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How Is Your Digital Transformation Going?

Iver van de Zand

If you haven’t read about the digital transformation last year, you might have had a wi-fi connection issue. Digital transformation is everywhere. Connected networks provide access to new (un)structured data. In-memory platforms provide the capabilities to process stunning amounts of information, and the Internet of Things allows us to connect and follow to almost any device or object.

Digital transformation is about the use of technology to radically improve the performance and reach of enterprises. Digital transformation is also about change and adapting to turn technological capabilities into transformation.

How are enterprises doing with digital transformation today? What are they focusing on, and where do they see opportunities? Time to write up a status of digital transformation and examine where are we today and what we can expect in the near future.

Digital transformation in 2016

To get a grip on where enterprises are with digital transformation and—more importantly—what they plan to do with it in 2016, I consulted briefings from IDC, Gartner, and Forrester. These are well-grounded and provide good insights. Here are some predictions from those insights:

  • The various initiatives on digital transformation within enterprises will be consolidated into one “digital vision” showing how their businesses will generate revenue by delivering new digital experiences.
    • Next year, it’s expected that 60% of enterprises that have a digital strategy will raise it to top priority and even assign an executive to oversee the implementation.
    • 67% of the Global 2000 enterprises will have digital transformation at the center of their corporate strategy in 2018.
  • Rising customer expectations will force business-to-business (B2B) enterprises to close the digital gap with business-to-consumer (B2C) enterprises (today B2C market segments are in the lead when it comes to digital transformation).
  • With 35% in 2018 (and 50% in 2020), IT budgets will shift onto the creation of new digital revenue streams. This will have a huge impact on HR, since access to talent at the right moment and place becomes a big differentiator.
  • Digital skills like mobile app development, business analytics (yoohoo J) and design thinking will become the “new normal” for software development.
  • Since this brings a greater reliance on IT and its budget, the IT’s budget for governance, risk, and compliance (GRC) staff will increase by 10% in 2017.
  • Interactive exploration of Big Data analytics becomes the foundation of digital transformation.
  • A successful adoption of digital transformation will lead to newly established data streams in and out of the organization and the monetization of them.
  • The growth engine of digital transformation will be the Internet of Things (IoT).
    • Greatly expanding the range of digital interactions between the consumer and the enterprise, 2018 will bring 22 billion (!) IoT devices driving the development of more than 20,000 new IoT apps.
    • The support for almost 6 billion connected “things” will create new business models for support services.
    • Even more dazzling, it’s expected that in 2020, 1 million new connected “things” will come online every single hour.
    • Competitive advantage will be redefined by IoT devices and by consumers interact with them.
  • Predictive analytics will continue to rise.
    • It’s expected that in 2018, at least 20% of all workers in some way will use automated assistance technologies for their decisions. These technologies are driven by new algorithms and predictive models.
    • By 2020, it’s expected that 5% of all economical transactions will have some automated software agents participating. These agents are outside human control.

Where customers see opportunities for digital transformation

It’s interesting to hear what customers see as opportunities as part of the digital transformation. Recent studies from IDC, Gartner, CapGemini, and Forrester showed that customers see three domains with opportunities taken from the digital transformation:

  1. Digitally transforming customer experience
  2. Digitally transforming operational processes
  3. Digitally transforming business models

Let’s sort these out a bit more.

Digital Transformation.2

Transforming customer experience

My customers see three areas of opportunities when digitally transforming their customer’s experience:

  • Customer understanding

The majority of the enterprises will use business analytics capabilities to better understand their customers. In-memory computing, Big Data and business analytics, and the closed-loop portfolio are just three examples of how they plan do this. Self-service BI also helps to quickly assess new sources of data and gain valuable insights. Other initiatives include more effective promotion of brands through digital media and further exploration of social media data and GEO-based data.

  • Top-line growth

Many enterprises plan to start using digital technology to enhance in-person conversations. The aim is to have applications that allow salespersons to have customer-tailored functionality and data that transforms the selling process into a better customer experience. One example is an app that has customer purchasing data embedded to provide more personalized sales.

  • Customer touchpoints

More digital touchpoints for customers prevents the necessary physical contact customers have with their suppliers. Governments are creating massive electronic desks, like portals that act like a landing zone for citizens to request information, and enterprises are providing media apps to help customers find interesting places in cities they visit.

