Enterprise Transformation Circle

Chapter 4: Defining Digitalisation

Manas Deb — Wed, 01 Nov 2017 11:32:35 +0000

Everybody seems to be using the term ‘digital’ today. Politicians are laying the foundations for the ‘digital revolution’, product companies have off-the-shelf-solutions for being a ‘digital leader’, and consulting firms can help you with the ‘digital transformation’. However, you hardly ever find anybody who can tell you exactly what ‘digital’ is; in fact, the term means different things to different people.

At one end of the spectrum are the rather simple features, such as replacing paper. At the other end, ‘digital’ is a synonym for the transcendence of the industrial era.

Therefore, it is unsurprising that there is no consensus on the definition of digitalisation in the literature. Every author either comes up with their own definition or avoids taking a clear standpoint.

In the remainder of this book, we use the term ‘digitise’ (or ‘digitisation’) if we’re talking about modernising something with a few digital ingredients, for example converting paper to a digital format. Most of the time we take a more far-reaching perspective and use the term ‘digitalisation’ as the beginning of a new era beyond the industrial age. Businesses in the industrial age have been characterised by automation, standardisation, mass production and enormous increases in efficiency. So, what are the characteristics of their digital successors? For a closer understanding of the change encompassing us, look at an ordinary family at the intersection of the industrial and digital age: observe that parents and children have totally different preferences for maintaining social relationships and communicating.

For example, parents are used to making appointments with friends a few days in advance. Their relationships are characterised by well-thought-out arrangements. Communication is driven by the necessity to negotiate those arrangements. Young people behave differently. They are used to digital media that provide information instantly, allowing seamless connectivity with all their friends around the clock and automating repetitive tasks. They are not in favour of long-term planning and multi-step processes, but instead decide ad hoc and at short notice. They are also less reluctant to change plans.

We believe this to be the most important attribute of the digital age: the intensive usage of digital means to change and enhance the way we maintain social relationships and communicate.

Correspondingly, we define a ‘digital enterprise’ as an organisation that makes extensive use of new digital technologies, such as social media, mobile connectivity, analytics or embedded devices, to fundamentally enhance or alter its relationship with all its stakeholders, including clients, employees and suppliers, and its interactions with them.

The following table depicts the critical aspects of this new digital relationship:

The digital relationships and the fundamentally modified possibilities to interact have profound consequences: digital enterprises deal differently with innovation and have significantly different processes, organisational structures and culture, and business models compared to traditional companies.

Accordingly, ‘digital transformation’ (or ‘digitalisation’) is the organisational process of changing an enterprise towards being a ‘digital enterprise’. This transformation process is initiated purposefully to change the enterprise, as opposed to a force of nature that just happens to the enterprise.

This change is a fundamental one – it is nothing less than the reinvention of the enterprise, comprising its processes, organisations and business models.

Such a substantial change is necessary to facilitate truly digital relationships with the enterprise’s stakeholders.

5.3 Living Strategy

Mario A. Brückner — Tue, 31 Oct 2017 23:00:00 +0000

Few sectors are as challenged by as many changes in market conditions as the utility sector.

With a heritage of being very traditional and inﬂexible, companies in this sector need to try new things to survive. The following case study gives an example of a successful next step that a service provider in the utility sector took in its strategy work, ushering in an agile future.

In our work we realised that traditional strategy efforts are outdated. The pace of change is accelerating more rapidly than ever. Successful companies need to be ﬂexible and agile, and to understand trends. The ability to bring new products to market swiftly is key. A critical requirement in rapidly changing times is for the company’s aims to be clearly communicated and reﬂected in a transparent company vision. Only with a clear vision are companies able to set up a market-winning strategy.

Traditional strategy work is a kind of bureaucratic process focusing on the long-term goals of a company.

We often see strategies developed with a focus on the next 10 years, using a hierarchical process that involves strategy experts and external consulting companies. This process can take six to 12 months. This long duration can lead to the results being outdated by finalisation, communication and implementation of initiatives. In addition, the traditional strategy approach mainly involves strategy experts in the process. Research in many European companies over the last 10 years has shown that the majority of employees believe that strategies do not reﬂect their company’s current position or its environment, and that they have no real impact on their daily work.

Employees see strategy work as being reserved for senior management, and as a process that fails to take the abundant know-how of the employees into account.

We came to the conclusion that we had to reinvent the strategy world. Similar to a plant that constantly grows, adapts to its environment and competes with other plants in its surroundings, a company competes with other companies for resources and market share. A company will outperform its rivals by having a better survival strategy. A better survival strategy enables a company to use the right resources in the best and most efficient way by reacting to market impacts and trends. Adjustments need to be made rapidly and ﬂexibly. Therefore, a company needs to respond decisively and swiftly to internal and external feedback, developments and trends. This requires a fundamental change in strategy work so that the corporate vision, mission and strategic objectives are subject to continuous adjustment, where a strategy is never final. As you will see in the remainder of this section, this conclusion affected the entire framing of our strategy, the process itself, the resources involved and the way of involving people in the process.

We designed and implemented a new framework, the Living Strategy, by combining elements of design thinking and agile project management into a new way of doing strategy work. This enables the company to adjust swiftly and ﬂexibly to the environment.

To take into account environmental changes that impact the company’s business models, organisation and processes, we adjust key elements such as the vision, mission and strategy itself on a regular basis by performing sprints of approximately six to 12 weeks. In each sprint, a special deep-dive topic is discussed for its impact on the strategy.

