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Step-By-Step, How-To Guide To Digital Transformation

Florian Wagner

OK, maybe this headline exaggerated. There probably is no one step-by-step guide to digital transformation, but it’s safe to say that a thorough evaluation of five clearly defined areas can help companies assess digital business readiness based on a Digital Business Innovation framework developed by Digital Bridge Partners & SAP. This assessment of the key elements we have observed in successful digital innovation stories serves to identify strengths, weaknesses, gaps, and opportunities on the road to digital transformation.

A framework for success

The Digital Business Innovation (DBI) framework is a system of assessing the CIO’s and IT’s readiness for, and progress along, a digital transformation journey.

The framework consists of four pillars supported by DBI leadership:

  1. Define a digital strategy to raise awareness, set direction, and drive decision making
  2. Apply a best practice organizational innovation model and culture, including agile solution development processes to drive digital business value
  3. Establish a collaborative and agile IT operating model that allows for incubation of new approaches
  4. Deliver the right platforms ‒ technical and commercial ‒ to support enterprise-wide transformation and innovation required by digital business model changes

 Where should your digital transformation start?

According to the 2015 MIT Center for Information Systems Research survey, board members think that 32% of company revenues will be threatened by digital disruption by 2020. This should create a sense of urgency in any company. But preparing for transformation requires clarity in two areas: a strategy that outlines the scope, depth, and size of the change needed to realize your goals, and an assessment of what is required in terms of culture, capacity, leadership, models, and tools.

Many digital maturity assessments exist, but most are quite complex and time consuming, or lead toward a specific vendor’s solution. However, this assessment was designed to bring quick, clear focus to proven key success factors. The sample assessment questions below are a starting point for the conversations we have with technology leaders across a range of industries, so they are necessarily high-level. This approach focuses efforts on the degree to which maturity has been achieved and identifying strategic next steps rather than simplistic, tactical snapshots of the status quo.

The assessment

1. Leadership

  • To what degree do the CIO and IT recognize the importance of leading/driving a digital business innovation agenda?
  • To what degree is the CIO a key leader of digital business innovation?
  • How mature is IT’s drive of the digital business innovation function and culture?

2. Digital strategy

  • How well defined is the company-wide, CEO/board-driven business transformation agenda?
  • To what degree has the company committed to a comprehensive digital strategy that is aligned with your business transformation agenda?
  • To what degree does your leadership have a clear portfolio management approach to evaluate the risks and rewards of digital transformation?

3. Innovation model

  • To what degree do business peers look to IT as their co-innovation partner?
  • To what degree does your innovation model work enterprise-wide through agile, cross-functional teams working a well-managed portfolio of innovations?
  • To what degree is your organization ahead of competitors in its ability to leverage technology to drive innovation and financial results in both business processes and business models?

4. IT operations

  • To what degree has IT built a roadmap to close its tools and skills gaps between what is required and what is in place today to deliver on your digital strategy?
  • To what degree do business teams leverage IT’s tools and skills to drive digital business innovation?
  • To what degree does IT blend security, reliability, openness, and agility to support both ongoing operations and innovation work?

5. Platform

  • To what degree does IT have the end-to-end technical and commercial platforms required to facilitate effective digital transformation?
  • To what degree does IT have a clear plan for developing the technology platforms (owning or joining industry platforms, Big Data analytics, and APIs) required to facilitate value creation across your entire ecosystem?
  • To what degree is your organization clear about its relationship to the platform business models emerging in your value ecosystem (own, co-develop, join, counter)?

If a far more granular view would be helpful, use SAP’s Digital Innovation and Transformation Assessment.

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Florian Wagner

About Florian Wagner

Florian Wagner is marketing director for IT audience messaging at SAP. Together with his team, he is responsible to address the IT audience and to drive relevant thought leadership topics. He writes about technology trends on digital transformation, cloud and platform strategies with a focus on customer experiences.