Transforming operational processes

Though transformed customer experiences are more visible and probably more exciting, the opportunities to transform operational processes due to digital transformation cannot be underestimated. Here are some examples of where customers see opportunities to transform operational processes:

1. Process digitization

Digitalized automation of processes has many flavors, but they all aim to free up resources to focus on more strategic activities. Many examples can be found in the area of shortening and simplifying product development cycles.

2. Workers’ enablement

Separating work processes from work location while also transforming collaboration processes is something I have heard many times. This is obvious, since today’s cloud capabilities facilitate this transformation perfectly.

3. Enterprise performance management and the closed-loop portfolio

Transforming into a closed-loop portfolio for analytics and performance management is also on the list of opportunities customers see to transform operational processes. The availability of real-time insights at the highest-detailed level available – in a governed way – for all applicable people is a huge opportunity. It saves everlasting discussions on both the availability and the quality of insights.

Transforming business models

Applying the digital transformation brings new opportunities for digitalizing business models or even creating new ones:

1. Digitally modified businesses

Integrated and in-memory platforms are big facilitators for digitally modifying businesses. One obvious example is growing e-commerce platforms. But there are many more examples of how the Internet of Things (IoT) will radically change and modify business processes: A hotel group that uses IoT devices to check each room’s supply of toilet paper instead of sending personnel, or a tire company putting “connected things” in their tires to measure the tire condition, just to name a few. Huge opportunities are found in this space of business models.

2. New digital business

Digitally modifying businesses almost automatically implies finding new business models. Have a look at these examples from the finance & insurance sector, in which the modification of the business process is to use “connected things” to link to an insured object, but the new process is the partner network for preventive maintenance of the insured objects. Another example is the tire company mentioned about that applies a new business model to sell back (!) its IoT data to transport companies who can use the data to improve their maintenance and service.

3. Digital globalization

Enterprises are increasingly transforming from multinational to truly global operations. Digital technology, coupled with closed-loop analytics, allows businesses to gain global synergies while remaining locally responsive. These enterprises benefit from global shared services for finance, HR, and even core capabilities like manufacturing and design. Global shared services promote efficiency and reduce risk. They even promote global flexibility. One manufacturer can shift production around the globe with only a few days’ notice in response to interruptions or excess demand.

Digital transformation requires strong leadership to drive change. But it also requires a vision for what parts of the company you want to transform.

Companies in all industries and regions are experimenting with—and benefiting from—digital transformation. Whether it’s in the way individuals work and collaborate, how business processes are executed within and across organizational boundaries, or how a company understands and serves customers, digital technology provides a wealth of opportunity.

Want more insight on digital transformation? See 5 Digital Trends Changing Business And Enabling The Possible and visit discover.sap.com/hana.

Follow me on Twitter @IverVandeZand.

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Iver van de Zand

About Iver van de Zand

Iver van de Zand is a Business Analytics Leader at SAP responsible for Business Analytics with a special attention towards Business Intelligence Suite, Lumira and Predictive Analytics.

Smart Machines Create Markets For Cyber-Physical Advances

Marion Heindenreich

Today, industrial machines are more intelligent than ever before. These intelligent machines are changing companies in many ways.

Why smart machines?

Mobile networked computers were a key breakthrough for making smart machines. Big Data allows machines and computers to store information and analyze complex patterns. Cloud computing offers broad access to information and more storage.

These computerized machines are both physical and virtual. Some call them “cyber-physical” machines. Technology lets them be self-aware and connected to each other and larger systems.

Businesses change their approaches

Intelligent machines allow companies to innovate in many areas. For one, the value proposition for customers is evolving. Businesses now model and plan in different ways in many industries.

Makers of industrial machines and parts work in new ways within the organization. Engineering now partners with mechanical, electronic, and software staff to develop new products. Manufacturing now seamlessly ties what happens on the shop floor to the customer.

Service models are changing too. Scheduled and reactionary servicing of machines is fading. Now intelligent machines track themselves. Machines detect problems and report them automatically. Major problems or failures are predicted and reported.

A data mining example

One good industrial example is mining, which can be dangerous and difficult. As ores become scarce, the costs of mining have increased.

“Smart machines” started in mining in the late 1990s. Software and hardware let remote users change settings. Operators moved hydraulic levers from a safe distance. Sensors observed performance and diagnosed issues.

