Innovation: Driven by Startups and enablers of Digital Transformation

There are 4 core enablers of the digital transformation that are key for today’s innovations and technologies. These 4 core enablers are:

  • Automation
  • Connectivity
  • Digital data
  • Digital customer access

In addition to these core enablers, there are interdependent / correlated enablers of course, i.e. cloud computing, adaptive manufacturing, autonomous vehicles, artificial intelligence, the internet of things, etc.

Leveraging these enablers lead to so-called Smart Products and Smart Services which heavily base on collected data (from Big Data to Smart Data), hence create an ideal Product-Market-Fit and at the same time accelerate innovation cycles and the competitive pressure.

A Smart Product can stand for very different tangible assets and therefore includes complex industrial machines and plants as well as privately used devices e.g. in a smart home and even your smartphone. Within the industrial sector, smart products (technical systems) are usually cyber-physical systems (CPS) that allow the coupling and coordination of computing power and mechanical elements. These products or systems typically “talk” to each other (machine-to-machine; M2M) and exchange relevant operational data, which they typically collect using different sets of sensors, and they can event (re)act on that data using actuators.

Smart Services are individually configured packages of (smart) products and services over the Internet. The focus is on private and commercial users. With the help of digital data from all areas, smart services are tailored to their preferences and situation-specific “as a service” to generate value-add. Digital platforms and marketplaces play a central role: Here, products and services are displayed virtually, combined, refined with additional digital services and offered as smart services.

A smart product typically ends up in a smart service, and both nowadays are mainly created / invented by startups. Not only since founding a startup has never been so easy – just take a look at all the crowdfunding possibilities – but also due to the importance of diversity and culture within a company: corporates typically do struggle with employee engagement and with their amount of hierarchy levels, which makes them very slow in becoming digital leaders:

DMM

Hence today, corporates do rely on startups, driving external innovation or by hiring from or M&Aing them, but also using accelerators, incubators and innovation hubs and labs to not doom in the digital transformation age.

Cheers,
Sebastian

My Bot and I – Digital Learning, Working and Living

Bots and other digital assistants, which interact with people in natural language and support us in a multitude of ways, have been the subject of many companies at least since Microsoft’s Build Conference 2016. Certainly, bots are only one form of the digital transformation, but there is no doubt, they are one of the fastest growing.

Why?
Well, here are some of the key reasons:

1. Ease of use
Bots can be controlled by natural language. Everyone can use them. Users do not have to first learn where a particular menu item or function is hidden, which best practice must be adhered to, or which keyboard commands are valid.

2. Versatile valuable data collection
In addition to voice recognition (paradigm shift from graphical user interfaces to conversational user interfaces), bots are also able to recognize emotions and gestures (and much more) of the user if desired. They could, for instance, recognize if someone is falling down and call for help. In addition, the entire context of a user can be better captured, which can lead to completely novel data correlations; e.g. checking how much more satisfied and productive employees are after switching to S/4 HANA.

3. Artificial Intelligence learns at every minute
Bots can also use cognitive technologies to learn by themselves. The more questions they answer and the more data they collect, the more cunning cognitive bots become. They are similar to a child who brings a certain DNA and then learns through education, social interaction, further education, and so on.

4. Automation of processes
Bots can be provided in a variety of ways, with different skills, knowledge levels, personalities, and connections to other bots, as well as software applications, or hardware (e.g., smart homes, smart factories, or smart offices). They can be equipped and expanded with a wide variety of sensors and with very practical as well as versatile actuators.

It is therefore not surprising that bots have been used by companies worldwide for a long time, across all industries. CB Insights presented a great overview in September 2016 (https://www.cbinsights.com/blog/corporate-chatbots-innovation/), listing bots from companies like Taco Bell, Domino’s, Burger King, Yahoo, AT&T, CNN, KLM, Fox News and many more.

Bots are already part of a wide range of business processes worldwide. Often even without the user noticing it. And even in the private sphere, language-driven assistants such as Cortana, Siri or Echo already are a cross-generation paradigm; especially in Asia and North America.
Another “trend” of digitization is the reduction of business process outsourcing (BPO) projects worldwide. Alone between 2010 and 2014, the outsourcing industry in India, one of the most important BPO countries, has halved according to KPMG. (https://assets.kpmg.com/content/dam/kpmg/pdf/2016/02/bots-in-the-back-office.pdf)
Shared services organizations and/or outsourcing customers increasingly rely on so-called Robotic Process Automation (RPA) rather than on human workers or traditional off- or near-shoring anymore, since RPA provides 20% to 30% higher savings than BPO engagements.

RPA solutions can, however, experience an analogous advancement here. Traditional RPA tools are based neither on bot technologies nor on artificial intelligence. They are also detached from single-source-based content creation. This means that, for example, process documentation, training documents and the automation projects must be created and maintained independently of one another with increasing overhead.
But what happens when you combine bot technologies, artificial intelligence, RPA and single-source-based authoring tools?

Got curious? Comment here or reach out to me if you want to discuss…

Cheers,
Sebastian

Social Robots – An introduction to the robotics market

Let’s dive a bit into the robotics market today.

There are two main categories of robots: industrial robots, which we know from the automotive, high tech and other verticals. And there are service robots, which we find in hospitality, healthcare, but also at home, like vacuum cleaners for instance. Following research done by KPMG, there are roughly 30 million robots active today. 6% of these are industrial robots, and 94% are service robots.

The social robots form a special class of service robots; Currently there are approximately 2,2 million active social robots, which corresponds to 8% of all service robots. They interact and communicate on an emotional, personal level with people, and not just with other robots. They react differently to the respective individual. They are integrated into daily life and replace, because of their nature/ability to interpret and imitate human behavior, in some cases even human relationships – especially in Asia, where (social) robots are already common and even participate in family life; The best known and probably the most widely used bot is certainly Pepper, which is available since mid 2015 and (according to Inc) sold more than 7.000 times alone in Japan already – however the Kirobo Mini, Buddy, Kuri and other bots, will certainly create some demand in Europe and the USA as well.

But also service robots that do not accompany us directly in our daily lives or don’t live with us in our own home can be social. For example, such bots interact with us in hotels, hospitals, shops, museums, etc. (e.g. relays, LEA, Oshbot, …) – although these service robots are not really socially, as they replace jobs, they are also classified as social robots. Ultimately, the built-in sensors, actuators and the brainware (an artificial intelligence/cognitive computing thing) are decisive for the perceived “social behavior”.

Examples of sensors might be video and audio – e.g. via webcams, microphones – but also geo-coordinates, temperature, pressure, light/brightness, acceleration, ionic strength and many other measurable variables.

Actuators or triggered actions can be virtually anything: dialogues with a person, other robots or even with your smart home, sending information/alarms, making the robot move/drive, etc.

Apart from the hardware and software of the sensors and actuators in robots, social robots do in addition have a that brainware piece, which allows the the robot to learn and “develop” itself; It represents more or less the personality and logic of the bots, the cognitive abilities, and generates the actions due to the sensory inputs.

For instance, when the sensor system films a face, the brainware is responsible for face, emotion, and speech recognition, and more. It decides/interprets how a person feels, whether she is alone, what the person is doing or maybe has just fallen, and it can even make recommendations for action. The brainware that is created/growing by machine-learning is an essential aspect of cognitive computing and artificial intelligence. In one of my next posts, I will tell you more about cognitive computing – so, stay tuned.

Cheers,
Sebastian Grodzietzki