Category Archives: Digital Innovation

Smart Machine Marketing and the Algorithmic Economy

The reason why Smart Machines are so much more powerful than conventional computer programs are the advanced AI algorithms and the data that they can absorb. Smart Machines can sense their own state and their environment, can communicate with other Smart Machines, they are self-learning and can solve very complex problems, and they can act, sometimes autonomously. There are many technologies behind the capabilities of Smart Machines. The most important enabler is the massive amount of computing power and storage that is available today for a relatively cheap price, which makes it finally possible to apply computational heavy artificial intelligence algorithms that would have not been possible some years ago.

Many characteristics distinguish traditional software applications from Smart Machines. Computers have always been pretty good in repetitive and clearly described tasks and in applying strict logic and complex mathematics. An abundance of tasks today are solved by computers much faster, cheaper and more reliable than by humans. Yet, in many ways, computers appear oftentimes annoyingly stupid. Have you tried to have a meaningful and interesting conversation with a computer? It can be a difficult and typically very frustrating endeavour. What computers are missing is the ability to understand the meaning of what we have to say. This is because language is very ambiguous. The very same sentence can mean something completely opposite if said in another situation or by a different person. “I love this computer” could mean either did I really like my computer a lot but it could also mean that I really hate my computer because it doesn’t do what I want it to do. It is very unlikely that love refers to romantic love in this context. The idea that computers can think like a human sounds stretched, it is, however, closer than you might think.

It is changing with the up-rise of Smart Machines. It makes machines being able to handle situations with ambiguity, sparse information and uncertainty, thus, be able to solve human kind of problems. Instead calculating the optimal solution using a predefined algorithm, smart machines evaluate different options and choose the best option out of the possibilities. Problems do not need to be provided in a specified machine readable format, they can be simply formulated in natural language or even normal speech. Looking at the context of the problem makes it possible to interpret the question correctly. When I ask a smart machine “what is the best restaurant?”, it should understand that I am probably looking for a good restaurant that is not too far away from my current location. Based on the outcomes of an action, smart machines can learn and improve their problem solving. Instead of being programmed, they can read PDF documentations to understand a business process and observe how humans perform a business process to build its own knowledge base and eventually be able to handle the business process on its own.

The key components of a Smart Machine are depicted in the figure and will be explained in detail in the following. An incentive and rule system needs to be set for a Smart Machine which provides a purpose for the Smart Machine to exist (e.g. as a self-driving car) and the rules it needs to obey (e.g. ethics, law, company procedures, business goals).

Smart Machine Marketing Artwork

In order for machines to see, feel, hear, smell, and taste like human beings, all aspects of the physical world need to be translated into “digestible” data for machines to process, reason, and act. The rise of low-cost sensor technologies and the Internet of Things with its connected devices enables the collection of data from the physical world without human interaction. All senses are needed to cover an entire customer journey from inspiration to usage. The augmented senses of machines allow a broader, deeper, and more personalized customer experience. Sensed information is fed, interpreted, filtered, interlinked and used to initiate further activities.

The most important ability of Smart Machines is to process the sensed information similar to the way us humans process information (i.e. empirical learning). Smart machines are able to think and solve problems by understanding and clarifying objectives (and sometimes coming up with their own objectives), by generating and evaluating hypotheses, and by providing answers and solutions like a human would do (and unlike a search machine which gives a list of results). Smart Machines are self-learning, they can adapt their own algorithms through observing, discovery and by doing.

Finally, Smart Machines can act, by visualizing and providing the responses to a human decision maker, by informing or even commanding a human to execute certain activities, or in the extreme case, by completely autonomously executing a business process or any other actions. Based on the results of the actions, Smart Machines are able to re-calibrate their goal setting.

The impact of Smart Machines will be observable in three domains for Marketing Professisonals. First of all, customers will get a more contextualized and personalized experience. Secondly, the marketing departments will be able to do more with less people building on automation and scale of intelligent algorithms that take over some of the human labor. Thirdly, there will be advances in the customer journey possible which are of disruptive nature.

