Collaboration Tech Development Rests On Community-Enabled Innovation

James Penfold

The most recent findings of Gallup’s 2017 “State of the American Workplace” report opened my eyes to a potential opportunity for IT developers. A dramatic shift in the workforce, once viewed as a threat to the IT function, is now an open invitation for developers to flex their innovation muscle and add value to the employee experience.

According to Gallup, the percentage of employees engaged in remote workplaces has quadrupled over the last two decades, from only nine percent in 1996 to 37% in 2016. And this trend is expected to continue to escalate; Society for Human Resources Management research indicates that 60% of companies offer employees telecommuting opportunities – a threefold increase from the 20% who offered them in 1996.

This dramatic workforce shift is bringing a broad range of collaboration tools into the world of work. Because employees are empowered to work the way they want, they are purchasing and implementing their own technology, ranging from enterprise solutions to mobile apps and small team applications. But in reality, this move just undercuts the efficiencies and performance improvements that can only be realized through development innovation.

The desire for enterprise collaboration maturity opens the door to development opportunities

Enterprise collaboration is still happening outside of the solutions and tools used to access and analyze data. And it’s done for a justifiable reason: Very few of these technologies feature components that support it. Although designed to reduce barriers to information, more often than not enterprise collaboration tools reside in a tangled web of poorly integrated business applications and impenetrable information silos.

“As the level of acceptance of social technologies has increased over the past few years, the way we think about social business has undergone rapid change,” says Vanessa Thompson, research manager, Enterprise Social Networks and Collaborative Technologies, at IDC. “This change also comes with the confluence of a number of intersecting market trends – cloud, mobile, and Big Data. This exacerbates the ways we can use these new communication and collaboration channels to connect with employees, customers, partners, and suppliers in order to meet future potential needs.”

For developers, Thompson’s observation sends an urgent message to start looking at the existing IT landscape to determine where enterprise collaboration capabilities could add value to the way people work. Better yet, this may be an excellent opportunity to break down data silos that have plagued the business environment for decades.

Community-driven innovation paves the way to data democratization

After spending most of my career surrounded by developers, I have seen firsthand why successful change does not happen in a vacuum. Developers who leverage expert content, support, and innovative technology to extend enterprise investments are more likely to drive a competitive advantage that is valued by the business.

Through a community of innovators, developers can embed complementary interfaces in existing systems and applications to support the collaboration needs of any company, department, or industry. This environment should provide flexible capabilities including:

  • Customizable work patterns to address unique business demands and enable repeatable work
  • Integration of in-context business data from native and third-party systems with work patterns through APIs that help ensure that real-time data is available for assessment and decision making
  • Capabilities that are embedded through widgets to support enterprise collaboration in existing applications
  • Development of extension applications that take advantage of the power of the cloud platform based on in-memory computing to deliver rapid analysis, storage, transformation, and rendering

Development is an important part of integrating capabilities into existing software to create engaging experiences for employees of all levels and functions. However, it’s not innovation that should be done by scratch and alone. A community of expertise, best practices, content, and tools can help developers quickly set up a foundation for enterprise collaboration and devise new ways of work that reflect the business’ culture, preferred engagement models, and digital strategy.

Get started on your enterprise collaboration initiatives. Sign up for a free SAP Jam Collaboration, developer edition, and get full access to all of the capabilities of SAP Jam.


James Penfold

About James Penfold

James Penfold is Vice President of Business Development at SAP, responsible for the ISV and Developer Programs for SAP Jam. Prior to joining SAP, James managed the EMEA Web experience business for Akamai Technologies and was Senior Director of Applications Development (EMEA) for Oracle. James has more than 20 years’ technology leadership experience in product management, product marketing, and presales for global technology including Salesforce and Siebel Systems. James earned his BSc in Computer Science from the University of Portsmouth in conjunction with IBM.

