Amp The Supply Chain

Hans Thalbauer and Michael S. Goldberg

Earlier this decade, manufacturing executives were skeptical about the benefits of digitizing their operations. According to various studies, only 37% believed digital business could drive revenue growth; 25% thought the sector would be highly impacted by digital transformation within the following five years; and fewer than 10% were implementing digital technologies to transform their businesses end to end.

That was then. The future is arriving fast.

Now every manufacturing C-suite in the world is on the path to digital transformation, with the supply chain at its heart. A transformed supply chain is the enabler for companies to deploy technology for personalizing products, accelerating delivery, and meeting rising customer expectations—all while constantly probing the boundaries of their existing business models.

Researchers at IDC have identified a clear turning point ahead: they predict that half of manufacturers will be benefiting from digital transformation in their supply chains by 2019.

Charging Ahead with
Supply Chain Transformation

When successfully implemented, digital supply chain technologies will lead to revenue gains, boost service quality, help cut innovation costs, and speed product-to-market times. The evidence is already apparent.

 2018

90% of supply chains will use B2B commerce networks to collaborate. By enabling decentralized collaboration among members of networks, blockchain technology is beginning to demonstrate its potential to automatically speed up supply chain network transactions. CoinDesk reports that BHP Billiton, one of the world’s largest mining companies, has started using blockchain technology to automatically share data with vendors (including geologists and shipping firms) that collect and analyze mining samples instead of relying on spreadsheets.

Manufacturing centers and microfactories with 3D printers will receive 500% more funding. Ford is testing 3D printing to make parts, starting with plastic molding for auto interiors and spoilers that go on racing models. The technology has potential to speed delivery of parts and save money in assembly and service processes.

Data: IDC

2019

Supply chain productivity and efficiency using Internet of Things (IoT) sensors will improve 30%. IoT-based sensors that enable the collection and analysis of data—and the analytics tools that make good on the variety and speed of that data—make productivity and efficiency improvements possible. Following a model with jet engines made famous by General Electric, Kaeser Compressors has fitted its air compressors with internet-connected sensors and is selling metered air compressor services rather than the equipment itself. Not only does this represent a new business model for Kaeser, it also improves uptime and service quality for customers, because the manufacturer, not the user, is responsible for maintenance.

50% of supply chains will benefit from digital transformation, while others will lag due to outdated business models and systems. The creation of local factories and mini-warehouses will put subsets of products closer to where they are needed and will locate production processes and products closer to customers. Adidas is building a “Speedfactory” in Atlanta, slated to open in 2017, that will bring customized products to American retail customers faster than could be done when manufacturing is executed primarily in Asia. The Atlanta facility, modeled after a factory in Germany, will use robots to automate production processes that can, for example,  customize shoe styles and fit to match customer specifications.

Data: IDC

2020

50% of mature supply chains will use artificial intelligence and advanced analytics for planning and forecasting. Intelligent systems can make faster and better predictions than people can. The healthcare unit at Merck KGaA is working on an initiative to bring sensors and intelligent software algorithms to bear on its supply chain, according to The Wall Street Journal. The goals: better data about how products do in the market and an accelerated planning process.

50% of manufacturers will deliver directly to consumers. The McDonald’s supply chain once stopped at the restaurant door. But after offering delivery services in Asia and the Middle East, the company has begun pilots to bring burgers to customers—even partnering with ride-sharing digital natives at Uber in Florida to deliver meals.

Data: IDC

Digital Power Source

The opportunities for supply chain transformation are real, although the path forward is challenging. An SAP-sponsored study by research and advisory firm Longitude notes that while many enterprises appear to be digitized, the foundations of their operations—supply chain, procurement, and logistics—are still analog. Market forces are placing these companies under great strain, making them susceptible to disruption by digital startups.

Transformation means converting analog processes into digital supply networks—now. While every company’s digitization strategy will be different, enabling these processes requires the following:

  • Ask the right questions. To avoid being overtaken by a lean startup, you need to continually evaluate your operations against competitors. Some questions to ask, according to Peter Weill and Stephanie L. Woerner in the MIT Sloan Management Review: Are the products you make ordered and delivered digitally? Can you equip them with data to make them more valuable? Are there other firms serving your customers that could become competitors? Can a digital offering replace your products now or in the future?
  • Have the right data systems in place. You need information from everything in your production ecosystem—including sensors, machines, factory and warehouse equipment, trucks, and even products—in forms that you can analyze to improve production processes.
  • Commit to automation. Machine-learning technologies make your systems more intelligent, so you can pursue the right opportunities and produce the right outcomes. For example, blockchain technology applied to supply chain systems can configure order processes so they happen immediately.
  • Include every process. The digitization effort should cover manufacturing processes from product design and configuration to supply chain planning, manufacturing, shipping, and after-sales service.