Banking IT Leaders Can Drive Digital Transformation With Internal Partners, Fintech Collaboration

Karen McDermott

Banks today are in a position of strength when it comes to digitalization. In general, banks still hold two important assets – customers and data.

Banks looking to leverage and innovate in an era of digitalization are increasingly looking at those two asset classes as the key.

Changing expectations in a digital world

Banks are feeling pressure to innovate to respond to shifting consumer expectations. Consumers increasingly expect to access products and services via digital channels.

To deliver what their customers’ expect, banks can take advantage of new collaboration opportunities. By working with financial technology startup companies, banks can maximize new technologies while not losing focus on core strengths and advantages.

Surveying the landscape

There is a clear recognition within the industry that change is on the horizon … and necessary to continue positions of strength. A recent survey of 103 senior executives in banking and financial services found a majority (69%) saw digital initiatives as high or relatively high compared to other strategic priorities. The survey was conducted by The Economist Intelligence Unit, sponsored by SAP.

The focus needs to be squarely on the customer experience, according to those respondents. In fact, of all the industries included in the survey of IT and non-IT leaders, banks and financial services companies were the most focused on using digital transformation to improve the customer experience. Forty-eight percent indicated that of all digital initiatives, the customer experience was the top priority.

In addition, 72% of financial services executives had launched new customer-facing digital channels over the past three years, far outpacing the 55% in other industrial sectors.

The role of IT in digital innovation at banks

The opportunity for IT leaders at banks is profound. At financial institutions, the role of the IT department needs to evolve to meet the demands and expectations of digital innovation. No longer is IT merely about keeping systems running and passwords secure. Today, given the importance of digitalization, the IT team can and should play a vital role in leading innovation throughout the enterprise.

Instead of focusing on system innovation and being seen as a back-office function, IT needs to step into the spotlight. Digitalization provides opportunities for IT leaders to break down organizational silos and lead innovation. IT teams can help disparate parts of the enterprise see what customers need, bringing together product owners and leading the change from within.

That is not the approach most banks are taking today. The aforementioned survey showed that in 51% of companies, digital innovation is led by individual business departments, in 25% by dedicated digital units, and in just 23% by IT departments. Among those initiatives led by a business unit, the IT department fulfills only a support function among 25% of the companies.

The data indicate clearly that in banking and financial services, IT is primarily taking a backseat when it comes to digital innovation. While this is the norm, it is not necessarily the preferred state. Sixty-one percent of the senior leaders surveyed believe that more collaboration between business units and IT will drive success of digital initiatives. Only 10% believe that IT departments are taking a lead role in supporting institutional agility, but 43% would prefer that IT play that lead role.  

External partnership opportunities

Big banks and financial institutions should consider deeper partnerships with financial technology (fintech) startup firms as a way to gain the agility they so desire. Fintechs generally have a deeper focus on customer-centric solutions and processes, but lack the large customer bases and data troves that big banks hold.

Collaboration between the two can leverage each organization’s strengths. Banks would be able to deliver to their customers new, innovative, and wanted tools, products, and services. Fintechs would gain expanded market penetration that could fuel growth and expansion.

There would be cultural issues to overcome. Large organizations would need to accelerate approval and implementation processes, for example. Software development, as another example, would need to happen on a collaborative basis, seizing on the speed in which a typical fintech operates while leveraging the industry and customer knowledge that banks bring to the table. Here are a few tips banks should follow when considering such partnerships.

  • Focus on the customer. To succeed in these collaborative efforts, banks need to adopt a customer-first approach. At the same time, they need fintech partners that understand the complexities and processes in place in large organizations.
  • Look for complements. There are hundreds of fintechs developing applications, software programs, and new tools to reach and serve customers. The key for banks is to find a fintech partner that complements existing development teams and helps fill gaps and needs in the development pipeline.
  • Understand needs. Fintechs are looking for significant revenue growth. Banks are looking for changes in approach and process that drive customer acquisition and retention. Banks need to seek out and partner with fintechs that understand the bigger picture.
  • Consider timing. Banks need to understand and help their fintech partners understand the importance of timing. Disruption happens best when there is a full understanding of markets and customer expectations. It also requires an understanding of the technology solutions and when it is optimal to launch.