The marketing profession will be impacted fast and significantly by Smart Machines and the Algorithmic Economy. Personalizing and contextualizing the customer experience is the aim of everyone. But, creating meaningful continuous 1:1 interactions can only be feasible on a large scale with thousands or millions of customers if Smart Machines take over a lot of the work. This means that smart machines take over work reserved for humans in the past, as, for example, generating new content, and supervising staff in retail stores to ensure high customer engagement. It also means that those companies that still struggle with data-driven marketing will be in deep trouble. Those who embrace Smart Machines will be able to drive productivity beyond the imaginable for marketing and sales within the next decades.

Like all things in life, Smart Machines are all a matter of perspective. For marketing divisions in traditional companies, they might be seen as the biggest threat in history. The way most marketing departments work today is very reliant on human labor and decision making. Shifting the work to Smart Machines will make a lot of the abilities needed for traditional marketing personnel redundant and will require new capabilities that the workforce does not necessary have. For others, Silicon Valley startups and companies, Smart Machines generate an once in a lifetime opportunity. Smart Machines enable them to scale their limited resources and, thus, be able to challenge even the largest established players in their own strongholds, irrespective if it is retail, consumer goods, banking, insurance, manufacturing, entertainment or any other type of industry which requires Smart Machine Marketing.

Is it Time for a 2-Speed Business?

Shortly before my summer break – a lovely holiday in Northern France – I gave a keynote at a data science event that highlighted the importance of a bimodal IT for digital innovation.

The key idea behind bimodal IT is that IT needs to offer a second mode in addition to traditional IT that is more risk taking, agile and customer-centric in order to drive digital & analytics innovation more effectively.

Mode 1 is characterized by Gartner as the traditional mode of IT, which has a focus on reliability, is plan and approval-driven, uses large enterprise IT suppliers and typically follows a waterfall approach for implementations.

Mode 2 emphasizes agility and, hence, uses agile implementation approaches, it utilizes often small, new innovative vendors and works closely with the business to drive fast and frequent customer-centric business innovations.

There are many organizations that have started to establish a second, more agile, mode of IT (e.g. in form of a data science lab, a digital factory, or an agile development and DevOps department) and they usually run into two major challenges which impede them to reap the expected benefits:

(1) The two modes of IT are not synchronized well enough

(2) Business is not able to engage effectively with agile IT

I will explain these issues in more depth in the following and some lessons learned how to resolve them.

(1) The two modes of IT are not synchronized well enough

What many organizations get wrong is that they focus to much on creating the new agile Mode 2 of IT.  However, this is only one component of implementing a bimodal IT. The real challenge is how to synchronize both modes so they can play as a team. Having them in silos will not only create conflicts, but also will limit the success of any projects that need both Mode 1 and Mode 2 resources to succeed – which is rather the usual. So, what organizations need to establish is a bridge between the two modes.

Practically speaking, it all starts with mutual understanding and respect between the two modes. If Mode 1 resources have the feeling the they are a second class of IT, they will stop supporting Mode 2 and hinder them wherever possible. Leadership needs to communicate that no mode is better than the other, and both modes of IT are equally needed for success. Mode 2 resources need to understand that Mode 1 is crucial to renovate the core of IT, which enables innovative digital apps to be built on top of a healthy infrastructure efficiently and securely.

Moreover, there are touchpoints between Mode 1 and Mode 2 that require bimodal synchronization through explicit governance:

~ When a new application is planned to be developed, selection criteria have to be defined that outline which implementation should be done in which mode of IT.

~ When a new Mode 2 implementation project is starting, it has to be examined if interfaces to Mode 1 applications are needed and/or if other Mode 1 resources are required.

~ In particular, when the Mode 2 product is supposed to be released in a Mode 1 production environment, traditional release management needs to be involved already in the beginning of an agile project.