These points are where the discussion starts. Every C-suite will have its own approach to how these elements come together for their firm to succeed. Many companies are executing their strategies now. The rest need to head that way. D!

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Hans Thalbauer

About Hans Thalbauer

Hans Thalbauer is globally responsible for solution management and the go-to-market functions for SAP digital supply chain solutions and the SAP Leonardo portfolio of Internet of Things solutions. In this role, he is engaged in creative dialogues with businesses and operations worldwide, addressing customer needs and introducing innovative business processes, including the vision of creating a live business environment for everyone working in operations. Hans has more than 17 years with SAP and is based out of Palo Alto, CA, USA. He has held positions in development, product and solution management, and the go-to-market organization. Hans holds a degree in Business Information Systems from the University Vienna, Austria.

Michael S. Goldberg

About Michael S. Goldberg

Michael S. Goldberg is an independent writer and editor focusing on management and technology issues.

Savour The Flavour

Lucy Thorpe

Next time you pop a stick of strawberry gum, it might be worth remembering that there are dozens of different varieties of strawberry flavour, each one tailored to suit the market preferences of people from all over the globe.

Welcome to the world of flavour according to TasteTech, a family-run manufacturing business in the UK which has been making controlled-release food flavourings and ingredients for the food industry for the past 25 years. They have ambitious plans for growth, but until recently did not have the digital-first mindset necessary to get there in today’s competitive world.

As a highly specialised company, TasteTech must offer very high levels of safety, efficiency, and discretion, with many of their clients insisting on non-disclosure agreements to protect their secret recipes. They must also comply with the very strict British standards around food manufacturing. Rob Sinton, supply chain manager and owning family member says, “Food safety is at the forefront of everything that we do which in turn helps to build customer trust.” Correct labeling is vital and everything must be traceable on its journey in and out of the factory.

That is why an analogue approach no longer cuts it at TasteTech, or indeed at thousands of other growing manufacturing companies around the world. A patchwork of different server-based systems assembled on the hoof are not efficient enough in an environment in which accuracy, flexibility, and timely delivery are paramount.

Once they adopted a digital-first mindset, TasteTech were able to streamline their production and distribution processes while gaining greater transparency and end-to-end control over operations. Today, checks are faster, labeling is more accurate, and they can make changes more simply when adding products to their portfolio—all of which enhances their reputation for quality.

They now have a fully integrated ERP system based in the cloud with finance and project management capacity which can manage sales as well as manufacturing.

Theirs is a complex business, and by taking these digital next steps they have managed to increase transparency and efficiency, putting them in a great position to meet ambitious growth targets in the near future.

For more insight on digital-first strategies, see Next-Gen ERP: The Digital Foundation For Cloud-First Firms.

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Lucy Thorpe

About Lucy Thorpe

Lucy Thorpe is a digital marketer and writer with SAP Platinum Partner In Cloud Solutions. Based in the UK, she is a former BBC journalist and presenter. Much of her work is now focused on explaining the benefits of digital enterprise resource planning (ERP) systems for small and midsize businesses.

Courier Service Thrives Under Radical Business Model

Judith Magyar

Originally, Aramex was big locally and small internationally. In his influential book The World is Flat, Thomas Friedman described Aramex as the epitome of globalization. One way companies can flourish in a flat, non-hierarchical world, he wrote, is to act small in order to enable their customers to act big.

The key to being small and acting big is to take quick advantage of new tools for collaboration, and that attitude is deeply ingrained in the Aramex DNA. Decades ago, co-founder Fadi Ghandour offered to partner with international players like FedEx that did not yet have a foot in the Middle East. He knew the local market and could handle the ins and outs of the local clashes and other political and economic disruptions in the region.

The company made its online tracking and tracing system available to its partners, providing them with a unified language and set of quality standards as well as training and best-practice sharing in an alliance that united more than 40 regional delivery companies.

Today, the first home-grown package delivery service in the Arab world is a pioneer in digital disruption.

Crowd-sourced delivery

If you’re in logistics, you’d better be fast—not just because speed is the essence of a courier company, but because of rapid technological advances. The sector is changing. Thanks to the surge in online shopping, small package delivery has become a huge source of revenue, along with the traditional bulk freight business.