Data cables connected machines to computers on the surface. Continuous and remote monitoring of the machines grew. Over time, embedded sensors helped improve monitoring, diagnostics, and data storage.

The technology means workers only go underground to fix specific issues. As a result, accident and injury risk is lower.

New wireless technology now lets mining companies connect data from many mine sites. Service centers access large amounts of data and can improve performance. Maintenance is prioritized and equipment downtime is reduced.

Opportunity abounds

For companies the time is now. Today, mobile “connected things” generate 17% of the digital universe. By 2020 that share grows to 27%.

You might not be investing in this so-called “Internet of Things” (devices that connect to each other). But it’s a good bet your competitors are. A December 2015 study reported 33% of industrial companies are investing in the Internet of Things. Another 25% are considering it.

There are risks

This new dawning era of manufacturing is exciting. But there are concerns. Cyber attacks on the Internet of Things are not new. But as the use of intelligent machines grows, the threat of cyber attacks in industry grows.

Data confidentiality and privacy are concerns. So too are software and hardware vulnerabilities. Exposure to attack lies not just in the virtual space but the physical too. Tampering with unattended machines and theft pose serious risk.

To address these threats, industries must invest in cybersecurity along with smart machines.

Conclusion

The potential advantages of smart machines are staggering. They can reshape industries and change how companies produce new products and create new markets.

For more information, please download the white paper Digital Manufacturing: Powering the Fourth Industrial Revolution.

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Marion Heindenreich

About Marion Heindenreich

Marion Heidenreich is a solution manager for the SAP Industrial Machinery and Components Business Unit who focuses on solution innovations like Product Costing on SAP HANA and cloud solutions, as well as providing financial and business analysis for industry business strategy definition and business planning.

Mining Firms Turn To Tech

Ruediger Schroedter

Gone are the days in mining when assessments of potential dig sites meant lots of waiting for results. Gone, too, is the uncertainty on a mine job about where to go next.

For mining executives, recent advances in digital technology allow companies to make decisions at a rapid pace. Decisions that used to take days and weeks now can be done in minutes and hours.

With more information available faster, mining leaders reduce both short- and long-term financial risk. Data from across the enterprise inform decisions about buying and selling assets. Profitability should increase, driven by key technology advances.

Digging in to the data

There are two key drivers to this digital revolution. The first is the rise of the Internet of Things (IoT). The IoT consists of devices that are equipped with sensors, software, and wireless capabilities. These devices are connected to each other and can detect, store, and send data.

Bonus: Click here to learn more about Digital Transformation in Mining.

The second is the rise of Big Data, mobile, and cloud computing. Today’s mobile devices can track, send, and receive data from remote sites worldwide. Cloud computing stores billions of bytes of data at low cost. Big Data analytics programs take data coming from many different locations and systems and synthesize it. Those programs then better inform decisions by offering dashboards, metrics, and predictive modeling.

Robots are able to venture into hazardous areas and move material with remote human oversight. On-site mining data is sent via mobile phone to a cloud-based platform. For mining, the convergence of these technologies provides extraordinary possibilities.

Technology at play

The potential impact is significant. A recent report by McKinsey & Co. showed the use of advanced analytics in mining and related industries had a major impact. Firms using these programs to assess production areas increased their profit margins by 2-3 percentage points.

One mining company used so-called Monte Carlo simulations to reduce certain capital expenses. Monte Carlo simulations use complex algorithms and repeated random sampling to model possible outcomes. They’re frequently used in finance, biology, and insurance. The Mining Journal reported how the company challenged assumptions about a project’s capital needs. It took historical data on certain disruptions such as rainfall patterns. Then models of its mines were made showing the impact of flooding and rainwater. The data led to a new strategy that maximized storage capacity and handling across all its mines. Capital costs dropped by 20 percent.

18 Aug 2012, South Dakota, USA --- USA, South Dakota, Lead, View of open pit --- Image by © Bryan Mullennix/Tetra Images/Corbis

Buy or sell?

With so many variables at play, mining valuation is not for the faint of heart. Integrated data streams available at the discovery stage make for better informed purchase decisions.

Software programs today can take data to build and validate exploration models. These programs use 3D visualization and validated geophysical, analytical, and drill hole data. In turn, detailed 3D topographical models are possible.

Other programs assess historical, assay, and drilling data. This information creates viable scenarios for determining whether to buy or sell a site.