The results of a given sprint form the basis for the next sprint. The decision on which deep-dive topic will be the focus of each sprint is taken by the (Product) Owner of the strategy together with the company’s Management Board, in so-called ‘Strategy Scrum Meetings’, which take place before each sprint. The strategy team (organised as a department reporting directly to the CEO) prepares these scrum meetings. They suggest topics and prepare the sprint by collecting all necessary internal and external information. In addition, an analysis will be performed to find out which employees need to be involved and which (workshop) methods need to be selected. In some cases, external support will be requested, depending on the sprint topic.

In the sprint, the strategy team works with three major tools. The Strategy One-Pager describes the future picture of the company. The Strategy Radar illustrates the focus areas that encompass initiatives and projects, monitored via our Strategic Roadmap. As the result of a sprint, all these three instruments will be adjusted and the results will be presented in the scrum meeting. Indicators of how successful we are in establishing the future picture will be monitored via the Balanced Score Card.

The Living Strategy is not only a new process; it is also a cultural change, or can be part of one. It is of utmost importance to involve all employees, external experts and customers in discussing and creating the future of a company.

For example, we invited all interested employees for strategy workshops in Sprint 1, developing an initial future company picture, mission and strategic objectives, as well as defining strategic focus areas. The workshops were performed with 200 participants all over Europe with very good results. This approach was highly appreciated by the managing directors of the company.

11.10 Data, Analytics and Insights

Frank Kaminsky — Tue, 31 Oct 2017 23:00:00 +0000

Data is the fuel for business processes.

It has been so throughout time, from the ancient stone tablet to the modern era, but data is never nearly as important as it is for the digital transformation.

The digitalised company is driven from its core by data, and digital business processes bind together all partners in the respective digital ecosystem. Digital companies virtualise their offering, their customer and business partner relationships, as well as their sales channels. Similarly, data represent every interaction of the network’s participants. Therefore, data has become an essential asset for the company.

Digitally processed data have been used since the sixties to document master and transactional data of the company. Since the eighties, they have been increasingly used for ex-post analysis. Alongside digitalisation, two new key disciplines enter the stage: the prediction of future market behaviour, and automated individual decision-making in real time.

In general, data represent business objects for a defined purpose in a simplified manner. Data objects are based on a reality space, the scope of which will be defined in order to support given business goals, together with the necessary entities, attributes and activities. In the digital environment, however, this reality space tends to become larger, as business processes are transferred to the customer side and become more inﬂuenced by external actors. Every activity in digital business leaves traces in the form of data, which are stored within the company. Internal data are those resulting from the execution of transactions with customers, products, services, partners and so on. They also represent business processing, and thus status and rules of business processes themselves that run automatically in the digital ecosystem.

This way, all fully executed and also incompletely executed activities are documented. Internal data are the foundation of the business, because they are also legally relevant (e.g., for contracts, financial data, risk calculations, compliance). Beyond that, they provide detailed information on all activities associated with the business. Unstructured internal information is becoming more important than ever, as it is considered highly relevant for the appropriate interpretation of customer needs.

Data and processes are connected in a true symbiosis in order to create value.

Data last for a long time and must usually be accurate, at least when they are legally or financially relevant for the company. Due to this fact, a structured, precise and typically rather cautious data development process is required. Processes related to these data objects, however, are much more dynamic and volatile, because they are – especially in digital businesses – affected by outside factors, requiring a more agile approach. Consequently, the objects’ attributes (data) should follow a different development model from activities related to such objects (processes), allowing for different development speeds.

Publicly available information is increasingly attracting the interest of digitalised companies, in order to access both new customers in well-known target groups and even new markets with their potential for accelerated growth. At first sight, such information represents seemingly unrelated pieces of a puzzle of target objects and entities (e.g., people, products, companies). The collected pieces must be evaluated in terms of relevance and likelihood of fitting into a desired, initially unknown object. Additionally, behavioural information on the detected entities is of great importance, because it hides business-related events and is derived through analysis of previously collected raw data.

Unlike internal data, publicly available data are largely uncontrollable; data quality, reliability of the source (e.g., content changes, structural changes, temporary or permanent non-availability, update frequency), redundancy of the same information across different sources and so on, affect the collection and analysis of data, which complicates matters.

The collection and use of publicly available data require new technologies, which many companies have yet to master.

This is also true for the analysis, for example, of unstructured content from non-secure, potentially amorphous and independent data sources, often with unreproducible or non-controllable changes, possibly describing initially the ‘world’, but not necessarily the known or searched-for (yet sometimes still unknown) business opportunities.

From many seemingly unrelated pieces of information, data need to be processed into a structured and analysable form.

With self-learning mechanisms, they are merged and transformed into complex structures mirroring reality. Therefore, new disciplines are needed for processing publicly available data, disciplines which are, by the way, to a great extent similar to those necessary when creating a business ecosystem from internal unstructured content, an ecosystem which finds its cornerstones, business definitions and foundation in the new data. Such mechanisms include:

Source intelligence to scout and make available relevant sources
Entity intelligence to form objects from unknown, initially isolated data sources
Context intelligence to connect external and internal objects and to associate with the business context of the digitalised company
Continuous market monitoring to derive signals, trend values and forecasts from previously developed data structures for past, present and future business opportunities.

In such a process – which needs to be elaborated – new data are generated that must first be transferred into the right business context (business ecosystem) in order to create benefit for a specific use case. Digital enterprises must learn to deal with concepts such as the relevance of information or the probability of correctness of their business objects. This applies both to the creation and the usage of data. Derived actions based on objects that exist only with relative certainty and processes that are based on probabilistic methods cannot be classified into categories like ‘exact’ or ‘correct’. This is not so much a technical issue, but rather a cultural change for the decision makers in the company.