The Rise Of The Dual-Role CIO Redefines Digital Commitment

Cristiano Barbieri

First of three blogs about SulAmérica and part of the “Digital CIO” series

Managing one line of business comes with many responsibilities and commitments. But CIOs who are leading their enterprises through massive changes enabled by technology may soon find themselves running two. That’s what I’ve been doing for the past two years at SulAmérica, and I’d like to share my experience with you.

Since 2010, I have been immersed in building SulAmérica’s digital capabilities to keep up with the fast pace of the insurance market here in Brazil. But over time, I began to realize that my IT domain was bleeding into other areas of the businesses, especially when it came to customer relationships. My executive team agreed, and in 2016, asked me to assume the additional strategic responsibilities for customer relationships across our contact center channels.

To manage these dual roles well, I run on a full schedule and heavy load of action items. But at the same time, I feel like a kid in Disneyland every day. This challenge is always evolving, mesmerizing, and fun.

And why not? SulAmérica is in the middle of the most significant transformation in its 123-year existence, which is enabling us to deliver the digital experiences that customers expect today without compromise.

Redefining a traditional business with next-generation values

Designating a single leader for both IT and customer relationships created an opportunity to experiment and find the right mix of technology, processes, and measurement for offering an engaging customer experience. And for us, this was the start of our transformation journey.

As the fourth-largest insurance company in Brazil, SulAmérica provides a full range of insurance and investment offerings – from life, health, property, casualty, and auto insurance to asset management – to 8 million customers across 25 states. IT is a highly regarded critical area for ensuring efficient execution of our core processes. However, changing customer behavior and their use of digital technology opened up an opportunity that is helping our 30,000 brokers and 5,000 internal employees create closer relationships with every customer.

This defining realization empowered my IT team and customer relationship team to work together to develop and execute a strategic initiative based on three fundamental principles:

1. Go cloud-first in everything we do

Cloud technology serves as the foundation for every digital initiative. As we moved our applications, data, and interactions to the cloud, we replaced 20 disparate legacy systems with a companywide, connected platform. Now, teams across the business are accessing and contributing to this network of knowledge and working together as a single unit.

2. Operate with a 360-degree view of every customer

After setting up our cloud platform, we created a master data management repository and customer relationship management platform that allows our employees and brokers to tap into a 360-degree view of every customer with one click. With this insight, they can offer our customers the right products, get their concerns resolved quickly, and assure them that their claims are processed fairly without unnecessary frustration.

No matter which channel they choose to engage us, our millions of customers know that the person at the other end of the interaction knows what they need. More importantly, every experience is just as productive and simple as the last.

3. Experiment for our digital future with an innovation garage

One of the keys to running as a successful digital business is fostering a culture of continuous innovation. While running in the cloud enables this capability, we needed a dedicated space to experiment and test innovative developments with tangible and measurable results – and without spending significant money, time, and resources on it.

Creating this space, which we call our innovation garage, allows technology experts to identify new opportunities for customers, as well as further differentiate our businesses in a highly competitive marketplace. However, this team resides by themselves, not within IT nor any other business area. Each member understands how to use digital thinking, apply prototyping, and look beyond business requirements to sense and respond to the real opportunity ahead.

Heading into a digital horizon of excellence and dynamism

Some people may say that embracing and enabling each of these three capabilities means that we are well underway in our digital transformation. However, I believe that we have only just begun. From the adoption of the cloud and a well-rounded view of the customer to the enablement of an innovation space, we have the foundation our business needs to perform and deliver competitively.

In a matter of weeks or even days, we are better equipped to fund and bring to market high-potential innovations – and know when to dismiss weaker ideas and which ones to pursue. But no matter the project, everything we do is aligned with our ultimate mission of customer proximity, transparency, excellence, and dynamism.

For more insight on IT leadership, see Hack The CIO.


Cristiano Barbieri

About Cristiano Barbieri

Cristiano Barbieri is chief information officer and head of customer relationships at SulAmerica Seguros. He has been leading the digital transformation of the company, spearheading important initiatives including "Transforming the Customer Experience," which created a 360-degree view of the customer, and "A New Customer Platform," totally cloud based. "A New Digital Customer Journey" recently launched where more than 2 million calls a year were transformed into digital interactions. He has also created an experimentation lab within the company named "Innovation Garage," another important initiative where culture transformation is the main goal and drives many innovative projects.