These tools use data consistently from one potential site to the next, allowing for forecasting of economic risk that is consistent across the organization. The firm today can use “real options valuation” to develop models of outcomes given changing economic conditions. With clearer information about potential risks, firms can decide whether to stage, sell, abandon, expand, or buy.

Anticipating, not reacting

Mining companies realize today that these analytic platforms and dashboards offer many advantages. Users have a clearer interpretation of the aggregated and analyzed data points from multiple areas. Using predictive analytics, mining decisions are made based on smart assumptions, not past historical information.

Robust software programs can generate reports almost instantaneously. Supervisors have on-site access to the analysis through a web browser or app. This data has many uses. Drilling managers save time and can make quicker decisions on next moves. Supplies can be ordered faster. Needed data for accreditation and compliance is immediately accessible.

Selecting the right sites

One example is assay analysis. Today, geologists do not wait weeks or months for assay results. Instead of off-site analysis, web-based applications deliver information much faster to inform decisions.

Robots are sending information about field operations, safety, needed maintenance, and drilling performance.  Some devices send the information themselves. In other cases, staff use mobile phones, tablets, or laptops.  This information and analytics in turn help with site selection. Integrating data from mine planning, ventilation, safety, rock engineering, and mineral resources improves overall forecasting.

Discovery, particularly of Tier 1 sites, is an increasingly costly venture for mining companies. Demand for many products is increasing while discovery rates are dropping. Mined product is of a lesser quality, particularly in mature mining locations. Many possible sites are in areas that are underexplored areas with difficult and deep cover.

The advanced technologies available today are contributing to rapid improvement in these discovery issues.

Prospective drilling

Consider the drill hole. To reduce costs in exploration, there needs to be enough rich information from the opening drill hole. It needs to be delivered in as close to real time as possible. Doing so lessens the risk of the second drill hole. Better information from the start helps improve vectoring. It provides better information about what mineral systems are being drilled.

This approach, called prospective drilling, is becoming increasingly used in mining. It employs drilling activity to map covered mineral systems. In turn, geochemical and geophysical vectoring can lead firms toward deposits.

Australia has invested heavily in this area. The Deep Exploration Technologies Cooperative Research Centre (DET CRC) has a singular vision: uncovering the future. Its core purpose is “develop transformational technologies for successful mineral exploration through deep, barren cover rocks.”

To get to that point, the DET CRC is borrowing a drilling technique from the oil business. Coiled tubing is paired with downhole and top-of-the-hole sensors. The informaton provides petrophysical, structural, rock fabric, geochemical, and mineralogical data all at once.

Conclusion

To meet increasing demands for new viable sites, and to improve efficient on sites, mining is changing. Using smart, connected products and robust data modeling, mining is being done faster, safer, and more efficiently than ever.

Join a LiveTwitterChat on digitalization in mining on May 4th from 10-11 a.m. EST: #digitalmining

The global mining and metals industry will come together to discuss how digital innovation is impacting the mining industry July 12-14 at the International SAP Conference for Mining and Metals in Frankfurt, Germany.  Don’t miss this opportunity to meet with world leaders and learn how your organization can become a connected digital enterprise.

Follow speakers and pre-event activities by following sapmmconf and @sapmillmining on Twitter

AA Mining and Metals Forum

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Ruediger Schroedter

About Ruediger Schroedter

Ruediger Schroedter is responsible for solution management of SAP solutions for the mining industry worldwide. He has spent more than 15 years in the mill products and mining industries and has extensive experience implementing SAP solutions for customers in these industries before coming to SAP.

Live Businesses Deliver a Personal Customer Experience Without Losing Trust

Lori Mitchell-Keller, Brian Walker, Johann Wrede, Polly Traylor, and Stephanie Overby

Trust is the foundation of customer relationships. People who don’t trust your business are not likely to become or remain customers.

The trust relationship has taken some big hits lately. Beloved brands like Chipotle and Toyota have seen customer trust ebb due to public perception of their roles in safety issues. Consumers continue to experience occasional data breaches from large brands.

Yet these traditional threats have short half-lives. The latest threat could last forever.

Most customers claim they want personalization across all the channels in which they interact with companies. Such personalization should create long-term loyalty by creating a new level of intimacy in the relationship.

sap_Q216_digital_double_feature3_images2But that intimacy comes at a high price. For personalization to work, brands need to gather unprecedented amounts of personal information about customers and continue to do so over the course of the relationship. Customers are already wary: 80% of consumers have updated their privacy settings recently, according to an article in VentureBeat.