Each of these suggestions carries with it the need for strong IT leadership to connect and implement change. With fintech partners, IT teams serve an even more critical role in serving as leaders and bridge-builders.

It is a heady time for IT leaders in banking. By seeing the opportunities and boldly leading both internally and with key partners, IT leaders can position themselves … and their companies … for extraordinary change.

For more on adopting a customer-centric approach, see Corporate Banking: Learning From The Consumer Side.

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Karen McDermott

About Karen McDermott

Karen McDermott is Global Head of Financial Services Industries Marketing and Communications at SAP, responsible for driving the growth of SAP's value proposition as a technology provider, trusted business partner, and thought leader for the financial services industry.

Enterprise Information Management: The Foundational Core Of Digital Transformation Success

Paul Lewis

The definition and implementation of digital transformation has become so muddled that no two organizations are focusing on the same strategies and initiatives. Many companies choose to engage in e-commerce and social media to extend their customer base with engaging, personalized, and round-the-clock shopping experiences. Some eye operational efficiencies through the Internet of Things (IoT) and artificial intelligence. And a growing segment is enticed by game-changing insights from analytics and social sentiments.

No matter the digital strategy, data is the foundation of all of these efforts. The customer experience is about understanding clients and offering services that answer their needs. Decision making requires stored knowledge that can be easily shared, secured, and applied. Operational excellence runs on meaningful insight that drives performance and keeps workers safe.

In digital transformation, every change relies on converting data into actionable decisions. According to Capgemini, companies that act on an enterprise information management (EIM) strategy outperform their rivals by as much as 26%.

The EIM difference in digital transformation

A data point by itself may seem unrelated and inconsequential. But when enterprise data is united and managed as one asset, decision makers finally have trusted, complete, and relevant information they need to seize opportunities and avoid risks that were previously hidden in the background.

One of my clients, Pravine Balkaran, global head of IT at Spin Master, one of the world’s largest toy and media entertainment companies, said it best: “It’s about being able to apply standardization and automation to the entire ecosystem to bring value and move the business forward.”

EIM derives new value by incorporating the traditional functions of data, including business intelligence, data science, analytics, data storage and archiving, data stewardship, and data mobility technology. The more data added, the more valuable the ecosystem becomes – without the complexity commonly experienced when searching for potentially valuable data across a diverse set of existing applications.

By applying EIM to the core of its digital strategy, companies like Spin Master are capturing and coalescing data from a variety of sources and turning it into actionable information to drive better decision making, innovate new products, enter new markets, and encourage a more responsive customer experience.

The EIM road map towards rapid creation of new value

Now for the hard part: Putting EIM into action and at the center of your digital transformation business strategy. There are five things you should do now before moving to a more digitalized and data-driven way of doing business.

1. Inventory available information

Most companies believe that their data resides in core databases and a data model of known entities such as claims, transactions, vendors, and suppliers. Although this is a widely used approach to determining the class of your information, it is only a small part of what you actually own. Structured, unstructured, and semi-structured data; log files; conversations; customer sentiment; and real-time information from suppliers and vendors, for example, should be integrated as part of the overall EIM philosophy.

2. Classify your inventory

Data typically can be classified with one or more of these six attributes:

  • Real-time, streaming data, which potentially comes from machines
  • Static data from production databases
  • Valuable data in real time once stored
  • Realizes value over time and as it changes
  • Relevant to a particular government mandate or legislative concern
  • Objective and relative importance to divisions of the overall enterprise, including customers and the business network

With this exercise, you can begin to understand the function that each data point serves and its usefulness in the future.