~ Finally, when a Mode 2 product is released, there might be a decision to further manage it in Mode 1 in the future.

(2) Business is not able to engage effectively with agile IT

Today´s businesses are not ready yet to engage with Mode 2 IT in a productive manner. This has two main reasons.

First, the second mode of IT is all about experimentation. Trying out new features, new approaches to analyze data and new ways to interact with customers, and taking into account that many of the experiments will not turn into viable products after all. Today, most traditional organizations have not developed a mindset for experimentation yet.

Second, using agile IT methods requires a much more intense participation of business during IT projects. Business is used to “throw business requirements over the fence” and IT would take them, take a few months or even years to implement them, and would come back eventually for testing. In the meanwhile, business does not need to spend much time for the  IT project. This is not the case for agile projects. In each sprint, the business needs to closely work with the developers and defines the business requirements on the run during the project.

These two points highlight some of the obstacles that come up, when there is a two speed organization on the IT side, but only a one speed organization on the business side. The solution is simple, but substantial: Many large organizations that I work with have recognized the need to establish also a second mode of business, which is more experimental, fast paced and enables real digital innovation.

The consequences are visible: There are more and more business labs and business innovation centers of large enterprises popping up around the world in addition to data labs that have the role to work with agile IT to come up and test new innovative ideas in a fast mode. They aim to imitate a startup environment  where creativity, experimentation  and disruptive innovation is in the focus. The results are impressive so far. Mode 2 IT can be much better utilized and the collaboration between business and a bimodal IT becomes significantly better when a two speed business has been established.

This is only the beginning, but one new imperative clearly emerges: It is time for a two speed business for any organization. The pace of change will become faster and volatility will increase in the future. So, let´s get business ready for it.

 

Dr. Alexander Borek advises Forbes 500 companies in multiple industries with regards to their digital transformation, data governance and Big Data Analytics innovation strategy.

All opinions in this blog are written in private capacity and do not express or reflect the opinions of his employer.

Frontend Versus Backend for Digital Innovation

Very simply speaking, business processes can be divided into two categories, namely, front office processes, which are all customer interfacing business processes and, back office processes, which are all business processes that have no customer touch points.   The back office is usually what the customer does not see.

Let me use a simplified exemplary scenario to explain how all these things interplay:

A customer finds a red wardrobe in a catalog and would like to know if his nearest furniture shop has this particular product available to make sure he does not drive 35 miles to the store for no reason. The front office business process in this scenario is that the customer asks the question if the product is in stock and gets the answer to his question. To answer his question, we need to know which products are available at any given time. Hence, there is also a back office process required, which is to keep track which products are in stock and which ones are out of stock at the moment.

If the front office process and the back office process are both not digitized at all, the customer has to give the store a phone call and hope that some staff member will pick up the phone, go to the shelf where the product is stored and checks visually if there is still a red wardrobe available for sales.

Examples Front office process Back office process
Not Digitized Process Customer gives the store a phone call. Staff member picks up the phone, checks if the product is available Staff member goes to the shelf where the product is stored and checks visually if there is a red wardrobe still available for sales
Digitized Process Customer types “red wardrobe” and his address at the web site of the furniture store and it shows that product is available in the nearest store All products contain an RfiD chip that can track them on the shelf. IT System can provide real-time availability information to staff and customers.
Automation of Business Process Website makes call obsolete and staff does not need to take an additional phone call RfiD tracking of stock instead of visual check if product is available
Digital Data Generation Customer address and product of interest is captured Stock level and availability for each product is captured
Digital Data Usage Data about availability of red wardrobe is used to answer request Data showing which RfiD tag is linked to which product is used to track stock level

In contrast, if we want to digitize the front office process, we could create a website through which the customer can check if the wardrobe is in stock. The website would automate the business process in the front office. By typing the product name of interest at the website, the customer provides this information in a digital format. The result comes back on the screen, which uses existing digital information about product availability in store. The data about product availability could still be entered into an IT system and maintained manually by an employee in the back office. The customer would not notice if the back office process is digitized or not as long as the information is up to date.