CRM In Today’s Ecosystem: What CIOs Need To Know

Riaz Faride

Companies these days usually choose to position themselves as an entity with purpose – a purpose reflecting customer-centricity beyond profit. They develop and commercialize their products accordingly, whether the products are architecturally interdependent or modular. In addition to market share, profitability, and earnings-per-share growth, measuring advocacy as a metric is trending, since it can be an indicator of positive customer experience. It is equally important as measuring satisfaction.

A customer relationship management (CRM) solution is an obvious choice for today’s leaders due to its capabilities of tracking the customer base and their experiences by channels and touch points. Combining CRM with a business intelligence (BI) tool adds significant value since it draws data from multiple sources and provides a business-focused analysis.

Leaping ahead with sophisticated functionality

Today’s CRM solutions are no longer limited to contact management, campaign management, lead management, deals and tasks, email and social media tracking; CRM has leaped beyond its traditional boundaries. Native capabilities or implementation readiness with marketing automation, online reputation management (ORM), and voice of the customer (VoC) solutions are some key options available for consideration by today’s leaders. This flexibility allows businesses to build relationships with unidentified viewers and their influencers, leads, customers, and even advocates of the products!

From a functionality perspective, selecting a CRM solution encompasses many criteria. These include the ability to mine, consolidate, and analyze data for better insights; scalability; high availability; intuitive and process-driven interface; mobile support, spanning the most commonly used device sizes and types; and operating systems. In this age, the need for responsive or adaptive mobile sites is paramount. All these factors are reflected through the architecture, features, and adaptability of a CRM solution. Thus, software lifecycle management and product roadmap should be evaluated during selection of a CRM solution.

Incorporating the latest technologies

CRM is being impacted by contextual customer service through chatbots. Predictive analysis of historical and live data through machine learning has influenced CRM, as well. Ditto virtual reality (VR), which allows customers to interact through software, and the Internet of Things (IoT), which greatly facilitates analysis of customers through real-time data from devices. Inversely, CRM has a meaningful impact on real-time personalization and connected experience.

CRM helps businesses look at their markets through different lenses. This allows them to offer their products that serve the “purpose” of their respective customer base: the task the customers are trying to accomplish or a problem or issue they want to resolve.

Businesses with mature products can leverage CRM and its extensions to define a winning strategy and help them determine success and failure criteria. CRM is also useful during the early phases of a company’s or product’s life, or when the future is unknown and the competitive landscape is changing. The mix of these two use cases is very common and dictates the need for a flexible, user-friendly, scalable CRM solution.

Protecting privacy and complying with regulatory mandates

While CRM in the cloud is gaining popularity exponentially, some decision-makers are still concerned about security and the privacy of customers, leads, and uncategorized users. This is understandable given the importance of compliance with data processing and privacy directives across multiple jurisdictions. In addition, IT leaders need to protect systems and data against vulnerabilities and ensure business continuity. Cloud providers can play an important consultative role during CRM planning and implementation – for example, recommending or providing managed services.

Learn more

For more information about solutions supporting customer engagement and commerce, and fully integrating marketing, commerce, sales, and service, please visit SAP Hybris.


Riaz Faride

About Riaz Faride

Riaz Faride joined SAP in 2017. Prior to this, he worked in the retail industry and had an extensive history in delivering high-value omnichannel projects. Throughout his career, Riaz has been exposed to all avenues of e-commerce, making him a subject matter expert. As a thought leader in his field, Riaz is a mentor for a number of professionals in e-commerce, omnichannel, and project management. He values ongoing learning and growth in both technical and non-technical fields.

The Blockchain Solution

By Gil Perez, Tom Raftery, Hans Thalbauer, Dan Wellers, and Fawn Fitter

In 2013, several UK supermarket chains discovered that products they were selling as beef were actually made at least partly—and in some cases, entirely—from horsemeat. The resulting uproar led to a series of product recalls, prompted stricter food testing, and spurred the European food industry to take a closer look at how unlabeled or mislabeled ingredients were finding their way into the food chain.