Companies must get personalization right. If they do, customers are more likely to purchase again and less likely to switch to a competitor. Personalization is also an important step toward the holy grail of digital transformation: becoming a Live Business, capable of meeting customers with relevant and customized offers, products, and services in real time or in the moments of customers’ choosing.

When done wrong, personalization can cause customers to feel that they’ve been deceived and that their privacy has been violated. It can also turn into an uncomfortable headline. When Target used its database of customer purchases to send coupons for diapers to the home of an expectant teen before her father knew about the pregnancy, its action backfired. The incident became the centerpiece of a New York Times story on Target’s consumer intelligence gathering practices and privacy.

Straddling the Line of Trust

Customers can’t define the line between helpful and creepy, but they know it when they see it.

Research conducted by RichRelevance in 2015 made something abundantly clear: what marketers think is cool may be seen as creepy by consumers. For example, facial-recognition technology that identifies age and gender to target advertisements on digital screens is considered creepy by 73% of people surveyed. Yet consumers were happy about scanning a product on their mobile device to see product reviews and recommendations for other items they might like, the survey revealed. Here’s what else resonates as creepy or cool when it comes to digital engagement with consumers, courtesy of RichRelevance and Edelman Berland (now called Edelman).

Creepy

  • Shoppers are put off when salespeople greet them by name because of mobile phone signals or know their spending habits because of facial-recognition software.
  • Dynamic pricing, such as a digital display showing a lower price “just for you,” also puts shoppers off.
  • When brands collect data on consumers without their knowledge, 83% of people consider it an invasion of privacy, according to RichRelevance’s research, and 65% feel the same way about ads that follow them from Web site to Web site (retargeting).

Cool

  • Shoppers like mobile apps with interactive maps that efficiently guide them to products in the store.
  • They also like when their in-store location triggers a coupon or other promotion for a product nearby.
  • When a Web site reminds the consumer of past purchases, a majority of shoppers like it.

There are no hard-and-fast rules about which personalization tactics are creepy and which are cool, but trust is particularly threatened in face-to-face interactions. Nobody minds much if Amazon sends product recommendations through a computer, but when salespeople approach customers like a long-lost friend based on information collected without the customer’s knowledge or permission, the violation of trust feels much more personal and emotional. The stage is set for an angry, embarrassed customer to walk out  the door, forever.

sap_Q216_digital_double_feature3_images3It doesn’t help that the limits of trust shift constantly as social media tempts us to reveal more and more about ourselves and as companies’ data collection techniques continue to improve. It’s easy to cross the line from helpful to creepy or annoying (see Straddling the Line of Trust).

Online, customers are similarly choosy about personalization. For example, when online shoppers are simply looking at a product category, ads that matched their prior Web-browsing interests are ineffective, an MIT study reports. Yet after consumers have visited a review site to seek out information and are closer to a purchase, personalized content is more effective than generic ads.

Personalization Requires a Live Business

Yet the limits of trust are definitely shifting toward more personalization, not less. Customers already enjoy frictionless personalized experiences with digital-native companies like Uber, and they are applying those heightened expectations to all companies. For example, 91% of customers want to pick up where they left off when they switch between channels, according to Aspect research. And personalization is helpful when you receive recommendations for products that you would like based on previous in-store or online purchases.

sap_Q216_digital_double_feature3_images-0004Customers also want their interactions to be live—or in the moment they choose. Fulfilling that need means that companies must become Live Businesses, capable of creating a technological infrastructure that allows real-time interactions and that allows the entire organization—its structure, people, and processes—to respond to customers in all the moments that matter.

Coordinating across channels and meeting customers in the right moments with personalized interactions will become critical as the digital economy matures and customer expectations rise. For instance, when customers air complaints about a brand on social media, 72% expect a response within an hour, according to consulting firm Bain & Company. Meanwhile, an Accenture survey found that nearly 60% of consumers want real-time promotions; 48% like online reminders to order items that they might have run out of; and 51% like the idea of a one-click checkout, where they can skip payment method or shipping forms because the retailer has saved their preferences. Those types of services build trust, showing that companies care enough to understand their customers and send offers or information that save them time, money, or both.

