IoT im Klartext: Herzschrittmacher überführt Brandstifter

Die Story war diese Jahr schon in der Presse in den USA, wollte aber unbedingt darüber bloggen, da es ein konkreter Anwendungsfall ist der letzte Woche auf dem Gartner Data & Analytics Summit in Frankfurt diskutiert wurde.

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Bei der Untersuchung des Hausbrandes zog die Polizei dabei die Daten eines Herzschrittmachers heran. Wie Ihr wisst ist der Herzschrittmacher ist ein Ding (im Englischen als Thing oder Device bezeichnet) der ja nicht nur die Pumpe am Laufen hält, sondern auch Herzfrequenz und Cardio-Daten aufzeichnet und dokumentiert. Sicherlich noch wesentlich mehr, bin aber kein Arzt und kennen glücklicherweise auch niemand mit einem.

Die Daten bewiesen dass der Mann in keiner Sekunde nervös, oder gar in Panik war als er den Notruf absetze und das Haus verließ. Seine wichtigste Habe konnte er sogar noch retten.

Das Ende vom Lied: er wurde der Brandstiftung und des Versicherungsbetruges überführt.

Diese Geschichte ist nur einer von zahlreichen Anwendungsfällen des Internet of Things (IoT).

Die Anzahl der “connected deviced” wächst rasant und wird schon bald die Weltbevölkerung bei weitem übersteigen. Alle Unternehmen und Organisationen werden davon gebrauch machen. Alle.

It is time to master things.

Es ist an der Zeit das “Internet of Things” zu nutzen. Für effiziente Produktion, bessere Produktentwicklung, besseren Kundenservice clevere Up-Sell-Strategien und viel ,viel mehr.

Was brauchen Unternehmen heute um das IoT-Potential wirklich gewinnbringend nutzen zu können?

In erster Linie Master Data Management (MDM). In meinem nächsten Blog werde ich das Thema tiefer beleuchten. Dann geht es nämlich um die Kriterien für das “MDM for Things”.

Dabei geht es um wesentlich mehr als das aufnehmen, verarbeiten, anreichern und veröffentlichen von Produktinformationen.

Dabei geht um unglaubliche Mengen. Experten schätzen das Apple bisher 33 Millionen mal die Apple Watch verkauft hat. Was bisher ein Produkt im Onlineshop war, wird dann zu 33 Millionen Versionen mit komplett unterschiedlichen Daten.

Aber was tun mit diesen Daten?

Was tun wenn eure MDM/ PIM Lösung heute schon mal bei einem Export oder Update des E-Commerce Shops in die Knie geht auf Grund von wenigen Millionen Artikeln?

Fortsetzung folgt.

Klartext: Das ist die Wahrheit – Schluss mit den Mythen rund um den MDM Gartner Magic Quadrant

 

Der “Gartner Magic Quadrant for MDM Solutions 2017” wurde kürzlich veröffentlicht. Einen kostenlosen Download gibt es hier. Ein guter Anlasse mit ein paar Gerüchten aufzuräumen die seit Jahren kursieren.

Ein Analyst verglich den Magic Quadrant einst mit Fußball. Da hatte er meine Aufmerksamkeit. Er meinte, Analyst im MQ zu sein, ist wie Schiedsrichter im Mädchenfußball. Er meinte das nicht despektierlich, da seine Kindern Fußball spielen. “Vor dem Spiel will jeder Software Anbieter dein Freund sein. Doch bereits in der Halbzeit hassen dich alle.” Der Spruch sorgte für Gelächter. Schließlich saßen im Publikum auch einige Software Anbieter und fühlen sich den Spiegel vorgehalten.

In den letzten zehn Jahren hatte ich die Möglichkeit der aktiv an verschiednen MQs mitzuwirken, in erster Linie für Master Data Management und Data Quality. Es ist also an der Zeit mit ein paar Gerüchten aufzuräumen, dabei will ich mich auf die drei wichtigsten beschränken.

Gerücht 1: Wer am meisten bezahlt steht ganz oben

Unglaublich viele Menschen haben die Eindruck dass die Softwareanbieter die das meiste Geld an Gartner bezahlen sich im Quadranten noch oben bewegen. Das ist sowas von falsch. Gartner trennt alle finanziellen Prozesse enorm strikt von dieser Marktanalyse. Der Prozess und die Integrität der Analysten wie Bill O’Kane, Simon Walker, Michael Moran, und zuvor Andrew White sind höchst professionell.