In the process of digitalisation, direct personal contact with targeted clients and business partners is purposefully reduced so that, in return, every potential customer on the planet can in principle be addressed.

Thus, personal judgement as well as the traditional gathering of information (e.g., recognition processes, identity and sentiment/ mood, desire to buy) must be substituted by data-driven alternatives.

‘Analytics’ is the key to creating these substitutes artificially while itself producing large amounts of derived and calculated data.

2.4 Pressure on Employees

Jürgen Hemmer — Tue, 31 Oct 2017 23:00:00 +0000

Today, global competition drives many traditional companies to increase pressure on their employees. Companies use new digital media such as email, online messaging and smartphones to raise expectations of employee reachability, intensify working processes and enhance control.

Under this model, employees are considered resources. Reorganisations, work intensification, out- and insourcing activities etc. lead to an increasing alienation of employees from their companies. At the same time, market pressure urges companies to adapt to global supply chains and ﬂexibly react to ever-changing customer demands. Innovation cycles are shrinking with tremendous speed. While a company might be ﬂexible enough to meet such challenges for a while – for example by physically moving production to a more favourable location – its employees might not have similar ﬂexibility.

Applying traditional methods to meet the challenges of the digital age will always lead to the dehumanisation of work.[1],[2]

Conversely, many companies do not yet use the merits of the digital age to empower their employees. They apply the same processes, stick with their inherited organisational structure and foster the same old corporate culture, which worked fine in the industrial age. By doing so, they misjudge the fact that a sustainable increase in efficiency driven by digitalisation goes hand in hand with new processes, organisational structures and culture.

The phenomenon of work-related diseases caused by mental stress is omnipresent.

In particular, the popular term ‘burnout’ summarises various mental health conditions from which all industrialised nations suffer. A steady amount of the wrong type of pressure leads motivated and productive employees to become sick and non-productive. The result is tremendous damage for the individuals as well as for the companies and society at large. For example, current figures in Germany show that the average depressed person was unable to work for 60 days of the year in 2014. This is an increase of 135% compared to 2003.[3],[4]

In 2014, 1.6% of Germany’s working population fell ill with some form of depression, resulting in the loss of 40 million workdays.[5] The figures in other industrialised countries are similar.[6],[7],[8],[9]

Literature separates the risk factors for burnout into two categories.[10] On one side are personal risk factors, such as low self-esteem or the pursuit of perfection. The second category refers to external factors, which include risks due to the working environment, such as permanent overload, contradicting goals, work instructions contrary to personal values, lack of meaning and appreciation, environmental conditions, night and alternative shifts, an ever-changing organisation, permanent disturbance, fear of job loss, lacking autonomy, ubiquitous control, ruthless colleagues, etc.

Interestingly, digitalisation has the capability both to amplify existing risk factors and to mitigate them.

Especially in global companies with virtual teams and ﬂexible workplace concepts, there is a huge potential either to damage the organisation or to strengthen it. Due to new organisational and communication concepts, along with increased transparency, digitalisation opens up the opportunity to create a new identity for the employee alongside the digitally transforming company.

However, this will only succeed if ethical and social principles are an integral part of the digitalisation contract. Digitalisation allows certain risk factors to be turned into advantages:

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[1] Illek, C. O.: ‘Die Menschen mitnehmen – Wir laufen Gefahr, als Wissensgesellschaft zu versagen, und gefährden so unsere Zukunft’, Die Süddeutsche Zeitung Online, 2015.

[2] Wander, F.: ‘Transforming IT Culture: How to Use Social Intelligence, Human Factors and Collaboration to Create an IT Department That Outperforms’, Wiley CIO Series, p. 2, 2013.

[3] Grobe, T. G., Steinmann S.: ‘Depressionsatlas – Arbeitsunfähigkeit und Arzneiverordnungen’, Techniker Krankenkasse, 2015.

[4] Rennert, D.: ‘Zahl des Monats Juli 2015’, BKK Dachverband, 2015.

[5] Hahlen, J.: ‘Arbeitsmarkt – ILO-Arbeitsmarktstatistik’, Statistisches Bundesamt, 2015.

[6] ComPsych: ‘Loss of productivity among employees in North America due to stress in 2014’, Statista, 2014.

[7] Johnson, M. W.: ‘Burnout Is Everywhere – Here’s What Countries Are Doing To Fix It’, The Huffngton Post Online, 2013.

[8] Health and Safety Executive: ‘Work-related stress, anxiety and depression statistics in Great Britain 2016’, Health and Safety Executive, 2016.

[9] Prinz, C.: ‘How Your Mental Health May Be Impacting Your Career’, PBS Newshour, 2013.

[10] Stock, C.: ‘Burnout: Erkennen und verhindern’, 2nd ed., Haufe-Lexware, pp. 29-66, 2015.

Chapter 6: Linking Enterprises to Form Digital Ecosystems

Marcel Nickler — Tue, 31 Oct 2017 23:00:00 +0000

The revolution that we are witnessing started with the hum of electricity and cooling fans. It has taken us from the mechanical to the digital age and, as with the Industrial Revolution, it marks a significant leap that affects every aspect of our daily life.

The digital revolution is accelerating at a breakneck speed and transforming business models. It is an age of collaboration – innovative technology partners can quickly turn a small bricks-and-mortar store into a global enterprise.