By 2020, a scandal like this will be eminently preventable.

The separation between bovine and equine will become immutable with Internet of Things (IoT) sensors, which will track the provenance and identity of every animal from stall to store, adding the data to a blockchain that anyone can check but no one can alter.

Food processing companies will be able to use that blockchain to confirm and label the contents of their products accordingly—down to the specific farms and animals represented in every individual package. That level of detail may be too much information for shoppers, but they will at least be able to trust that their meatballs come from the appropriate species.

The Spine of Digitalization

Keeping food safer and more traceable is just the beginning, however. Improvements in the supply chain, which have been incremental for decades despite billions of dollars of technology investments, are about to go exponential. Emerging technologies are converging to transform the supply chain from tactical to strategic, from an easily replicable commodity to a new source of competitive differentiation.

You may already be thinking about how to take advantage of blockchain technology, which makes data and transactions immutable, transparent, and verifiable (see “What Is Blockchain and How Does It Work?”). That will be a powerful tool to boost supply chain speed and efficiency—always a worthy goal, but hardly a disruptive one.

However, if you think of blockchain as the spine of digitalization and technologies such as AI, the IoT, 3D printing, autonomous vehicles, and drones as the limbs, you have a powerful supply chain body that can leapfrog ahead of its competition.

What Is Blockchain and How Does It Work?

Here’s why blockchain technology is critical to transforming the supply chain.

Blockchain is essentially a sequential, distributed ledger of transactions that is constantly updated on a global network of computers. The ownership and history of a transaction is embedded in the blockchain at the transaction’s earliest stages and verified at every subsequent stage.

A blockchain network uses vast amounts of computing power to encrypt the ledger as it’s being written. This makes it possible for every computer in the network to verify the transactions safely and transparently. The more organizations that participate in the ledger, the more complex and secure the encryption becomes, making it increasingly tamperproof.

Why does blockchain matter for the supply chain?

  • It enables the safe exchange of value without a central verifying partner, which makes transactions faster and less expensive.
  • It dramatically simplifies recordkeeping by establishing a single, authoritative view of the truth across all parties.
  • It builds a secure, immutable history and chain of custody as different parties handle the items being shipped, and it updates the relevant documentation.
  • By doing these things, blockchain allows companies to create smart contracts based on programmable business logic, which can execute themselves autonomously and thereby save time and money by reducing friction and intermediaries.

Hints of the Future

In the mid-1990s, when the World Wide Web was in its infancy, we had no idea that the internet would become so large and pervasive, nor that we’d find a way to carry it all in our pockets on small slabs of glass.

But we could tell that it had vast potential.

Today, with the combination of emerging technologies that promise to turbocharge digital transformation, we’re just beginning to see how we might turn the supply chain into a source of competitive advantage (see “What’s the Magic Combination?”).

What’s the Magic Combination?

Those who focus on blockchain in isolation will miss out on a much bigger supply chain opportunity.

Many experts believe emerging technologies will work with blockchain to digitalize the supply chain and create new business models:

  • Blockchain will provide the foundation of automated trust for all parties in the supply chain.
  • The IoT will link objects—from tiny devices to large machines—and generate data about status, locations, and transactions that will be recorded on the blockchain.
  • 3D printing will extend the supply chain to the customer’s doorstep with hyperlocal manufacturing of parts and products with IoT sensors built into the items and/or their packaging. Every manufactured object will be smart, connected, and able to communicate so that it can be tracked and traced as needed.
  • Big Data management tools will process all the information streaming in around the clock from IoT sensors.
  • AI and machine learning will analyze this enormous amount of data to reveal patterns and enable true predictability in every area of the supply chain.