Sie betreiben einen hohen Aufwand um ein reales, neutrales Bild des Marktes und der Anbieter zu zeichnen. In diesem Fall bezieht es sich auf den Zeitraum 2016 und das erste Quartal 2017. Die einzige Kritik die angebracht ist, ist dass die Daten bereits jetzt schon etwas veraltet sind.

Gerücht 2: Die großen Anbieter sind immer vorne

Alle reden in diesem Tagen von “Transformation” und “Disruption”. Meine Damen und Herren, es ist kein Hype, es ist Realität. Die Tagen in denen nur die ganz großen Anbieter, wie SAP, IBM und Oracle, den Markt dominiert haben sind vorüber. Beispielsweise hat im letzten Jahr meine ehemalige Firma, Informatica die Spitzenposition im MDM Magic Quadrant erreicht, basierend auf den beiden ehemaligen Lösungen für Kundendatenmanagement (Siperian) und Product Information Management (Heiler). Ich bin dankbar dafür, dass ich die letzten zehn Jahr dazu beitragen konnte.

Bis heute haben viele neue Ansätze und Start-ups den Markt und den status quo der Etablierten herausgefordert. Es herrscht eine starke Dynamik im MDM Markt. Neue Technologien, wie Big Data & Artificial Intelligence bieten neue Möglichkeiten an die Herausforderungen der Unternehmen zu lösen. Es ist Zeit für neue Wege und neue Ansätze um das Volumen und die Volatilität von morgen in real-time zu lösen. Beispielsweise wenn es darum geht Unstrukturierte und bekannte Datenformate in der Supply chain zu verarbeiten, oder große Mengen an Produkten im E-Commerce in real-time zu aktualisieren. Denken wir an Black Friday, Cyber Monday oder anderen Shopping Events.

Gerücht 3: Ein Bild sagt mehr als 1000 Worte

Jetzt mal ehrlich, das erste auf was Sie achten ist das die Darstellung des Magic Quadrants. Wer steht wo? Was hat sich verändert? Wo steht mein derzeitiger Anbieter. Wer ist gar nicht mehr dabei? Ja es hilft einen ersten Eindruck zu gewinnen, aber es ist viel zu kurzsichtig sich nur auf das Chart zu konzentrieren.

Analysten und Anbieter investieren wirklich viel Zeit in dieses Projekt, sie alle verdienen es, dass sie als Leser tiefer einsteigen. Lesen Sie den Text, lesen Sie zwischen den Zeilen. Wussten Sie, dass der Magic Quadrant in erster Linie das Unternehmen beurteilt? Zusätzlich gibt es noch das “Critical Capability Report for Master Data Management” der die Lösungen funktional im Detail beleuchtet.

Zu guter letzt

Es wurde bereits viel geschrieben zur neuen Sicht auf den Markt mit der Einführung es neuen MQ in 2016, als die beiden separaten Quadrants für Customer Data bzw. Product Data aufgelöst und ein ganz neuer definiert wurde.

Mein Tipp: Wenn Sie den MQ nutzen um eine MDM/ PIM-Auswahl zu treffen, denken Sie an die Zukunftsfähigkeit der Lösung und des Anbieters. Das Thema ist von strategischer Bedeutung für Ihre Digitale Transformation, für den Erfolg ihres Unternehmens. Entscheiden Sie sich für Zukunft, nicht die Vergangenheit.

Gartner Magic Quadrant for Master Data Management als kostenloser Download.

IoT: Pacemaker Helped Police To Accuse Someone With Arson

The story was in the press earlier, but I have to admit that I heard it at the Gartner Data & Analytics Summit in Frankfurt for the first time this year.

In this case the police called pacemaker data an ‘excellent investigative tool’ that provided ‘key pieces of evidence’ to charge a man with arson and insurance fraud.The data collected from his “device/ thing” (heart rate, pacer demand and cardiac rhythms) before, during and after the fire, clearly proved that he was not in panic.