According to Weill and Woerner,[1] four different classes of business model can be distinguished, each of which implies significant differences in operating model, transformation strategy, scalability, etc. So it is wise to deliberately choose your arena.

In many respects the most promising class of business model is the ecosystem initiator. The initiator of an ecosystem owns the customer relationship and orchestrates various suppliers.

Smart players can maximise profits by exploiting the customer relationship and minimising costs along the supply chain.

Furthermore, the initiator of an ecosystem is able to shift risks to its suppliers and – if necessary – replace them. Therefore, many digital players aim for a dominant role in an ecosystem (see figure below).

Previously, the small bricks-and-mortar store could grow organically or through M&A – both of which can be slow, ineffective and value destroying. Linking enterprises to form digital ecosystems is seen as a third way to grow, not just moderately but exponentially. From Airbnb and Uber to Amazon and Alibaba, today’s big growth stars all share a key characteristic in their business models: they have created digital platforms that manage and monetise the vibrant ecosystem of consumers, producers and innovators.

How did Airbnb become the world’s biggest hotelier in a few short years with only 2,500 employees and without owning any hotels?

They did it by creating a digital platform that connects hosts (people with available rooms or accommodation) with travellers – the participants themselves interact and share in value creation.

These platforms, like the one Airbnb created and manages, are the basis of the business models of companies that are experiencing astronomical growth. Incumbent enterprises are trying to tap into these digital ecosystems because they see the potential to realise their ambitions almost instantly on a global scale, as compared to growth before digitalisation. In the majority of cases, a digital platform is the first step to initiating an ecosystem. Only when the platform is in place can you begin to attract suppliers and customers. BearingPoint research, for example, distinguishes four different platform categories: transaction platforms, innovation platforms, integrated platforms and investment platforms (see table below).[2]

Starting a platform presents a tricky chicken and egg problem. You must attract different partners, such as suppliers and customers, at the same time as making the platform attractive to all participants.

Not surprisingly, all-in-one solutions are already available on the market in the form of Digital Ecosystem Management (DEM), such as BearingPoint’s Infonova R6.

What is attractive for large enterprises, and even small bricks-and-mortar stores, is that DEM enables an enterprise to rapidly launch new services and service types, and manage and monetise an ecosystem of partners and third parties.

The example of a major telecommunications company illustrates how an enterprise can transform its business model through a DEM solution. This telco chose BearingPoint’s Infonova R6 as its DEM solution. The solution enhanced the telco’s data centre collocation and cloud services portfolio, which includes storage offerings as well as third-party software applications. It enabled the telco to seamlessly aggregate new cloud services and software applications so that it could then offer them as new products and services to customers who can now exploit the full benefits of cloud and digital transformation. The DEM solution empowered the telco to provide white-label facilities to third parties seeking to sell their own cloud and application services, and enabled them to offer and monetise their services as bundles in combination with the telco and other third-party services. In this way the solution ultimately opened new services and possibilities for the telco, both locally and globally, whereby the power of DEM solutions in general is that nearly all enterprises can add new services and service types. Infonova is only one example, as there are several other such solutions in existence today.

Linking enterprises to form digital ecosystems wipes out the previous boundaries of business models. Looking ahead, disruption is likely to be experienced across all traditional businesses.

The winners will be the companies that evolve their business models by forming ecosystems, and many of the traditional giant enterprises will become dinosaurs. The digital revolution will not wait and will only continue to accelerate.

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[1] Weill, P., Woerner, S. L.: ‘Thriving in an increasingly digital ecosystem’, MIT Sloan Management Review, Vol. 56, Iss. 4, 2015.

[2] Evans, P. C., Gawer, A.: ‘The Rise of the Platform Enterprise – A Global Survey’, BearingPoint, 2016.

Chapter 10: Driving the Digital Transformation

Marc Roman Franke — Tue, 31 Oct 2017 23:00:00 +0000

We have organised the digital transformation into four phases. Part 3 of this book covered the first two phases: phase one of the transformation process revolves around launching and governing the transformation, followed by shaping as phase two. Part 4 contains driving and then executing transformative activities. In this chapter we take on driving, which is the third phase of the four.

Before driving the transformation, we have already completed the following steps. First, we have taken the decision to commit to the digital transformation and started its implementation (launching and governing), including getting the right management team on board and mobilising the organisation. Second, we have precisely defined what digitalisation means for the particular enterprise (shaping), for example by describing the future business portfolio, target architecture, transformation plan and capability needs.

At this point the driving begins and with it a tough work process for the CDO and other executives.

As seen in the graphic above, there are three main tasks involved in driving the digital transformation. The first task is to enable the organisation to implement the new strategy by teaching employees the appropriate skills and by providing organisational structures and resources. Next comes driving the transformation of the portfolio. At this point many aspects of the desired target state have already been defined at a coarse level. However, the target may change as we apply our strategy and gain experience, and details will be carved out more precisely.

Neither change nor experience will happen accidentally – we have to guide, push, lead, seduce, compel and urge, leaving no doubt that transforming the portfolio also means a change in the business model.

To complete the driving phase, we must also manage the changes in the business model and the corporate culture. This is an enormous task as any change of this magnitude will inevitably create resistance if not managed properly.

This may sound like a rigid plan that determines each step of the digital transformation. Unfortunately it is not a step-by-step process. Even though it is wise to make a transformation plan, the journey’s end remains unpredictable. Politics, unforeseen twists and changes in the market environment may interfere with nicely developed plans. The goal here is to think big, start small and scale rapidly. Here follows a brief exploration of this approach.

