technology, accessible on any device -- smartphone, tablet, desktop, or laptop -- at any location, they could repackage their 35 year-old world-class content and reach a brand new audience of emerging leaders. Blanchard had used eLearning for more than a decade, but found the results to be disappointing. The technology was cumbersome and not user friendly. The lessons on the existing Learning Management Systems did not allow for interaction that was essential to making the content come to life. They were never able to deliver eLearning to clients that was consistent with the high standards of The Ken Blanchard Companies.

The Food & Beverage industry faces the highest turnover rate among all industries, with training often being task-based and lacking in soft skills or leadership development. Many employees in this sector are in their first job, presenting a unique challenge. Additionally, financial pressures from healthcare costs, slow economic recovery, and potential minimum wage increases have led restaurants to trim budgets, often cutting developmental training first. This raises the question of whether reducing investment in training ultimately costs more than it saves.

Cost simulation engineers at Soucy faced significant delays in pricing due to their production being located in China. This delay, averaging nine to ten days, was causing frustration among customers and potential loss of business. The lengthy pricing process was particularly problematic for their print-to-build business, where timely quotes are crucial. Soucy's development process, which averaged 51 weeks, was also too long given the three-year average ownership of power sports equipment. The company needed to find ways to trim their lead-time without compromising the critical stages of investigation, proof of concept, validation, and production.

As a new business creating a new design with a new team, a new factory, and a new supply base, the number one priority for LEVC was getting to market quickly with a high quality product. This drove a focus on delivery at the expense of an integrated manufacturing costing strategy. The closer they got to launch, the more apparent it became that they hadn’t put as much into the cost management side of the vehicle as they should have. It was during this time that LEVC committed to developing a cohesive cost strategy going forward. Once this priority was established, LEVC realized they needed some type of tool and process to help identify where they could reduce costs both internally and with suppliers in the future.

For any contract manufacturer, accurate and timely project quoting is a critical success factor. It can make the difference between winning and losing business and making and losing money. And like many others, SFI’s estimators used its own unique blend of different cost calculators, spreadsheets and off-the-shelf cost management tools. It was all very manual and time consuming. In most cases, SFI’s Cost Estimators had to analyze a series of 2-D drawings and then add in each, different attributes, runs rates, parts and labor costs. A big project with 500 different parts could takes weeks or more to quote. In some cases, SFI was getting 3-D models from customers and then taking the time to turn them into 2-D prints. This created a lot of unnecessary extra work and extended the quoting time frame from days to weeks. All this manual effort meant more time spent responding to customer quote requests, more overhead, difficult tradeoffs on priorities and even “no-quoting” some jobs which negatively impacted potential future business. SFI’s estimating team felt it was always playing catch up. Every customer wanted their quotes yesterday because they were likely already behind on their own schedule.