So while trust is difficult to earn, once you’ve earned it and figured out how to maintain it, you can have customers for life—as long as you respect the shifting boundaries.

“Do customers think the company is truly acting with their best interests at heart, or is it just trying to feed the quarterly earnings beast?” asks Donna Peeples, a customer experience expert and the former chief customer experience officer at AIG. “Customer data should be accurate and timely, the company should be transparent about how the data is being used, and it should give customers control over data collection.”

sap_Q216_digital_double_feature3_images-0005How to Earn Trust for a Live Business

Despite spending US$600 billion on online purchases, U.S. consumers are concerned with transaction privacy, the 2015 Consumer Trust Survey from CA Security Council reveals. These concerns will become acute as Live Businesses make personalization across channels a reality.

Here are some ways to improve trust while moving forward with omnichannel personalization.

  • Determine the value of trust. Customers want to know what value they are getting in exchange for their data. An Accenture study found that the majority of consumers in the United States and the United Kingdom are willing to have trusted retailers use some of their personal data in order to present personalized and targeted products, services, recommendations, and offers.
    “If customers get substantial discounts or offers that are appealing to them, they are often more than willing to make that trade-off,” says Tom Davenport, author of Big Data at Work: Dispelling the Myths, Uncovering the Opportunities. “But a lot of companies are cheap. They use the information but don’t give anything back. They make offers that aren’t particularly relevant or useful. They don’t give discounts for loyalty. They’re just trying to sell more.”
  • Let customers make the first move. Customers who voluntarily give up data are more likely to trust personalization across the channels where they do business. Mobile apps are a great way to invite customers to share more data in a more intimate relationship that they control. By entering the data they choose into the app, customers won’t be annoyed by personalization that’s built around it.
    For example, a leading luxury retailer’s sales associates may offer customers their favorite beverages based on information they entered into the app about their interests and preferences.
  • Simplify data collection and usage policies. Slapping a dense data- use policy written in legalese on the corporate website does little to earn customers’ trust. Instead, companies should think about the customer data transaction, such as what information the customer is giving them, how they’re using it, and what the result will be, and describe it as simply as possible.
    “Try to describe it in words so simple that your grandmother can understand it. And then ask your grandmother if it’s reasonable,” suggests Elea McDonnell Feit, assistant professor of marketing at Drexel University’s LeBow College of Business. “If your grandmother can’t understand what’s happening, you’ve got a problem.”
    The use of data should be totally transparent in the interaction itself, adds Feit. “When a company uses data to customize a service or offering to a customer, the customer should be able to figure out where the company got the data and immediately see how the company is providing added value to the customers by using the data,” Feit says.
  • Create trust through education. Yes, bombarding customers with generic offers and pushing those offers across the different Web sites they visit may boost profits over the short term, but customers will eventually become weary and mistrustful. To create trust that lasts and that supports personalization, educate the customers.

Procter & Gamble’s (P&G’s) Mean Stinks campaign for Secret deodorant encourages girl-to-girl anti-bullying posts on Twitter, Facebook, and Instagram. The pages let participants send apologies to those they have bullied; view videos; and share tips, tools, and challenges with their peers.

P&G has said that participation in Mean Stinks has helped drive market share increases for the core Secret brand as well as the specific line of deodorant promoted by the effort. Offering education without pushing products or services creates a sense that companies are putting customers’ interests before their own, which is one of the bedrock elements of trust. Opting in to personalization seems less risky to customers if they perceive that companies have built up a reserve of value and trust.

“Companies that do personalization well demonstrate that they care, respect customers’ time, know and understand their customers and their needs and interests,” says Peeples. “It also reinforces that interactions are not merely transactions but opportunities to build a long-term relationship with that customer.”

Laying the Foundation for Live, Personalized Omnichannel Processes

sap_Q216_digital_double_feature3_images-0006Creating a personalized omnichannel strategy that balances trust and business goals starts with knowing the customer. This can happen only when multiple aspects of your business are coordinated in a live fashion. But marketers today struggle to collect the kind of data that could drive more meaningful connections with customers. In an Infogroup survey of more than 500 marketers, only 21% said they are “very confident in the accuracy and completeness of their customer profiles.” A little over half of respondents said they aren’t collecting enough data overall.