In contrast to industries like media and retail, where digital technology has been a significant disruptive force and is essential to their core business, process-oriented industries such as energy, transport, industrial goods and healthcare have yet to see its full effects. For management teams in these industries, it can be difficult to know how to start implementing digital technology – or even to see the need.

As a result, many companies have yet to take action to capitalise on digital. Some of these late adopters say they are hindered by legacy information technology (IT) systems or do not have the necessary capabilities in place. Others spend months studying the market and get bogged down in large-scale strategic and conceptual considerations, believing – incorrectly – that they need to understand exactly how and where the journey will end before they can take the first step.

The development cycles of digital technology are extremely rapid – far faster than for most traditional products and services – and this deliberate (and outdated) approach means that these companies are essentially fighting yesterday’s battles.

That does not mean no target state needs to be envisioned. However, to avoid a stalemate, starting to experiment with digital is the essential and suggested next step to explore the digital options and create solid ideas.

Given the pervasiveness, low cost of entry and potential impact of digital technology, it is imperative that companies act today. Late adopters, in particular, must step up the pace and follow early adopters in launching new digital products and services and digitise internal processes. This means they must implement far nimbler development processes and become far more comfortable making decisions amid uncertainty. In addition to a well-thought-out top-down, strategy-driven approach (which worked in the past), these companies need to innovate using ‘build-assess-learn’ cycles, even when not entirely sure of the outcome.

They need to focus on pilot tests and prototypes that can be developed and rolled out quickly, assessed for performance and scaled up (or shut down) accordingly.

They need to embrace the concept of ‘fail fast and fail cheap’ and build up their digital capabilities through direct experience.

And rather than making a single big, strategic bet, they need to manage multiple initiatives, trying out new business models with low sunk costs, killing off the losers and scaling up the winners.

Our experience with companies in virtually all industries shows that success with this kind of trial-and-error approach requires a structured transformation methodology built around three steps:

Securing quick wins at the outset: Speed is more important than perfection. Companies should launch small-scale digital initiatives to improve the customer experience, bring new products and services to the market and digitise internal processes.
Scaling up successful initiatives: Once they have identified promising digital ventures, companies need to scale them up and establish the right organisational model to integrate them with existing operations.
Leading and sustaining change: Successful digital transformations require strong leadership, alignment between IT and the business units and a culture that celebrates risk-taking and rapid action.

Together, these steps can help management teams determine where to start, how to manage the process and how to generate sustainable progress with their digital transformations.

10.1 Think Big – Start Small

Marc Roman Franke — Tue, 31 Oct 2017 23:00:00 +0000

Companies seeking to pursue digital often proceed from very different starting points, with different capabilities, circumstances and degrees of ambition. Some will require a full transformation of their operations, processes and business model in order to fully leverage digital technology and drive revenue. Others may only need to increase efficiency by re-engineering their existing business and operating models.

Given the fact that defining a strategy takes valuable time, it is key to start early on with real projects, even before a strategy has been fully defined.

In addition to that, a top-down approach can never foresee everything, and therefore starting with an incomplete transformation plan that evolves over time is inevitable.

Regardless of how ambitious their digital initiative is, companies should start with quick wins in at least one of several areas, for example improving the customer experience while at the same time digitising internal processes.

As an illustration of how businesses are enhancing the customer experience, some energy companies are starting to offer mobile apps that allow customers to check bills and obtain meter data. More advanced offerings from retail chains allow customers to keep track of shopping lists, or even share lists among family members for them to add items, and order out-of-stock items through an e-commerce portal on their smartphone. Some of these customer facing improvements go hand in hand with optimised and simplified internal processes.

Another approach to benefiting from the digital mindset and technology is to improve internal processes and functions, such as finance or HR.

This approach is particularly relevant for B2B (business to business) companies, which place less emphasis on the end-customer experience. Digital technologies can improve the efficiency and accuracy of processes and thereby reduce costs, and they allow the company to run data-driven analytics to first analyse and then improve performance over time.

Whether a company begins its digital transformation by improving the customer experience or improving internal processes, speed is critical. Instead of taking the traditional, linear approach to rolling out new initiatives, companies should bring new ideas to market early on, collect customer feedback and refine the concept iteratively. Many accomplish this by means of the minimum viable product (MVP) process of prototyping.

The MVP process is based on the idea of the ‘good enough’ product. Rather than trying to perfect new services internally during the development stage, the company instead aims at getting them to market quickly, with just enough features included to make them functional. That allows the company to minimise its investment, test the functionalities and services in the real world (instead of in artificial settings such as focus groups) and refine them based on customer feedback. For example, the initial versions of apps and online stores are often quite basic, with new features and functions added over time, depending on how the products are used by customers.

The following example nicely illustrates this approach: A multinational big-box retailer operating in an emerging market launched a quick-win initiative with a mobile app to boost declining sales at its physical stores. Rather than develop a grand digital strategy or conduct detailed market research to determine the scope of the opportunity, the retailer outsourced the entire app development process so it could build something for the market quickly. When the app turned out to be a successful idea, customer-friendly features were added to the app, such as personalised coupons and offers, tools to plan shopping trips, automatic replenishment of regular purchases (through a subscription model) and even in-store navigation. It resonated strongly with customers and led to increased sales at the retailer’s stores, especially once management learned what worked well and continued to add new features, such as in-store WiFi and home delivery of goods purchased online.

It is important to note that we do not view a strategy as useless. The opposite is true. We strongly encourage companies to define a digital strategy.