Combining these technologies with powerful analytics tools to predict trends will make lack of visibility into the supply chain a thing of the past. Organizations will be able to examine a single machine across its entire lifecycle and identify areas where they can improve performance and increase return on investment. They’ll be able to follow and monitor every component of a product, from design through delivery and service. They’ll be able to trigger and track automated actions between and among partners and customers to provide customized transactions in real time based on real data.

After decades of talk about markets of one, companies will finally have the power to create them—at scale and profitably.

Amazon, for example, is becoming as much a logistics company as a retailer. Its ordering and delivery systems are so streamlined that its customers can launch and complete a same-day transaction with a push of a single IP-enabled button or a word to its ever-attentive AI device, Alexa. And this level of experimentation and innovation is bubbling up across industries.

Consider manufacturing, where the IoT is transforming automation inside already highly automated factories. Machine-to-machine communication is enabling robots to set up, provision, and unload equipment quickly and accurately with minimal human intervention. Meanwhile, sensors across the factory floor are already capable of gathering such information as how often each machine needs maintenance or how much raw material to order given current production trends.

Once they harvest enough data, businesses will be able to feed it through machine learning algorithms to identify trends that forecast future outcomes. At that point, the supply chain will start to become both automated and predictive. We’ll begin to see business models that include proactively scheduling maintenance, replacing parts just before they’re likely to break, and automatically ordering materials and initiating customer shipments.

Italian train operator Trenitalia, for example, has put IoT sensors on its locomotives and passenger cars and is using analytics and in-memory computing to gauge the health of its trains in real time, according to an article in Computer Weekly. “It is now possible to affordably collect huge amounts of data from hundreds of sensors in a single train, analyse that data in real time and detect problems before they actually happen,” Trenitalia’s CIO Danilo Gismondi told Computer Weekly.

Blockchain allows all the critical steps of the supply chain to go electronic and become irrefutably verifiable by all the critical parties within minutes: the seller and buyer, banks, logistics carriers, and import and export officials.

The project, which is scheduled to be completed in 2018, will change Trenitalia’s business model, allowing it to schedule more trips and make each one more profitable. The railway company will be able to better plan parts inventories and determine which lines are consistently performing poorly and need upgrades. The new system will save €100 million a year, according to ARC Advisory Group.

New business models continue to evolve as 3D printers become more sophisticated and affordable, making it possible to move the end of the supply chain closer to the customer. Companies can design parts and products in materials ranging from carbon fiber to chocolate and then print those items in their warehouse, at a conveniently located third-party vendor, or even on the client’s premises.

In addition to minimizing their shipping expenses and reducing fulfillment time, companies will be able to offer more personalized or customized items affordably in small quantities. For example, clothing retailer Ministry of Supply recently installed a 3D printer at its Boston store that enables it to make an article of clothing to a customer’s specifications in under 90 minutes, according to an article in Forbes.

This kind of highly distributed manufacturing has potential across many industries. It could even create a market for secure manufacturing for highly regulated sectors, allowing a manufacturer to transmit encrypted templates to printers in tightly protected locations, for example.

Meanwhile, organizations are investigating ways of using blockchain technology to authenticate, track and trace, automate, and otherwise manage transactions and interactions, both internally and within their vendor and customer networks. The ability to collect data, record it on the blockchain for immediate verification, and make that trustworthy data available for any application delivers indisputable value in any business context. The supply chain will be no exception.

Blockchain Is the Change Driver

The supply chain is configured as we know it today because it’s impossible to create a contract that accounts for every possible contingency. Consider cross-border financial transfers, which are so complex and must meet so many regulations that they require a tremendous number of intermediaries to plug the gaps: lawyers, accountants, customer service reps, warehouse operators, bankers, and more. By reducing that complexity, blockchain technology makes intermediaries less necessary—a transformation that is revolutionary even when measured only in cost savings.

“If you’re selling 100 items a minute, 24 hours a day, reducing the cost of the supply chain by just $1 per item saves you more than $52.5 million a year,” notes Dirk Lonser, SAP go-to-market leader at DXC Technology, an IT services company. “By replacing manual processes and multiple peer-to-peer connections through fax or e-mail with a single medium where everyone can exchange verified information instantaneously, blockchain will boost profit margins exponentially without raising prices or even increasing individual productivity.”