Collecting enough of the right types of data requires more holistic data-collection techniques:

  • Take advantage of the lower costs for processing and storing terabytes of data, and develop a data strategy that combines and crunches all the customer data points needed to drive relevant interactions. This includes transactional, mobile, sensor, and  Web data.
  • Social media analytics is also a central tactic. Social profiles and activity are rich sources of data about behavior and character, merging what people buy or look for with their interests, for instance. Such data can feed predictive analytics and personalization campaigns.
  • Experiment with commercial tools that can filter and mine the data of customers and prospects in real time. This is a significant step beyond basic demographic data collections of the past.

sap_Q216_digital_double_feature3_images-0007Once the necessary data is available, companies need the technology, processes, and people to make sensible use of it in an omnichannel personalization strategy. Only when a company is organized as a Live Business can that happen. Here’s how your company can move toward being a Live Business:
Be live across channels. Having a consistent customer journey map across channels is core to omnichannel personalization. It requires integration across multiple systems and organizational silos to enable core capabilities, such as inventory visibility and purchase/pickup/return across channels. This integration also constitutes a major chunk of the transition to becoming a company that can act in the moments that matter most to customers. If all channels can sync in real time, customers can get what they want in the moment they want it.

Free the data scientists. Marketing rarely has full control over the omnichannel experience, but it is the undisputed leader in understanding customer behavior. While data science is part of that understanding, it has traditionally played a background role. Marketers need to bring the data scientists into efforts to sort through the different options for digitizing the omnichannel experience. The right data scientists understand not only how to use the tools but also how to apply the data to make accurate decisions and follow customers from channel to channel with personalized offers.

Walgreens’ Technology Approach to Personalization

Walgreens is a leader in building the kind of technology base that can enable real-time, omnichannel personalization. Its digital transformation is 16 years in the making, according to Jason Fei, senior director of architecture for digital engineering at Walgreens. At the heart of its infrastructure is a Big Data engine that feeds many customer interaction and omnichannel processes, including customer segmentation. The company adds third-party systems in areas such as predictive analytics and marketing software. Walgreens has a cloud-first strategy for all new applications, such as its image-processing and print-ordering applications. Other elements of the drugstore chain’s technology platform include:

  • Application programming interface (API)-driven architecture. Walgreens’ APIs enable more than 50 partners to connect with its apps and systems to drive customer-facing processes, including integrations with consumer wearables to drive reward points for healthy habits, as well as content partnerships with companies such as WebMD. “With APIs we can be an extensible business, allowing other companies to connect to us easily and help in the digital enablement of our physical stores,” Fei says.
  • Responsive Web sites. The company’s Web site is built using responsive and adaptive design practices so that the site automatically adapts to the consumer’s device, whether that is a mobile phone, tablet, or desktop computer. “We have a single code base that runs anywhere and delivers a consistent, optimized experience to all of our customers,” Fei says.

Making the Most of the Technology Base

This technology foundation has allowed Walgreens to push forward in personalization. For example, according to Fei the company uses sophisticated segmentation and personalization engines to drive outbound e-mail and text campaigns to customers based on their purchase history and profile. “We don’t blast out messages to customers; we use our personalization recommendations to be relevant,” says Fei.

The next phase of this strategy is to develop live inbound personalization tactics, such as recognizing customers when they come back to the Web site and tailoring their experience accordingly. These highly automated, self-learning systems improve over time, becoming more relevant at the moment a customer logs back in.

“When you search for a product, the Web site will take a good guess of what you might actually want. If you always print greeting cards at the same time of year, for example, the system would automatically deliver content around that,” Fei explains. “Everyone comes to Walgreens with a mission, so we can be very targeted with our communications.”

Walgreens’ mobile app combines real-time personalization with convenience. You can scan a pill bottle to refill a prescription, access coupons, send photos from your phone to print in the store, track rewards, and find the exact location of a product on the shelf.

Walgreens also recently deployed a new integrated interactive voice-response system that includes a personalization engine that recognizes the individual, says Troy Mills, vice president of customer care at Walgreens. The system can then predict the most probable reason for the customer’s call and quickly get them to the right individual for further help.

How to Get Started with Live Customer Experiences

sap_Q216_digital_double_feature3_images-0008As Fei can attest, getting Walgreens’ omnichannel and personalization infrastructure to this point has involved a lot of work, with much more to come. For companies just now embarking on this journey, especially midsize and large companies, getting started will mean overhauling an outdated and ineffective technology infrastructure where duplicate systems and processes for managing customer data, marketing programs, and transactions are common.