Guided by a disruption team reporting directly to the CEO, leaders at Aramex have the foresight to build for what is going to happen rather than what is happening now. With the rise of companies like Uber, Aramex quickly realized the need for a shift in mindset. Their business model is simple: Apps allow the customer to pay electronically for deliveries at a preferred delivery time, to communicate with the courier, and to rate their satisfaction. Apps for couriers enable them to see available jobs, claim tasks, and deliver to the customer’s location.

The model required a massive investment in mobile technology, but it is paying off. Quicker than the post but slower than overnight, Aramex fills a gap in emerging markets in Asia and Africa.

Instead of competing with well-established giants like DHL in Europe or the U.S., Aramex is targeting countries and cultures they know better than anyone. They know how the communities are networked. They can partner with small taxi companies or food-delivery firms that want to monetize their downtime. They are liberating the job market and enabling individuals to do more with their time. Employees can be a barber in the morning, for example, and a courier in the evening.

Power to the people

Like other successful companies in the sharing economy, Aramex is asset-light. Doing business requires engaged employees and partnerships with people who own and operate vehicles needed for logistics and transportation.

Sadek El-Assaad, chief human resource officer at Aramex, explains the secret to employee engagement: “Consumers are not the same, and business is not the same, in all the countries we serve. We need to give all employees the margin to best serve customers as they see fit in their own region. We are developing partnerships with our employees. They can work anytime, they can make deliveries by bike, they can have a franchise for a district or a block where they know the neighborhood and have trusted relationships with locals. They are paid by number of packages delivered.”

Just as consumer habits vary from country to country, so do HR processes. Aramex is now empowering managers to perform standard HR tasks on the go wherever they are, freeing them to spend more time on strategic acquisition of talent and continuous performance management.

“Roles are changing very quickly, so we need to train and upskill employees for the task at hand. Automation is not about removing jobs. It’s about enabling people to change jobs quickly to keep meeting the needs of the consumers. The future of HR is to enable business with the right skills and the right people,” says Sadek El-Assaad.

Few companies have such a successful disruptive business model. Aramex excels because they know that enabling their customers to act big starts with enabling employees to act big.

For more on how digitalization and the sharing economy is changing the workplace, see The New Rules Of Engagement.

This article first appeared on SAP Business Trends.

Follow me on Twitter: @magyarj

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Diving Deep Into Digital Experiences

Kai Goerlich

 

Google Cardboard VR goggles cost US$8
By 2019, immersive solutions
will be adopted in 20% of enterprise businesses
By 2025, the market for immersive hardware and software technology could be $182 billion
In 2017, Lowe’s launched
Holoroom How To VR DIY clinics

From Dipping a Toe to Fully Immersed

The first wave of virtual reality (VR) and augmented reality (AR) is here,

using smartphones, glasses, and goggles to place us in the middle of 360-degree digital environments or overlay digital artifacts on the physical world. Prototypes, pilot projects, and first movers have already emerged:

  • Guiding warehouse pickers, cargo loaders, and truck drivers with AR
  • Overlaying constantly updated blueprints, measurements, and other construction data on building sites in real time with AR
  • Building 3D machine prototypes in VR for virtual testing and maintenance planning
  • Exhibiting new appliances and fixtures in a VR mockup of the customer’s home
  • Teaching medicine with AR tools that overlay diagnostics and instructions on patients’ bodies

A Vast Sea of Possibilities

Immersive technologies leapt forward in spring 2017 with the introduction of three new products:

  • Nvidia’s Project Holodeck, which generates shared photorealistic VR environments
  • A cloud-based platform for industrial AR from Lenovo New Vision AR and Wikitude
  • A workspace and headset from Meta that lets users use their hands to interact with AR artifacts

The Truly Digital Workplace

New immersive experiences won’t simply be new tools for existing tasks. They promise to create entirely new ways of working.

VR avatars that look and sound like their owners will soon be able to meet in realistic virtual meeting spaces without requiring users to leave their desks or even their homes. With enough computing power and a smart-enough AI, we could soon let VR avatars act as our proxies while we’re doing other things—and (theoretically) do it well enough that no one can tell the difference.

We’ll need a way to signal when an avatar is being human driven in real time, when it’s on autopilot, and when it’s owned by a bot.


What Is Immersion?

A completely immersive experience that’s indistinguishable from real life is impossible given the current constraints on power, throughput, and battery life.