But the potential for blockchain extends far beyond cost cutting and streamlining, says Irfan Khan, CEO of supply chain management consulting and systems integration firm Bristlecone, a Mahindra Group company. It will give companies ways to differentiate.

“Blockchain will let enterprises more accurately trace faulty parts or products from end users back to factories for recalls,” Khan says. “It will streamline supplier onboarding, contracting, and management by creating an integrated platform that the company’s entire network can access in real time. It will give vendors secure, transparent visibility into inventory 24×7. And at a time when counterfeiting is a real concern in multiple industries, it will make it easy for both retailers and customers to check product authenticity.”

Blockchain allows all the critical steps of the supply chain to go electronic and become irrefutably verifiable by all the critical parties within minutes: the seller and buyer, banks, logistics carriers, and import and export officials. Although the key parts of the process remain the same as in today’s analog supply chain, performing them electronically with blockchain technology shortens each stage from hours or days to seconds while eliminating reams of wasteful paperwork. With goods moving that quickly, companies have ample room for designing new business models around manufacturing, service, and delivery.

Challenges on the Path to Adoption

For all this to work, however, the data on the blockchain must be correct from the beginning. The pills, produce, or parts on the delivery truck need to be the same as the items listed on the manifest at the loading dock. Every use case assumes that the data is accurate—and that will only happen when everything that’s manufactured is smart, connected, and able to self-verify automatically with the help of machine learning tuned to detect errors and potential fraud.

Companies are already seeing the possibilities of applying this bundle of emerging technologies to the supply chain. IDC projects that by 2021, at least 25% of Forbes Global 2000 (G2000) companies will use blockchain services as a foundation for digital trust at scale; 30% of top global manufacturers and retailers will do so by 2020. IDC also predicts that by 2020, up to 10% of pilot and production blockchain-distributed ledgers will incorporate data from IoT sensors.

Despite IDC’s optimism, though, the biggest barrier to adoption is the early stage level of enterprise use cases, particularly around blockchain. Currently, the sole significant enterprise blockchain production system is the virtual currency Bitcoin, which has unfortunately been tainted by its associations with speculation, dubious financial transactions, and the so-called dark web.

The technology is still in a sufficiently early stage that there’s significant uncertainty about its ability to handle the massive amounts of data a global enterprise supply chain generates daily. Never mind that it’s completely unregulated, with no global standard. There’s also a critical global shortage of experts who can explain emerging technologies like blockchain, the IoT, and machine learning to nontechnology industries and educate organizations in how the technologies can improve their supply chain processes. Finally, there is concern about how blockchain’s complex algorithms gobble computing power—and electricity (see “Blockchain Blackouts”).

Blockchain Blackouts

Blockchain is a power glutton. Can technology mediate the issue?

A major concern today is the enormous carbon footprint of the networks creating and solving the algorithmic problems that keep blockchains secure. Although virtual currency enthusiasts claim the problem is overstated, Michael Reed, head of blockchain technology for Intel, has been widely quoted as saying that the energy demands of blockchains are a significant drain on the world’s electricity resources.

Indeed, Wired magazine has estimated that by July 2019, the Bitcoin network alone will require more energy than the entire United States currently uses and that by February 2020 it will use as much electricity as the entire world does today.

Still, computing power is becoming more energy efficient by the day and sticking with paperwork will become too slow, so experts—Intel’s Reed among them—consider this a solvable problem.

“We don’t know yet what the market will adopt. In a decade, it might be status quo or best practice, or it could be the next Betamax, a great technology for which there was no demand,” Lonser says. “Even highly regulated industries that need greater transparency in the entire supply chain are moving fairly slowly.”