Finally, if we want to digitize the back office process in this scenario, we could, for instance, automate the tracking of products in the shelf by putting RfID tags on each product (RfID = Radiofrequency Identification). An RfID reader can then wirelessly detect how many products are on the shelf at any given time and store this information in an IT system. The IT system can provide this information to the website so it is visible to the customer. But the front office process does not necessarily have to be digitized. Even when the customer calls in, the staff member still saves time. The staff member would not need to make a visual inspection to capture the stock level as he can look up the product availability in the IT system.

Even if your customer does not see what is going on in the backyard, digital transformation of your back office is very important to your business success. A great customer experience is often not possible without efficient and effective back office processes. In our small furniture shop scenario, when the stock level and availability for each product is captured digitally, it is ensured that the customer has always accurate information in real time. Secondly, making your back office running more efficient with digital transformation can save you a lot of costs and make your operations run smoother and leaner. In our small example, you would need a lot of additional service staff that answers service requests. And thirdly, digital transformation makes your back office more effective, which can help you, for instance, to optimize your supply chain management, to prevent fraud, manage business performance better, optimize your physical assets, create the highest value with your human resources and better manage your finances.

In essence, executives should avoid to focus all their digital innovation efforts only on what is shiny and visible to the customers, the inner core of your business can be an even stronger competitive differentiator, even if that is not directly seen from the outside. And not everything that shines is gold.

Free Digital Lunch for Retail Banks

“When I go to Silicon Valley…they all want to eat our lunch. Every single one of them is going to try.” Jamie Dimon, Chairman and CEO of JPMorgan Chase

The pressure to innovate with digital technologies is enormous for banks. Yes, the competition is tough between existing banks. The biggest threat comes yet from outside the banking sector by startups and companies that never knew the pre-digital era.Tunde Olanrewaju, principal at McKinsey´s London Office highlights where the focus of digital transformation for banks lies: “Most of the potential value in digital banking comes from the impact on the cost base, particularly in the areas of automation of servicing and fulfillment processes and migration of front-end activity to digital channels.“ When you want to provide shinny new digital customer services to your customers as a bank, you have to sort out a lot of the back office challenges first. 60% of customer dissatisfaction sources and 10-20% of contact center volumes originate from execution issues in the back office.

Some of the results banks are achieving through digital transformation of the back office are truly game changing, for example:

  • Managing an end­ to ­end payments solution
  • Automating manual controls and processes
  • Simplifying the business by moving away from non­core products
  • Consolidating operating call centers
  • Optimizing the branch network
  • Reducing cost of service without reducing quality of service
  • Product back-office automation
  • Document-management digitization
  • Automation of credit decisions
  • 24/7 availability via interactive voice response

One way to achieve operational cost reductions is to get rid of the old branch structure. For example, piloted in Malaysia, the Philippines and Singapore, Citi Bank launched a new global initiative called Citibank Express, which is a next-generation ATM that allows clients to access nearly all the services available at a traditional branch. 

Barclays Bank, as many large banks that combine retail and investment banking, had to face a lot of mistrust by consumers in the aftermaths of the global financial crisis. And Barclays knows that cultural change  at the bank is necessary. “We were too aggressive, we were too short-term focused and too self-serving,” admitted Barclays CEO Antony Jenkins in an interview with CNBC, “The industry, and Barclays, got it wrong on occasions.” And digital technology is an important element for Barclays to restore trust with its customers.

In 2013, Barclays created two top positions for its technology driven transformation, a group chief data officer and group chief digital officer. Usama Fayyadd was appointed as chief data officer. He is regarded by many as the first executive ever to be titled chief data officer when he took on the role at Yahoo no less, back in 2004. Although a high profile executing, Fayyadd had not much previous banking experience. The firm-wide governance of data is something that is being looked with a view to simplification and gaining both efficiencies as well as a better overall quality of data. Shadman Zafar, who holds the position of the chief digital officer, has previously worked for mobile network giant Verizon.