To make current digital experiences more convincing, we’ll need interactive sensors in objects and materials, more powerful infrastructure to create realistic images, and smarter interfaces to interpret and interact with data.

When everything around us is intelligent and interactive, every environment could have an AR overlay or VR presence, with use cases ranging from gaming to firefighting.

We could see a backlash touting the superiority of the unmediated physical world—but multisensory immersive experiences that we can navigate in 360-degree space will change what we consider “real.”


Download the executive brief Diving Deep Into Digital Experiences.


Read the full article Swimming in the Immersive Digital Experience.

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Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Chief Futurist at SAP Innovation Center network His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation. Share your thoughts with Kai on Twitter @KaiGoe.heif Futu

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Why Artificial Intelligence Is Not Really Artificial – It Is Very Tangible

Sven Denecken

The topic of artificial intelligence (AI) is buzzing through academic conferences, dominating business strategy sessions, and making waves in the public discussion. Every presentation I see includes it, even if it’s only used as a buzzword – its frequency is rivaling the use of “Uber for X” that’s been so popular in recent years.

While AI is a trending topic, it’s not mere buzz. It is already deeply ingrained into the strategy and design of our products – well beyond a mere shout-out in presentations. As we strive to optimize our products to better serve our customers and partners, it is worth taking AI seriously because of its unique role in product innovation.

AI will be inherently disruptive. Now that it has left the realm of academic projects and theoretical discussion – now that it is directly driving speed and hyper-automation in the business world – it is important to start with a review that de-mystifies the serious decisions facing business leaders and clarifies the value for users, customers, and partners. I’ll also share some experiences on how AI is contributing to solutions that run business today.

Let’s first start with the basics: the difference between AI, machine learning, and deep learning.

  • Artificial intelligence (AI) is broadly defined to include any simulation of human intelligence exhibited by machines. This is a growth area that is branching into multiple areas of research, development, and investment. Examples of AI include autonomous robotics, rule-based reasoning, natural language processing (NLP), knowledge representation techniques (knowledge graphs), and more.
  • Machine learning (ML) is a subfield of AI that aims to teach computers how to accomplish tasks using data inputs, but without explicit rule-based programming. In enterprise software, ML is currently the best method to approach the goals of AI.
  • Deep learning (DL) is a subfield of ML describing the application of (typically multilayer) artificial neural networks. Neural networks take inspiration from the human brain, with processors consisting of small neuron-like computing units connected in ways that resemble biological structures. These networks can learn complex, non-linear problems from input data. The layering of the networks allows cascaded learning and abstraction levels. This can accomplish tasks like: starting with line recognition, progressing to identifications of shapes, then objects, then full scene. In recent years, DL has led to breakthroughs in a series of AI tasks including speech, vision, and language processing.

AI applications for cloud ERP solutions

Industry 4.0 describes the trend of automation and data exchange in manufacturing. This comprises cyber-physical systems, the Internet of Things (IoT), cloud computing, and cognitive computing – everything that adds up to create a “smart factory.” There is a parallel in the world beyond manufacturing, where data- and service-based sectors need to capture and analyze more data quickly and act on that information for competitive advantage.

By serving as the digital core of the organization, enterprise resource planning (ERP) solutions play a key role in business transformation for companies adapting to the emerging reality of Industry 4.0. AI solutions powered by ML will be a broad, high-impact class of technologies that serve as a key pillar of more responsive business capabilities – both in manufacturing and all the sectors beyond. As such, ERP must embrace AI to deliver the vision for the future: smarter, more efficient, more flexible, more automated operations.

Enterprise applications powered by AI and ML will drive massive productivity gains via automation. This is not automation in the sense of repetitive, preprogrammed processes, but rather capabilities for software to handle administrative tasks and learn from user behavior to anticipate what every individual in the company might need next.

Cloud-based ERP is ideal for companies looking to accelerate transformation with AI and ML because it delivers innovation faster and more reliably than any onsite deployment. Users can take advantage of rapid iterations and optimize their processes around outcomes rather than upkeep.

Case in point: intelligent ERP applications need to include a digital assistant. This should be context-aware, designed to make business processes more efficient and automated. By providing information or suggestions based on the business context of the user and the situation, the digital assistant will allow every user to spend more time to concentrate on higher-value thinking instead of on repetitive tasks. Combined with built-in collaboration tools, this upgrade will speed reaction to changing conditions and create more time for innovation.

