Create Customer-Driven Supply Networks To Enable Innovative Propositions

Chong Mock Seng

Many retailers are caught in a dilemma between service level and inventory. Missed revenue opportunities, unhappy customers – both scenarios are highly damaging to retailers in today’s digital era.

As it is, retail is hyper-competitive. Once a retailer faces an unexpected stock-out and is unable to satisfy a consumer’s needs, chances are the consumer’s attention will be diverted to (and held by) competitors. It’s no better if the situation is an unhappy customer who’s waiting for an unfulfilled order; in today’s terms, it’s akin to a broken promise. Negative customer sentiments can rapidly proliferate on social networks – disastrous in a world that now depends on user testimonials and feedback, especially by social influencers, for purchases.

However, stocking months of inventory in advance to avoid these issues significantly raises retailers’ inventory and warehousing costs. How then can retailers maintain the fine balance between service levels and inventory?

By becoming optimized for omnichannel commerce.

Optimizing the supply chain for omnichannel

Traditionally, most retail organizations are organized in silos. There is little collaboration across channel teams or functions such as supply chain, marketing, and procurement. The supply chain has also remained fairly linear from suppliers, to warehouses, to stores, to customers. This model offers little support in allowing customers to shop across channels – something that is almost an expectation today. Consumers expect to be able to buy from anywhere, for delivery anywhere, sometimes for pick up anywhere, pay anywhere, and even return anywhere.

So deeply has this expectation etched itself in the hearts of consumers that when Alberto Brea, an executive director at Ogilvy One, shared this quote in a post on LinkedIn, it spread like wildfire:

“Amazon did not kill the retail industry. They did it to themselves with bad customer service.”

Bain & Company highlighted the truth that retail’s most valuable customers are engaging across all channels: physical store, mobile, social, and online. And these omnichannel customers typically spend more – some as much as two to five times more than customers who buy in only one channel.

Clearly, omnichannel retailing is critical. But to facilitate that, a transparent supply network is required.

Let’s look at the increasingly common example of omnichannel retail: “Click and Collect,” in which the purchase is made online and the product is picked up in the store. This requires orchestration and quick decision-making across the online channel, in physical stores, and across the merchandising, marketing, and procurement functions. The online channel needs to know in real-time whether the goods are available at the point of order and in which stores. Marketing needs to know customer preferences to be able to up-sell and cross-sell, as well as the availability of the products it is trying to promote – also in real-time. Stores need to receive the order and package the goods in time for pickup. To enable all of this, retailers need full visibility of the entire supply chain in the moment.

These capabilities simply cannot be achieved in a siloed model because the different silos speak different languages. By the time the silos sort it out, the proverbial game is over.

Rather than grappling between improving service levels and reducing inventory costs to maintain or increase margins, retailers must organize themselves for omnichannel commerce and build a customer-centric supply chain to mitigate the classic dilemma. At the same time, they gain new capabilities to enable innovative propositions.

A customer-centric supply network

By placing the customer in the center with the traditional silos (supply chain, marketing, and procurement) networked, retailers can anticipate demand to get the right products to stores and customers at the right time, to fulfill demand from anywhere, and exceed customer expectations.

The customer-centric supply network also enables the retailer to reinvent its business models to stay ahead.

A good example of a company that understands this is Maui Jim, a U.S.-based manufacturer and retailer of sunglasses and accessories. As Maui Jim’s customers evolved, the retailer knew it needed to offer innovative new propositions. It wanted to deliver online orders in the same day or less to its customers. Maui Jim also wanted customers to have the freedom to touch and choose among its product selections; it wanted to be able to deliver multiple pairs of sunglasses to customers and allow them to return the ones they did not want, either in stores or by delivery pick-up.

Maui Jim achieved this by bringing a partner into its supply chain – embedding an UberRush microservice within its technical retail infrastructure – a noteworthy achievement. First of all, such extensive coordination among so many moving parts in the supply chain would have been impossible if the retail organization were still in siloes. The fact that Maui Jim had moved towards a transparent customer-centric supply chain scenario enabled this potential.

Furthermore, it would have been impossible to bring partners into the supply chain had Maui Jim not transformed it into a customer-centric supply network. Traditionally, to include this kind of functionality, IT would have to build or integrate with a complete delivery ecosystem. Thankfully, owing to Maui Jim’s agile supply network empowered by a digital core, the retailer was able to bring a partner onboard and implement the innovative value proposition in 60 days.

Now, Maui Jim knows – in real-time – the minute a customer places an order, and the optimal location(s) for him or her to pick up the sunglasses based on availability. Its customers enjoy speedy deliveries and top-notch service, helping Maui Jim maintain its edge over competitors.

It boils down to fundamentals

The speed at which retailers like Maui Jim are evolving their businesses is rapid. But this is what retailers should be expecting – if not from themselves, then from their competitors. Indeed, if “change” describes today’s business landscape, then “exponential” depicts the rate of it in the retail scene.

What we’ve been discussing – transforming the supply chain – is an important step forward in the right direction that can significantly improve both customer satisfaction and the bottom line. But even so, such efforts will get nowhere without strong fundamentals that allow retailers to evolve with the necessary speed and agility – and that means superior systems and processes as well as a flexible and strong digital core.

In fact, with innovation cycles that are becoming five to 10 times faster, retailers need to start thinking about the digital core of their future value networks and start to connect consumers, suppliers, workforce, and the Internet of Things in real-time. The ability to capture every opportunity and leverage digital transformation for increased business value in an industry-specific manner is an exponential advantage. And it’s a solution that’s already available.

Want to know how retailers can create a compelling competitive advantage? Discover more here.

 

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Chong Mock Seng

About Chong Mock Seng

Chong Mock Seng is Retail Industry Leader of Southeast Asia for SAP. He has focused on retail, consumer products, and high tech manufacturing customers in the Asia-Pacific region and has a wealth of insights and practical experience through his myriad engagements in which he enjoys sharing with his customers in his current role as Retail IVE for Southeast Asia. He is most passionate about dialogues and action plans on transformative retail engineering in the disruptive digital era.

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.