This story is just one of many in the world which will be massively impacted by the IoT (Internet of Things). Numbers of connected devices are growing by orders of magnitude. Every business will use data from outside.

You may thing the apple watch on the apple web shop is only two sized and about ten different arm bands and in the meantime three generation which is about 60 different product SKUs to manage. So why should I need a MDM solution to manage this? Well, the press says the watch was sold more then 33 million times, which massively changes the game about data. 33 million different data sets and profiles (for example: I am a runner and my neigbour does not do any sport but has the same watch), which can be used to improve product development or cross- and up-sell potential. Think about what this means for your business.

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It is time to master things!

In my next blog I will go deeper on the success criteria for the MDM (Master Data Management) of Things. And this is much more than mastering products. It will be about massive scale and connectivity and all humans expect relevant data for decision making as employees or customers in real-time.

Debunking Three Myths of The Gartner MDM Magic Quadrant

The new 2017 Gartner Magic Quadrant for MDM solutions is out and available for download here.

An analyst once compared the Magic Quadrant with sports. At a conference he said: “Being an analyst in the MQ is like being a referee in kids soccer. Before the game everybody wants to be your friend. By half time almost everybody hates you.” What he described was the relationship between analysts and software vendors with a wink 😉 … and all people were laughing in the audience.

After ten years being involved in different magic quadrant processes, I thought it is time talk about a few things which have not been in the news. I love to debunk three myths about the MQs.

Myth 1: Money makes the MQ go round

Many people live under the impression that vendors which pay the biggest checks to Gartner will jump on the MQ. This is sooo wrong. Gartner strictly separates any financial flow from this market evaluation. The process and the integrity of great analysts like Bill O’Kane, Simon Walker, Michael Moran in this case (and Andrew White in the past), who put a lot serious work into this process to paint a realistic and neutral picture of the market with looking at of the period of 2016 and Q1-2017.

Myth 2: Large vendors dominate

Disruption is more than a hype in these days, it is reality. Gone are the times where the so called mega vendors (SAP, IBM, Oracle) where the only dominators. My old company Informatica grew, based on two great solutions (Siperian customer MDM and Heiler PIM) to a new leader. I am thankful for ten years being part of it. Now many new start-ups and concepts have started to challenge this status quo again and again. New technologies have offered new and fast ways to address challenges where the industry thought it takes years. This is wrong. New ways and new tech have changed the MDM market as never before. Time for new things.

Myth 3: A picture paints a thousand words

Be honest, the first thing you look for is the chart. Who is where? What has changed? Yes it helps to get a first glance, but it is wrong to only consider the MQ chart. As mentioned above, a lot work goes into it from analysts, all customer and all vendors – so they all deserve to take a deeper look on strengths and cautions and reading between the lines.

Finally

There was enough said on the new market perspective Gartner defined with the 2016 release. Nothing is more constant than change, so also the MDM vendors have to revisit their strategy and offering regarding news technologies such as AI and big data, but first of all customer expectations.

If you are about to use the MQ as starting point for the vendor selection, my recommendation is: Let future readiness and vision be your factor. You will pick a solution which you will impact your business over the next decade. You don’t want to pick a solution which has home work to do cleaning up old heritage.

PS: I am a true believer in close collaboration with the analysts and learned incredibly much from many smart people of the years in this market.

The new 2017 Gartner Magic Quadrant for MDM solutions is out and available for download here.

Conversational Commerce: Two Third of Requests are about Products & Service

I had the great pleasure working with Smoope, a messaging as a service vendor recently. The segment is super relevant in these days selling to millennials. In these days every smart company is trying to find their strategy for turning conversations into transactions.

What I learned from a research in an analyst conversation with Lefti Co-Founder of Smoope and Forrester Analyst Laura Naparstek was, that 36% of conversations in chats are centered around “products & services”.  That emphasizes the need for rich and fast product master data to power the conversational commerce channel with the right and relevant data so that the customer can take a purchasing decision.

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I my opinion the omnichannel term continues to expand adding new interaction channels, such as messaging. This brings the need to integrate data and connect master data to new apps like messaging platforms. Clearly this is tied to the AI and chatbot discussion and blog, I published this summer. Wether you are talking to a human being or the AI-driven bot, answers can only be as good as the data foundation to offer the right product at the right moment. This promise and challenge, has just become more complex.