A strategy gives direction and a preselection of approaches that fit the enterprise in terms of its values, know-how or synergy. But in no circumstances should the strategy definitions slow down the transformation. The MVP approach allows a validation of the strategy and gives the opportunity to try out transformation steps. The goal is to proceed in those small steps, see what works, encounter failure as quickly as possible and adjust the strategy.

Enterprises have three major challenges to making an MVP approach successful:

Firstly, enterprises must choose projects that have respective growth potential. Remember that the ultimate goal of digitalisation is to turn around the way a company works as a whole, including operational procedures and business models. This can only be achieved with ideas that have the potential to deliver a notable contribution over the long run. Therefore, every project should have its path to achieving scale sketched out before it is started.

Secondly – and this is quite a challenging step for many enterprises – you must free resources by abandoning ideas that appear not to be taking off. Even projects explicitly started to prove the viability of a business idea are hard to stop when they do not deliver the desired results. This is because projects are staffed with people who have their own personal agendas. It is therefore essential to establish rigid governance that supervises the outcome of MVP projects and implements the fail fast principle.

Finally, enterprises face the challenge of scaling up the most promising ventures. Several levers are available to accomplish this. The right one depends on the company’s level of ambition, the strength of its existing digital capabilities and external market factors (primarily the degree of disruption posed by new digital competitors). For example, one way to scale up digital initiatives is to acquire digital talent on a temporary basis and then bring it in-house over time.

As the company embeds talent, it can create digital units that serve as a centre of excellence.

11.7 Digital Identity

Mamoon Yunus — Tue, 31 Oct 2017 23:00:00 +0000

Identity is the most fundamental tenet of establishing digital trust. As a producer of digital assets, you have to know who is interested in using your assets. A passenger has to present a passport to an officer who verifies their identity before letting them board a plane. Similarly, in the digital world, a consumer of your digital assets or services has to provide digital identities such as a username and password, which the producer of the service has to verify before letting the consumer access the digital asset.

In the era of legacy mainframe systems, the burden of managing identity was low given the closed nature of such systems. As mainframes evolved into open distributed systems communicating over the Internet, identity management across internal systems and corporate boundaries became necessary. Identity stores such as LDAP[1] servers became a central system of record for identities with a variety of standards such as Kerberos, SAML and OAuth enabling the sharing of identity information.

With corporations rapidly adopting public cloud services with their own set of identity requirements and users moving to mobile devices, handling a large variety of digital identities is now a critical issue for companies.

Layered on top of the efficient handling of identities is building mechanisms that prevent identity theft[2] – an issue that continues to plague our society with profound political, financial and social impacts.

Multifactor authentication that requires additional ‘factors’ (e.g., biometrics or SMS validation) beyond a simple username and password is now becoming a norm for most organisations.[3] Email systems, such as Gmail from Google and many online bank applications, now provide such multifactor capabilities.

So, what are the challenges for large corporations?

Establishing identity (authentication): In a highly distributed ecosystem of IoT, cloud, mobile, enterprise systems and humans, each consumer of a service, human or machine, has to let the service know who is trying to invoke it. With artificial intelligence (AI) driven devices, such as Amazon Echo, iPhone Siri, autonomous drones and vehicles replacing human functions, the number of non-human services interacting with each other will inevitability surpass human-to-device interaction. These services have to consume digital identity tokens and then make a decision on whether to allow the consumer, human or non-human, to use it. Once the service has properly interpreted the identity provided by a consumer, it then has to go to a central identity store, most likely an LDAP server, and check if the consumer is on the list of known users. In a rapidly scaling digital API economy, a service consumer may quickly face the challenge that a producer service may only know how to interpret a single type of identity, such as OAuth.[4] So it then becomes the responsibility of the consumer to provide the token in the correct format in order to invoke the service. This is, of course, neither user-friendly nor a policy that can be kept up to cover a global market.
Establishing access rights (authorisation): Who gets to see or use what is a simple exercise for a single application. However, opening up hundreds or thousands of applications is a different story. Once a consumer’s identity is validated by checking against an identity store, the next step is to decide whether or not the consumer should be given access to the requested service. Such digital access policies have to be established based on the value and sensitivity of the digital assets and intended actions requested by the consumer. Managing authorisation involves understanding the business value of the digital asset, who should be allowed to use this asset and for what purpose, when it should be accessible and from where a user can request the digital asset.
Context is everything: As we just described, with a well-established digital identity, the next decision of whether or not to authorise the consumer to invoke a service usually involves a significant number of attributes, such as consumer location, membership level (e.g., TOP SECRET) and, most importantly, the content sent by and returned to the consumer. Without deep business-level understanding of corporate data, user profiles and roles, service invocation patterns and the business partnership ecosystem, effective context-based access policies are impossible to implement. Once a corporate-level understanding is established, the next step is to use this knowledge to deploy an access control gateway.

All identity policies and actions should be consistently enforced across an enterprise.

They should be actively managed and audited for compliance with corporate governance directives. Letting API service producers and consumers code their own identity policies right into the business service components should be avoided at all costs since it results in an inconsistent and non-auditable infrastructure with a high-risk profile. We therefore recommend establishing a centralised and dedicated identity layer, which decouples business logic and services.

This layer can be implemented by an API security gateway, which brings authentication, authorisation and context-based access control all together in a centralised gateway model for strong governance. It provides deep, fine-grained content-based access control in a decoupled manner by sitting between the consumer and the producer services. Through centralised access control policies, API security gateways enable rapid deployment of business services. This level of agility is crucial in an era of accelerating digital transformation.