Blockchain will require acceptance by a critical mass of companies, governments, and other organizations before it displaces paper documentation. It’s a chicken-and-egg issue: multiple companies need to adopt these technologies at the same time so they can build a blockchain to exchange information, yet getting multiple companies to do anything simultaneously is a challenge. Some early initiatives are already underway, though:

  • A London-based startup called Everledger is using blockchain and IoT technology to track the provenance, ownership, and lifecycles of valuable assets. The company began by tracking diamonds from mine to jewelry using roughly 200 different characteristics, with a goal of stopping both the demand for and the supply of “conflict diamonds”—diamonds mined in war zones and sold to finance insurgencies. It has since expanded to cover wine, artwork, and other high-value items to prevent fraud and verify authenticity.
  • In September 2017, SAP announced the creation of its SAP Leonardo Blockchain Co-Innovation program, a group of 27 enterprise customers interested in co-innovating around blockchain and creating business buy-in. The diverse group of participants includes management and technology services companies Capgemini and Deloitte, cosmetics company Natura Cosméticos S.A., and Moog Inc., a manufacturer of precision motion control systems.
  • Two of Europe’s largest shipping ports—Rotterdam and Antwerp—are working on blockchain projects to streamline interaction with port customers. The Antwerp terminal authority says eliminating paperwork could cut the costs of container transport by as much as 50%.
  • The Chinese online shopping behemoth Alibaba is experimenting with blockchain to verify the authenticity of food products and catch counterfeits before they endanger people’s health and lives.
  • Technology and transportation executives have teamed up to create the Blockchain in Transport Alliance (BiTA), a forum for developing blockchain standards and education for the freight industry.

It’s likely that the first blockchain-based enterprise supply chain use case will emerge in the next year among companies that see it as an opportunity to bolster their legal compliance and improve business processes. Once that happens, expect others to follow.

Customers Will Expect Change

It’s only a matter of time before the supply chain becomes a competitive driver. The question for today’s enterprises is how to prepare for the shift. Customers are going to expect constant, granular visibility into their transactions and faster, more customized service every step of the way. Organizations will need to be ready to meet those expectations.

If organizations have manual business processes that could never be automated before, now is the time to see if it’s possible. Organizations that have made initial investments in emerging technologies are looking at how their pilot projects are paying off and where they might extend to the supply chain. They are starting to think creatively about how to combine technologies to offer a product, service, or business model not possible before.

A manufacturer will load a self-driving truck with a 3D printer capable of creating a customer’s ordered item en route to delivering it. A vendor will capture the market for a socially responsible product by allowing its customers to track the product’s production and verify that none of its subcontractors use slave labor. And a supermarket chain will win over customers by persuading them that their choice of supermarket is also a choice between being certain of what’s in their food and simply hoping that what’s on the label matches what’s inside.

At that point, a smart supply chain won’t just be a competitive edge. It will become a competitive necessity. D!

About the Authors

Gil Perez is Senior Vice President, Internet of Things and Digital Supply Chain, at SAP.

Tom Raftery is Global Vice President, Futurist, and Internet of Things Evangelist, at SAP.

Hans Thalbauer is Senior Vice President, Internet of Things and Digital Supply Chain, at SAP.

Dan Wellers is Global Lead, Digital Futures, at SAP.

Fawn Fitter is a freelance writer specializing in business and technology.

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.



The Differences Between Machine Learning And Predictive Analytics

Shaily Kumar

Many people are confused about the specifics of machine learning and predictive analytics. Although they are both centered on efficient data processing, there are many differences.

Machine learning

Machine learning is a method of computational learning underlying most artificial intelligence (AI) applications. In ML, systems or algorithms improve themselves through data experience without relying on explicit programming. ML algorithms are wide-ranging tools capable of carrying out predictions while simultaneously learning from over trillions of observations.

Machine learning is considered a modern-day extension of predictive analytics. Efficient pattern recognition and self-learning are the backbones of ML models, which automatically evolve based on changing patterns in order to enable appropriate actions.

Many companies today depend on machine learning algorithms to better understand their clients and potential revenue opportunities. Hundreds of existing and newly developed machine learning algorithms are applied to derive high-end predictions that guide real-time decisions with less reliance on human intervention.