A bad internal user experience often transcends into a bad customer-facing experience, says Peeples. “We can’t afford the distractions of the latest app or social ‘shiny penny’ without addressing the root causes of our systems’ issues.”

Live Business Requires Striking the Right Balance

The boundaries of trust are a moving target. Sales tactics that used to be acceptable decades ago, such as the door-to-door salesperson, are unwelcome today to most homeowners. And consumers’ expectations are unpredictable. At the dawn of social media, many people were anxious about their photos unexpectedly showing up online. Now our identities are tagged and our posts and photos distributed and commented on regularly.

But while consumers are getting more comfortable with online technology and its trade-offs, they won’t put up with personalization efforts that make use of their data without their knowledge or permission. That data has value, and customers want to decide for themselves when it’s worth giving it away. Marketers need to strike the right balance between personalization and a healthy respect for the unique needs and concerns of individuals. D!

 

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Lori Mitchell-Keller

About Lori Mitchell-Keller

Lori Mitchell-Keller is the Executive Vice President and Global General Manager Consumer Industries at SAP. She leads the Retail, Wholesale Distribution, Consumer Products, and Life Sciences Industries with a strong focus on helping our customers transform their business and derive value while getting closer to their customers.

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How Big Data Is Changing The News Industry

Maggie Chan Jones

In the runup to the U.S. presidential election, newsrooms are working at a fever pitch. But if we slow down a minute to take a closer look at modern-day news organizations, we might ask ourselves: Can they really provide accurate, unbiased information on current events at Twitter speed?

News and the art of gathering it has evolved exponentially in the last few years. How the news is consumed is also light years away from where it was a decade ago. The explosive growth of the Internet and mobile devices has anyone and everyone broadcasting their opinions. The former broadcast news landscape has shattered into millions of different sources, platforms, and feeds, each using curated content models that cater to the reader, allowing them to pick and choose their sources.

With the expanding market of content platforms and multichannel news sources has come a myriad of perspectives. Does having this choice of who we listen to – or don’t listen to – make us unintentionally biased? This question is incredibly important to consider when we as a society come together to make informed decisions that impact everyone’s future.

Today’s major news organizations are balancing two realities. One is civic responsibility for reliable, responsible journalism. The other is profitability that mandates speedy content for readers on the go. This has forced news providers to become data-driven machines – seamlessly reacting across browsers, mobile screens, and social feeds 24×7. The imperative for speed has trumped traditional ways of reporting news. Data algorithms now drive content. Data-driven research and statistics have become an important source to supplement the day’s news. Third-party data tools are being used.

But this new focus on Big Data is also a curse. A petabyte of unprocessed, unstructured data is almost as useful as having no data at all. That’s why better tools to manage Big Data and stronger data algorithms are needed to create content that can benefit today’s readers. This is an important initiative for SAP, and we’re providing technology that is already impacting the way news is prepared and consumed for important current events, such as the upcoming U.S. presidential election.

As the exclusive sponsor of Reuters’ Polling Explorer, SAP is working with Reuters to provide journalists and consumers the latest polling data, stories about the election, and more. Real-time data is fueling Reuters with the tools needed to execute news with accuracy, speed, and integrity. The new polling explorer increased their readers’ engagement from 240K visits for all of 2012 election cycle to 6.2M just in the first four months since launch in November. The Reuters election app uses the new data system to match users with the candidate who best fits with their own political leanings. And Reuters can also use software to inform polling data and other data sets into data visualizations that provide facts and stats in a dynamic, interactive manner.

By providing technology platforms that are easy to use and scalable for any sized business, technology providers can give news providers across the world a trove of insights that impact their readers in real time, especially during momentous, breaking news cycles.

For more insight on the power of Big Data, see The Risk And Reward Of Big Data.

This story originally appeared on SAP Business Trends

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Maggie Chan Jones

About Maggie Chan Jones

Maggie Chan Jones is CMO of SAP, responsible for leading SAP’s global advertising and brand experience, customer audience marketing, and field and partner marketing functions across all markets. Her mission is to bring to life SAP’s vision to help the world run better and improve people’s lives through storytelling, and to accelerate company growth. A career-marketer in the technology industry, Maggie has held a succession of roles at Microsoft, Sun Microsystems and other technology companies.