3. Encourage the business culture to appreciate the value of discovery

Data-driven decision making is not based on blind faith that data always tells the right story. Rather, it is asking the right questions, and knowing how to dig deep into the data helps us make the connections we need to get an accurate picture of the current situation. Once you discover those nuggets of insight gold, data science and advanced analytics can be applied to pinpoint the appropriate solution. Later, you can leverage data visualization tools to communicate findings and proposed action in a format that is quick and easy for all levels of the enterprise to consume.

4. Shift your focus from yesterday to today and beyond

Traditionally, data analysis is an exercise of looking backward to determine the how, what, when, and why an event happened. However, the pace of change in every aspect of the business has accelerated so much, that it’s rendered this retrospective approach to analytics nearly useless. Real-time access to data allows decision makers to know what’s happening in the moment and how it will impact the future to seize opportunities and mitigate risks.

The path to digital transformation is paved with data

The volume of data generated by people across the entire business network – from employee to consumer and everyone in between – represents a veritable trove of information, insights, and inspiration for innovation. But first, companies need to know where to find this data and how to best apply it to everyday decision making. With EIM, data can be broken down and reassembled into a manageable form that is meaningful, outcome-driven, and transformational.

Learn more about how to uncover Data – The Hidden Treasure Inside Your Business.

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Paul Lewis

About Paul Lewis

Paul Lewis is the Chief Technology Officer in Hitachi for the Americas, responsible for the leading technology trend mastery and evangelism, client executive advocacy, and external delivery of the Hitachi vision and strategy especially related to digital transformation and social innovation. Additionally, Paul contributes to field enablement of data intelligence and analytics; interprets and translates complex technology trends including cloud, mobility, governance, and information management; and represents the Americas region in the Global Technology Office, the Hitachi LTD R&D division. In his role of trusted advisor to the CIO community, Paul’s explicit goal is to ensure clients’ problems are solved and opportunities realized. Paul can be found at his blog, on Twitter, and on LinkedIn.

How Emotionally Aware Computing Can Bring Happiness to Your Organization

Christopher Koch


Do you feel me?

Just as once-novel voice recognition technology is now a ubiquitous part of human–machine relationships, so too could mood recognition technology (aka “affective computing”) soon pervade digital interactions.

Through the application of machine learning, Big Data inputs, image recognition, sensors, and in some cases robotics, artificially intelligent systems hunt for affective clues: widened eyes, quickened speech, and crossed arms, as well as heart rate or skin changes.




Emotions are big business

The global affective computing market is estimated to grow from just over US$9.3 billion a year in 2015 to more than $42.5 billion by 2020.

Source: “Affective Computing Market 2015 – Technology, Software, Hardware, Vertical, & Regional Forecasts to 2020 for the $42 Billion Industry” (Research and Markets, 2015)

Customer experience is the sweet spot

Forrester found that emotion was the number-one factor in determining customer loyalty in 17 out of the 18 industries it surveyed – far more important than the ease or effectiveness of customers’ interactions with a company.


Source: “You Can’t Afford to Overlook Your Customers’ Emotional Experience” (Forrester, 2015)


Humana gets an emotional clue

Source: “Artificial Intelligence Helps Humana Avoid Call Center Meltdowns” (The Wall Street Journal, October 27, 2016)

Insurer Humana uses artificial intelligence software that can detect conversational cues to guide call-center workers through difficult customer calls. The system recognizes that a steady rise in the pitch of a customer’s voice or instances of agent and customer talking over one another are causes for concern.

The system has led to hard results: Humana says it has seen an 28% improvement in customer satisfaction, a 63% improvement in agent engagement, and a 6% improvement in first-contact resolution.


Spread happiness across the organization

Source: “Happiness and Productivity” (University of Warwick, February 10, 2014)

Employers could monitor employee moods to make organizational adjustments that increase productivity, effectiveness, and satisfaction. Happy employees are around 12% more productive.




Walking on emotional eggshells

Whether customers and employees will be comfortable having their emotions logged and broadcast by companies is an open question. Customers may find some uses of affective computing creepy or, worse, predatory. Be sure to get their permission.