Imagine a system that, like a highly capable assistant, can greet you in the morning with a helpful insight: “Hello Sven, I have assessed your situation and the most recent data – here are the areas you should focus on first.” This approach to contextualized analysis of real-time data is far more effective than a hard-programmed workflow or dump of information that leaves you to sort through outdated information.

Personal assistants have been around in the consumer space for some time now, but it takes an ML-based approach to bring that experience, and all its benefits, to the enterprise. Based on the pace of change in ML, a cloud-based ERP can best deliver the latest innovations to users in a form that has immediate business applications.

An early application of ML in the enterprise will be intelligence derived from past patterns. The system will capture much richer detail of customer- and use-case-specific behavior, without the costs of manually defining hard rule sets. ML can apply predictive detection methods, which are trained to support specific business use cases. And unlike pre-programmed rules, ML updates regularly as strategies – not monthly or weekly – but by the day, hour, and minute.

How ML and AI are making cloud ERP increasingly more intelligent

Digital has disrupted the world and changed the way businesses operate, creating a new level of complexity and speed. To stay competitive, businesses must transform to achieve a new level of agility. At the same time, advances in consumer technology (Siri, Alexa, and Google Now in the personal assistant space, and countless mobile apps beyond that) have created a desire and need for intuitive user interfaces that anticipate the user’s needs. Building powerful tools that are easy to interact with will rely on ML and predictive analytics solutions – all of which are uniquely suited to cloud deployment.

The next wave of innovation in enterprise solutions will integrate IoT, ML, and AI into daily operations. The tools will operate on every type of device and will apply native-device capabilities, especially around natural language processing and natural language interfaces. Augment this interface with machine learning, and you’ll see a system that deeply understands users and supports them with incredible speed.

What are some use cases for this intelligent ERP?

Digital assistants already help users keep better notes and take intelligent screenshots. They also link notes to the apps users were working on when they were created. Intelligent screenshots allow users to navigate to the app where the screenshot was taken and apply the same filter parameters. They recognize business objects within the application context and allow you to add them to your collection of notes and screenshots. Users can chat right from the business application without entering a separate collaboration room. Because the digital assistants are powered by ML, they help you move faster the more you use them.

In the future, intelligent cloud ERP with ML will deliver value in many ways. To name just a few examples (just scratching the surface):

  1. Finance accruals. Finance teams use a highly manual and speculative process to determine bonus accruals. Applying ML to these calculations could instead generate a set of unbiased accrual figures, so finance teams have more time during closing periods for activities that require review and judgment.
  1. Project bidding. Companies rely heavily on personal experience when deciding to bid for commercial projects. ML would give sales and project teams access to decades-worth of projects from around the world at the touch of a button. This capability would help firms decide whether to bid, how much to bid, and how to plan projects for greatest profitability.
  1. Procurement negotiation. Procurement involves a wide range of information and continuous supplier communication. Because costs go directly to the bottom line, anything that improves efficiencies and reduces inventory will make a real difference. ML can mine historical data to predict contract lifecycles and forecast when a purchasing contract is expected so that you can renegotiate to suit actual needs, rather than basing decisions on a hunch.

What does the near future hold?

An intelligent ERP puts the customer at the center of the solution. It delivers flexible automation using AI, ML, IoT, and predictive analytics to drive digital transformation of the business. It delivers a better experience for end users by providing live information in context and learning what the user needs in every scenario. It eliminates decisions made on incomplete or outdated reports.

Digitization continues to disrupt the world and change the way businesses operate, creating a new level of complexity and speed that companies must navigate to stay competitive. Powering business innovation in the digital age will be possible by building and deploying the latest in AI-powered capabilities. We intend to stay deeply engaged with our most innovative partners, our trusted customers, and end users to achieve the promises of the digital age – and we will judge our success by the extent to which everyone who uses our system can drive innovation.

Learn how SAP is helping customers deploy new capabilities based on AI, ML, and IoT to deliver the latest technology seamlessly within their systems

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Sven Denecken

About Sven Denecken

Sven Denecken is Senior Vice President, Product Management and Co-Innovation of SAP S/4HANA, at SAP. His experience working with customers and partners for decades and networking with the SAP field organization and industry analysts allows him to bring client issues and challenges directly into the solution development process, ensuring that next-generation software solutions address customer requirements to focus on business outcome and help customers gain competitive advantage. Connect with Sven on Twitter @SDenecken or e-mail at sven.denecken@sap.com.