“What is happening is that customers are becoming much more used to using technology and want to use technology to deal with their banking. Why not check your balance on your smart phone? Why not pay a check on your smart phone? That means that over time we are seeing a shift how customers do business and technology allows us to serve them where and when they want to be served. […] I think we should accept that, over time, there will be more and more delivery of our services by technology”, says Jenkins. “Barclays has spent time and money on mobile – and it shows”, comments Forrester analyst Stephen Walker. In 2014, Barclays has been recognized to be the top mobile banking provider. Moreover, 6,500 cashiers from Barclays branches are trained as a new breed of ‘community bankers’, who, armed with iPads, will help customers use automated machines. A new voice recognition system and a voice-biometrics security system is planned to be rolled out to its 12 million retail customers in 2016.

Banks have to live with a lot of legacy systems. In fact, up to 90% of the average bank´s IT budget is spent on keeping up those systems. To avoid replacing the legacy systems, banks have often built new applications on top of old ones and added new interfaces. A typical retail bank has to manage and monitor between 300 and 800 back-office processes. Many of these tasks are redundant tasks, create excessive manual processing with slow response times. The potential for digital transformation is huge. Automating and digitizing processes can help to mitigate the risks of human error and reduce paper consumption costs. It can lead to leaner channel and organization structures, a streamlined governance, a more agile culture and an enhanced revenue model.

The Pressure for Traditional Companies

Characteristics of a new digital world

The world is changing rapidly and becoming digital. Digital technologies fundamentally change how we live, work and interact and will also transform the basis of competition in most industry. This can make “the physical world better, worse, or just different”, as Eric Schmidt and Jared Cohen describe it. What are the characteristics of this new digital world? We can observe three major trends which will be laid out in more detail during the next paragraphs. The physical world is becoming rapidly more instrumented and interwoven with the physical world. Having all the information about the world digitized allows computers to analyze this data with speed, precision and context-awareness, providing a new source of intelligence and automation. MIT researchers Eric Brynjolfsson and Andrew McAfee have announced the second machine age: “Now comes the second machine age. Computers and other digital advances are doing for mental power – the ability to use our brains to understand and shape our environments – what the steam engine and its descendants did for muscle power”. As a large proportion of the whole planet will be equipped and interconnected with smartphones and integrated mobile computing devices at home and everywhere else in the not too far off future, this new intelligence will be fully integrated into our lives.

When I talked to top executives of incumbent leaders in traditional industries such as banking, insurance, consumer products and manufacturing, they all admitted that their biggest threat for their companies future they see are digital savvy companies like Google, Facebook, Amazon and Apple and new technology startups from Silicon Valley and other innovation hubs.  CEOs have carefully observed how new digital players have exiled established players in the retail, music and TV industry and they fear that the same will happen to them. The new wave of digitization does not stop at the online channel. It includes every part of our lives through the new mobile channel, social media and the Internet of Things (sensors and chips hidden in traditional products).

Companies have entered the digital race

Data and digital technologies are becoming the new major source for productivity, competition and innovation. Collecting, combining, analyzing and using the large volumes of data available to us can provide companies with such valuable insights that it can be a true game changer in nearly any industry. But real change comes only, when the new data and insights are fully integrated into the business processes of the company, and when customer experiences and the underlying business models are redesigned. So, if you take away only one thing about the digital world that is evolving, this should be it:

The most important imperative for business leaders is that data will be the basis of competitive advantage across all industries and that companies need to digitally transform to reap the benefits

Naturally, data driven innovation and digital transformation get a lot of C-level executive attention today. Many companies are embarking on a journey to transform their core business processes with data and digitization. It is not enough to simply set up a single project that looks at disruptive technologies to compete in this brave new world. Leading companies have started to re-think their entire business.