Other limiting factors

The availability of the data required to infer a person’s emotional state is still limited. Further, it can be difficult to capture all the physical cues that may be relevant to an interaction, such as facial expression, tone of voice, or posture.



Get a head start


Discover the data

Companies should determine what inferences about mental states they want the system to make and how accurately those inferences can be made using the inputs available.


Work with IT

Involve IT and engineering groups to figure out the challenges of integrating with existing systems for collecting, assimilating, and analyzing large volumes of emotional data.


Consider the complexity

Some emotions may be more difficult to discern or respond to. Context is also key. An emotionally aware machine would need to respond differently to frustration in a user in an educational setting than to frustration in a user in a vehicle.

 


 

download arrowTo learn more about how affective computing can help your organization, read the feature story Empathy: The Killer App for Artificial Intelligence.


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Christopher Koch

About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing. Share your thoughts with Chris on Twitter @Ckochster.

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In An Agile Environment, Revenue Models Are Flexible Too

Todd Wasserman

In 2012, Dollar Shave Club burst on the scene with a cheeky viral video that won praise for its creativity and marketing acumen. Less heralded at the time was the startup’s pricing model, which swapped traditional retail for subscriptions.

For as low as $1 a month (for five two-bladed cartridges), consumers got a package in the mail that saved them a trip to the pharmacy or grocery store. Dollar Shave Club received the ultimate vindication for the idea in 2016 when Unilever purchased the company for $1 billion.

As that example shows, new technology creates the possibility for new pricing models that can disrupt existing industries. The same phenomenon has occurred in software, in which the cloud and Web-based interfaces have ushered in Software as a Service (SaaS), which charges users on a monthly basis, like a utility, instead of the typical purchase-and-later-upgrade model.

Pricing, in other words, is a variable that can be used to disrupt industries. Other options include usage-based pricing and freemium.

Products as services, services as products

There are basically two ways that businesses can use pricing to disrupt the status quo: Turn products into services and turn services into products. Dollar Shave Club and SaaS are two examples of turning products into services.

Others include Amazon’s Dash, a bare-bones Internet of Things device that lets consumers reorder items ranging from Campbell’s Soup to Play-Doh. Another example is Rent the Runway, which rents high-end fashion items for a weekend rather than selling the items. Trunk Club offers a twist on this by sending items picked out by a stylist to users every month. Users pay for what they want and send back the rest.

The other option is productizing a service. Restaurant franchising is based on this model. While the restaurant offers food service to consumers, for entrepreneurs the franchise offers guidance and brand equity that can be condensed into a product format. For instance, a global HR firm called Littler has productized its offerings with Littler CaseSmart-Charges, which is designed for in-house attorneys and features software, project management tools, and access to flextime attorneys.

As that example shows, technology offers opportunities to try new revenue models. Another example is APIs, which have become a large source of revenue for companies. The monetization of APIs is often viewed as a side business that encompasses a wholly different pricing model that’s often engineered to create huge user bases with volume discounts.

Not a new idea

Though technology has opened up new vistas for businesses seeking alternate pricing models, Rajkumar Venkatesan, a marketing professor at University of Virginia’s Darden School of Business, points out that this isn’t necessarily a new idea. For instance, King Gillette made his fortune in the early part of the 20th Century by realizing that a cheap shaving device would pave the way for a recurring revenue stream via replacement razor blades.

“The new variation was the Keurig,” said Venkatesan, referring to the coffee machine that relies on replaceable cartridges. “It has started becoming more prevalent in the last 10 years, but the fundamental model has been there.” For businesses, this can be an attractive model not only for the recurring revenue but also for the ability to cross-sell new goods to existing customers, Venkatesan said.

Another benefit to a subscription model is that it can also supply first-party data that companies can use to better understand and market to their customers. Some believe that Dollar Shave Club’s close relationship with its young male user base was one reason for Unilever’s purchase, for instance. In such a cut-throat market, such relationships can fetch a high price.

To learn more about how you can monetize disruption, watch this video overview of the new SAP Hybris Revenue Cloud.

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