There is an appetite talking to brands through messaging, but the brands need to be clear on expectation setting and their processes. Many brands seem not to do well and are not able to go beyond the welcome message. Many are not set for taking the conversation to the next level and advancing the conversation, which will turn customers away easily.

The future vision in this segment is clearly impacted by the Zeitgeist of Alexa and Siri where customers are getting used to the most simplest way of formulating their need. Like texting or saying “please transfer 20 Euro to Ben”, or “please send me the shirt which was delivered today in size M” without filling out a complex form.

The New Live Soccer Experience or The Bitter Truth of German Internet

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Germany is a highly developed economy which is not shy of any international benchmark. In times of the digital transformation discussion, politicians frequently address one of the foundations of making digital business and digital work place models a success: fast broadband internet. Yes, my friends in the US, we have a challenge here.

Germany’s soccer fans are unhappy this season with Sky who does not offer any more all Bundesliga games, while prices for their subscription have not changed. Clients have to sign up for the Amazon/ Eurosport channel to see the Friday games.

Last Friday I went to a local bar/ pub to watch the game of VfB Stuttgart with friends and many local supporters and had a real new live soccer experience:

The first five minutes the large plasma TV was all but not HD. Reality was it was unsharp lagging and stuttering. While discussing the first scenes and missed chances over a beer, I noticed vibrations in my pocket. It was my phone obviously alerting me that VfB Stuttgart leads 1:0. But the entire bar was still seeing the 0:0 score.

So I said to my friends “I bet player x has missed some chances, but he will score a goal today” with a bright smile on my face 😉  From this moment on a new pattern got established in the bar. People started to follow the game on live tickers and Twitter using their mobile phones to be right faster.

Everytime a critical alert came in people stopped their conversations, put their phones and came closer the the TV screen to see what will happen – or better “has” happened.

For all fans of live sport events, this is clearly a momentum, where watching sports in the internet is getting less attractive. In our case the bar owner was said because their guests have been unhappy about this. The bitter truth is, it is not their fault. They would go for a high speed internet deal, but is is just not available. I would go for it to, but it is not available.

How can the future of a connected home, working from home and all IoT connected devices work, if there is no fast internet? 

Conversational Commerce: Chat Bot vs Human Being

You may know from my blog, that I like to challenge brands and companies on their customer experience and understand how much they are using latest tech solution to enable a data-driven business in order to sell more or service better. As a fashionista I signed up for Zalon, a service by German fashion giant Zalando. They claim to jointly create my new outfit on their front page.

This is my summary of my experience after using for about two weeks: The first thing you do is selecting your preferences across all categories of clothes. For example if you are only looking for business or also for casual wear, of which kind of shirts you like (button down or kent, stripes or plain etc.)

You also are asked to add your size and you can submit pics of yourself, so that your personal shopping assistant will be able to better understand your style but also your body shape.

I decided to provide as much information as possible (also that I blog about fashion), hoping it will help to tailor the offerings to my need.

The pros of this service are:

  • They show customer orientation by offering it
  • It feels like responses are faster compared to email
  • you feel special having a personal shopping assistant

The cons after two weeks testing it:

  • I clearly told my sizes, but other sized have been offered (I am pretty tall)
  • The app says “Thomas” will be online again in 1 hour, but this gets postponed three times in a row
  • I asked questions and did not get answers on brand and price

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What role does AI and Customer 360 play?

Some questions I have are: Is the Zalon sharing my profile data with Zalando and Zalando Lounge to better understand my preferences and shopping history to predict my next action? How advanced are they on leveraging the potential of “Customer 360” including my social interactions.

Who is able to deliver more value with todays technology? A chatbot like Levi’s or a real person from Zalon? (You may also check what Suitsupply is doing using WhatsApp.) I checked the Levi’s bot and obviously it delivers all answers right away like my 505c I was not finding in stores, but I was limited showing the used style I wanted.

Clearly omnichannel customer engagement has found one important new trend and channel, called “conversational commerce”, where vendors like Smoope or Twilio are playing. An important questions will be how serious WhattsApp owner Facebook will be going after this B2B market opportunity. (Read more here.)