Hybrid cloud environments with mobile end-user devices will continue to be the norm for most corporations. To succeed in a fast-moving, complex and heterogeneous environment, where flexibility and cooperation are expected by all partners, digital identity management is crucial.

The digital economy is inherently entropic: more APIs continue to be produced and consumed, new data and identity standards continue to emerge, and the enterprise boundaries and functions continue to blur.

To flourish in this digital economy, it is imperative for everyone to build a scalable, flexible and agile architecture that adapts rapidly in an everchanging environment without compromising security.

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[1] Lightweight Directory Access Protocol.

[2] Puscual, A., Marchini, K., Miller, S.: ‘2017 Identity Fraud Study: Securing the Connected Life’, Javelin Strategy & Research, 2017.

[3] Ackerman, P.: ‘Impediments to Adoption of Two-Factor Authentication by Home End-Users’, white paper, SANS Institute InfoSec Reading Room, 2017.

[4] OAuth (Open Authorization) is an open standard for token-based authentication and authorisation on the Internet.

11.6 Digital Trust

Mamoon Yunus — Tue, 31 Oct 2017 23:00:00 +0000

Trust is the glue that maintains social groups. From an evolutionary perspective, trust enables social animals to share their specialised skills for survival and well-being. With an ever-increasing body of knowledge, humans continue to specialise. This specialisation increases the necessity for an individual to belong to and interact with a large number of groups. Trust, ‘the shared interest and lack of malice’, becomes the key ingredient for individuals to perform efficiently in a large number of groups that form a vibrant society.[1]

Trust is pivotal for modern society.

With the advent of the Internet, human interactions have moved from the physical world to the digital world. Much like in the non-digital world, where individuals trust their doctor for health care, an aeroplane for safe transport and a restaurant for clean food, in the digital world, consumers expect that their interactions will be without malice. We trust that, when we purchase a TV online, the right amount will be charged to our credit card only once, the product will be delivered undamaged in the time frame promised and the information we provided to the merchant during this process will not be misused. Without this trust, we may choose to find a more trustworthy physical store for our purchase, a different online store or not to purchase the product at all. Without trust, commerce and innovation slow down and progress is severely hampered.

To begin with, we expect that any digital transaction entailing the exchange of money or personal information will be performed with the expected results.

We also expect it to be done without information leaking to other entities through digital theft or unauthorised sale of information. A service delivered with poor quality or followed by digital information being shared with an external entity that can then use it without the owner’s permission destroys digital trust and makes subsequent transactions with the entity less likely.

We expect that if something goes wrong, and the digital exchange is not what we expected, then the entity we do business with will be capable of reversing the adverse impacts of the interaction. This may include compensating us through refunds or undoing an unauthorised transaction. At a minimum, we expect companies to inform us that our information has been compromised so that we can be prepared and take action, such as changing our passwords to prevent further loss. We expect companies to be proactive and continually engaged to ensure that digital trust is maintained between us.

For example, we expect our banks to detect anomalous transactions based on our established historical behaviour. It is particularly important that enterprises understand and respect those customer expectations, because the digital world empowers clients to communicate dissatisfaction with a service provider via social media, news groups etc. and rapidly damage the reputation of the enterprise.

Digital assets are under increasingly sophisticated attack, a phenomenon known as cyber warfare.[2] Digital asset theft is motivated by either financial gain or socio-political activism. One of the largest known cyber thefts motivated purely by financial gain cost companies over US$300 million in 2013, when a group of five hackers from Russia and Ukraine stole 160 million credit card numbers.[3]

In contrast to blatant theft of digital assets, organisations are engaged in micro-targeting consumers by learning their online behaviour. Using cookies – artefacts that companies can read from or write to on our devices – companies now collect thousands of attributes about consumers, mostly without their knowledge. The increasing popularity of big data analytics and machine learning for micro-targeting has resulted in a stronger drive for collecting customer information without their explicit consent. Digital asset theft is a significant tool for socio-political activism.

Perhaps Ashley Madison, a dating site marketed to people who are married or in relationships, has had one of the most direct impacts on users’ lives.[4] With 32 million records of customers involved in extramarital affairs exposed, the breakdown of digital trust made a direct and perhaps irreversible impact on personal trust, a cornerstone of marriage.

Breaching digital trust for political activism can cause significant changes in the way countries conduct themselves on the global stage.

The impact of Wikileaks, the Snowden leaks and the Panama leaks continue to have a profound impact on public opinion, which translates directly into changes in government leadership and policies.

Technology, process and culture are the fundamental building blocks of establishing and maintaining digital trust. All three are interdependent: strong technology alone does not ensure digital trust without the supporting processes and culture. From cryptographic clay tablets of 1500 BCE Mesopotamia to the quantum cryptography of the twenty-first century, the desire to protect information and communication has evolved to keep in step with human technological evolution. Significant tools, products and frameworks now exist that enable digital trust. From sophisticated multifactor biometric authentication for establishing identity, to strong crypto-algorithms for ensuring communication privacy and integrity, a wide array of commercial and open-source technologies are available for establishing digital trust. Trust in the virtual world should be measurable through outcomes. If the outcome of a transaction or a process is not as expected, the trust between the transacting entities should be reviewed, strengthened or annulled.

Digital assets, for example credit card numbers, should be protected with as much, if not more, diligence as a physical asset (for example, a new car). Unlike physical assets, digital assets can be stolen quickly with minimal physical effort. Once stolen, a digital asset cannot be recovered. A stolen digital asset can be reused repeatedly and rapidly, unlike most physical assets.