Business application of machine learning: employee satisfaction

One common, uncomplicated, yet successful business application of machine learning is measuring real-time employee satisfaction.

Machine learning applications can be highly complex, but one that’s both simple and very useful for business is a machine learning algorithm that compares employee satisfaction ratings to salaries. Instead of plotting a predictive satisfaction curve against salary figures for various employees, as predictive analytics would suggest, the algorithm assimilates huge amounts of random training data upon entry, and the prediction results are affected by any added training data to produce real-time accuracy and more helpful predictions.

This machine learning algorithm employs self-learning and automated recalibration in response to pattern changes in the training data, making machine learning more reliable for real-time predictions than other AI concepts. Repeatedly increasing or updating the bulk of training data guarantees better predictions.

Machine learning can also be implemented in image classification and facial recognition with deep learning and neural network techniques.

Predictive analytics

Predictive analytics can be defined as the procedure of condensing huge volumes of data into information that humans can understand and use. Basic descriptive analytic techniques include averages and counts. Descriptive analytics based on obtaining information from past events has evolved into predictive analytics, which attempts to predict the future based on historical data.

This concept applies complex techniques of classical statistics, like regression and decision trees, to provide credible answers to queries such as: ‘’How exactly will my sales be influenced by a 10% increase in advertising expenditure?’’ This leads to simulations and “what-if” analyses for users to learn more.

All predictive analytics applications involve three fundamental components:

  • Data: The effectiveness of every predictive model strongly depends on the quality of the historical data it processes.
  • Statistical modeling: Includes the various statistical techniques ranging from basic to complex functions used for the derivation of meaning, insight, and inference. Regression is the most commonly used statistical technique.
  • Assumptions: The conclusions drawn from collected and analyzed data usually assume the future will follow a pattern related to the past.

Data analysis is crucial for any business en route to success, and predictive analytics can be applied in numerous ways to enhance business productivity. These include things like marketing campaign optimization, risk assessment, market analysis, and fraud detection.

Business application of predictive analytics: marketing campaign optimization

In the past, valuable marketing campaign resources were wasted by businesses using instincts alone to try to capture market niches. Today, many predictive analytic strategies help businesses identify, engage, and secure suitable markets for their services and products, driving greater efficiency into marketing campaigns.

A clear application is using visitors’ search history and usage patterns on e-commerce websites to make product recommendations. Sites like Amazon increase their chance of sales by recommending products based on specific consumer interests. Predictive analytics now plays a vital role in the marketing operations of real estate, insurance, retail, and almost every other sector.

How machine learning and predictive analytics are related

While businesses must understand the differences between machine learning and predictive analytics, it’s just as important to know how they are related. Basically, machine learning is a predictive analytics branch. Despite having similar aims and processes, there are two main differences between them:

  • Machine learning works out predictions and recalibrates models in real-time automatically after design. Meanwhile, predictive analytics works strictly on “cause” data and must be refreshed with “change” data.
  • Unlike machine learning, predictive analytics still relies on human experts to work out and test the associations between cause and outcome.

Explore machine learning applications and AI software with SAP Leonardo.


Shaily Kumar

About Shaily Kumar

Shailendra has been on a quest to help organisations make money out of data and has generated an incremental value of over one billion dollars through analytics and cognitive processes. With a global experience of more than two decades, Shailendra has worked with a myriad of Corporations, Consulting Services and Software Companies in various industries like Retail, Telecommunications, Financial Services and Travel - to help them realise incremental value hidden in zettabytes of data. He has published multiple articles in international journals about Analytics and Cognitive Solutions; and recently published “Making Money out of Data” which showcases five business stories from various industries on how successful companies make millions of dollars in incremental value using analytics. Prior to joining SAP, Shailendra was Partner / Analytics & Cognitive Leader, Asia at IBM where he drove the cognitive business across Asia. Before joining IBM, he was the Managing Director and Analytics Lead at Accenture delivering value to its clients across Australia and New Zealand. Coming from the industry, Shailendra held key Executive positions driving analytics at Woolworths and Coles in the past.