Our digital presence continues to increase. This means that the digital ‘attack surface area’ also continues to increase.

Taking a holistic approach to establishing digital trust requires evaluating leading technologies (for example, face recognition as a login credential), implementing processes and building a culture in our ecosystem that considers digital trust as a fundamental pillar of modern society.

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[1] Warren, M. E.: ‘Democratic Theory and Trust’, Cambridge University Press, pp. 310-345, 1999.

[2] FBI, IC3, US Department of Justice: ‘Amount of monetary damage caused by reported cyber crime to the IC3 from 2001 to 2016’, Statista, 2017.

[3] Voreacos, D.: ‘5 Hackers Charged in Largest Data-Breach Scheme in U.S.’, Bloomberg, 2013.

[4] Zetter, K.: ‘Hackers Finally Post Stolen Ashley Madison Data’, Wired, 2015

10.5 Technical Skills

Léon Smiers — Tue, 31 Oct 2017 23:00:00 +0000

‘An ape may on occasion use a stick to beat bananas from a tree, but a man can fashion the stick into a cutting tool and remove a whole bunch of bananas.’[1]

The ability to apply technical skills is at the root of human superiority over other animals. The simple stone tool, possibly the first technical invention, was used as far back as 2.5 million years ago; scientific methods helped create a formal basis for technology and ﬂourished during the fifteenth century Renaissance; the Industrial Revolution followed a few hundred years later; twentieth-century technologies focused on automation and productivity; and computer-related technologies have been dominating the twenty-first century. Interestingly, the so-called digital technologies, a subset of computing technologies, have surged only for the last couple of decades, yet their impact has been explosive.

As we pointed out in on acquisition of digital capabilities, superior and appropriate technical skills are some of the necessary building blocks of the digital transformation of an enterprise. In fact, we explained in the ‘Digital in Action’ book how technology drives the digital transformation.

The difference in technologies, tools and methodologies between digital and traditional IT is often quite large. A strategy to balance the needs of day-to-day legacy business and the emerging digital transformation is to adopt what Gartner called ‘bimodal IT‘, also known as ‘two-speed IT’ or ‘multi-speed IT’[3] or a variation of the same (on previous page).Mode-1, made up of traditional software development life-cycle skills, mainly focuses on the longer-term IT projects typically directed at larger back-end record-keeping systems that evolve very slowly. Mode-2, using digital practices like Agile and DevOps, delivers projects much faster where the outcomes are frequently revised or replaced.

We can view technical skills through two separate lenses: ‘what technologies the enterprise must master’ and ‘how we should design and act using those technologies’. We can also recognise two categories of digital technology skills: ‘essential’, i.e., those basic ones that are almost always needed irrespective of industry or application, and ‘distinguishing’, i.e., those that provide special features unique to an industry or an application.

A quick summary of the essential technology skills:

Enhanced data (multi-source, formatted and unformatted) collection, (big data) processing and analytics extracting actionable insights.
Pervasive information integration providing ubiquitous and real-time information access to humans and machines, often done using application programming interfaces (APIs).
Intelligent business processes supporting extreme process automation with end-to-end transaction visibility leading to high efficiency and instant feedback to the digital customer.
Richly featured mobile apps handling a wide range of functionalities including product/service awareness, commercial transaction and payments and aftersales service.
Responsive and intuitive multi-channel user interfaces enabling human users to interact with the offered products or services quickly and easily regardless of their access modes.
Social media interactions facilitating product marketing and customer loyalty building, which may require exposing rich APIs and developing social media add-ons to products or services.
Cloud sourcing of applicable technologies enabling quick and cheap acquisition of latest and advanced technologies and tools without heavy upfront capital outlays.
Comprehensive security and regulatory compliance enforcement executed through transparent policies and lean (sufficiently adequate) governance and monitoring.

Some examples of distinguishing technical skills, which are typically industry-specific, are:

Super- or ultra-fast computing, useful in certain special applications involving genetics, weather or financial analysis and trading.
Sensors and Internet of things (IoT) with complex event processing (CEP) as in device-to-device communications, for example predictive maintenance and connected cars.
Big data collection, storage and analysis, potentially required in applications such as next-generation customer relationship management (CRM), real-time marketing and fraud detection.
Artificial intelligence and cognitive computing for self-learning machine applications.
Drones for special surveillance or packet delivery applications.

Technology-related architecture, in all its variations, such as enterprise architecture, solution architecture and deployment architecture, is heavily impacted by digital transformation.

Besides just accommodating the new technology components, digital architecture must enable emerging digital business models, be capability (as opposed to only technology) focused, and support bimodal IT and business agility by design (e.g., use of microservices and cloud-based services and infrastructure). An example of newer technology practices that complement digital technologies and architecture is the combination of agile development methodologies with DevOps to facilitate frequent release, say in days, of products using an automated chain of ‘concept to development to testing to deployment’ activities. Acquisition and retention of technical digital skills are among the greatest challenges of digital transformation.[2] Hence, dedicated leadership attention from the CDO Office and innovative HR practices are critical to closing this skills gap.

And, besides developing digital talent from within, a company must also consider external sources such as consultants, partners or M&A to be just as important a part of their technical skills acquisition strategy.

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[1] Sofroniou, A.: ‘Technology, A Study of Mechanical Arts and Applied Sciences’, lulu.com, p. 59, 2013.

[2] Daub, M., Wiesinger, A.: ‘Acquiring the capabilities you need to go digital’, McKinsey, 2015.