{"id":3902,"date":"2019-04-29T10:33:51","date_gmt":"2019-04-29T10:33:51","guid":{"rendered":"https:\/\/previous.predictiveanalyticsworld.de\/?page_id=3902"},"modified":"2019-06-19T08:07:19","modified_gmt":"2019-06-19T08:07:19","slug":"data-thinking-for-marketing-sales-mit-martin-szugat","status":"publish","type":"page","link":"https:\/\/previous.predictiveanalyticsworld.de\/en\/workshops\/data-thinking-for-marketing-sales-mit-martin-szugat\/","title":{"rendered":"Data Thinking for Marketing &#038; Sales with Martin Szugat"},"content":{"rendered":"<p><a name=\"paw-workshop2\" id=\"paw-workshop2\"><\/a><\/p>\n<div class=\"alert alert-warning alert-dismissable fade in\">\nThe following workshop with Martin Szugat will be held in German. <img title=\"Workshop will be held in English\" src=\"https:\/\/conversionconference.de\/wp-content\/plugins\/risingmedia_api\/img\/flags\/4x3\/de.svg\" alt=\"Workshop will be held in German\" width=\"20\" border=\"0\" \/>\n<\/div>\n<h3><u>Workshop:<\/u> Data Thinking with Martin Szugat<\/h3>\n<div class=\"col-xs-12 col-sm-12 col-md-8 col-lg-9 nopadding\">\n<h4>Wednesday, 20 November, 2019<\/h4>\n<h5>9:00 am &#8211; 5:00 pm<\/h5>\n<h5>Estrel Hotel Berlin<\/h5>\n<p>Included are two coffee breaks, lunch and soft drinks during the conference<\/p>\n<p><strong>The workshop places are limited \u2013 secure your space now!<\/strong><\/p>\n<div>\n<a href=\"\/en\/anmelden\/#pricecat426\" class=\"btn btn-register\" style=\"text-align: center; text-decoration: none;\">Register Now for <strong>\u20ac895<\/strong><\/a>\n<\/div>\n<h4 style=\"margin-top: 25px;\">Intended Audiences:<\/h4>\n<ul>\n<li><strong>Data Scientists and Data Analysts<\/strong> who want to successfully establish and drive data science in their organization.<\/li>\n<li><strong>Professionals &#038; Managers<\/strong> who want to transform their company into a data-driven business.<\/li>\n<li><strong>Project &#038; Product Managers<\/strong> who are already developing data-driven solutions and want to <strong>accelerate and focus the development<\/strong>.<\/li>\n<\/ul>\n<h4 style=\"margin-top: 15px;\">Goals:<\/h4>\n<ol>\n<li>Learn what are the <strong>critical factors for a successful data strategy and a data-driven business<\/strong>.<\/li>\n<li>Get to know the <strong>data strategy design method<\/strong> to develop an <strong>individual data strategy for your company on your own<\/strong>.<\/li>\n<li>Explore the power of analytical solutions and discover how to <strong>design, evaluate and prioritize analytics projects efficiently and effectively<\/strong>.<\/li>\n<\/ol>\n<\/div>\n<div class=\"col-xs-12 col-sm-12 col-md-4 col-lg-3\">\n<h4 style=\"text-align: center;\">Leader:<\/h4>\n<div class=\"singleprofile\"><div class=\"speaker personcard\" id=\"personcard39021095\" itemscope itemtype=\"http:\/\/schema.org\/Person\"><div class=\"inner\"><div class=\"backgroundimage\" style=\"background-image:url(https:\/\/stuff.risingmedia.eu\/images\/speaker\/1095.jpg?d=1560859081); width: 100%;\"><div class=\"gardient\"><div class=\"glass\"><div class=\"infos\"><div class=\"personpicture\"><a href=\"https:\/\/previous.predictiveanalyticsworld.de\/en\/abendveranstaltung\/#39021095\"><img class=\" img-person img-responsive\" src=\"https:\/\/stuff.risingmedia.eu\/images\/speaker\/1095.jpg?d=1560859081\" width=\"100\" height=\"100\" alt=\"Martin Szugat\" title=\"Martin Szugat\" border=\"0\" itemprop=\"image\" \/><\/a><img class=\"countryflag img-responsive\" src=\"https:\/\/previous.predictiveanalyticsworld.de\/wp-content\/plugins\/risingmedia_api\/img\/flags\/4x3\/de.svg\" width=\"30\" height=\"\" border=\"0\" \/><\/div><!-- \/.personpicture --><a href=\"https:\/\/previous.predictiveanalyticsworld.de\/en\/abendveranstaltung\/#39021095\"><h5 class=\"nameline\" itemprop=\"name\">Martin Szugat<\/h5><\/a><p class=\"jobline\" itemprop=\"jobTitle\">Founder & Managing Director<\/p><div class=\"companylogo\"><img class=\"img-brand img-responsive\" src=\"https:\/\/stuff.risingmedia.eu\/images\/partner\/1021.png?d=1487779083\" width=\"120\" height=\"27\" alt=\"Datentreiber GmbH\" title=\"Datentreiber GmbH\" id=\"brand1021\" border=\"0\" itemprop=\"image\" \/><\/div><!-- \/.companylogo --><div class=\"socialprofiles\"><\/div><div style=\"clear: both;\"><\/div><\/div><!-- \/.infos --><\/div><!-- \/.glass --><\/div><!-- \/.gardient --><\/div><!-- \/.backgroundimage --><\/div><!-- \/.inner --><\/div><!-- \/.speaker personcard --><\/div><!-- \/.singleprofile -->\n<div style=\"clear: both;\"><\/div>\n<\/div>\n<div style=\"clear: both;\"><\/div>\n<h4 style=\"margin-top: 15px;\">Content:<\/h4>\n<p>Data-driven businesses score higher than their competitors with an average of <strong>6% increased productivity<\/strong> and efficiency (according to a study by the renowned Massachusetts Institute of Technology). To gain this competitive advantage, a <strong>sophisticated and individual data strategy<\/strong> is required. Neither is it enough to hire data scientists and data engineers to build their own data labs, nor is it sufficient to buy expensive technologies for machine learning, deep learning and artificial intelligence or to accumulate huge data lakes in the sense of big data. Without <strong>a clear objective and roadmap to achieve these goals<\/strong>, the data science team will be aimless, the technology will stand still, and the data will be left unused. All in all, <strong>companies lose money twice<\/strong>: they <strong>unnecessarily spend money on resources<\/strong> that they do not need, and the positive effects of potential analytics solutions, such as <strong>revenue growth or cost reduction<\/strong>, are either left over or only come with <strong>considerable delay<\/strong>.<\/p>\n<p>With design thinking, an established approach exists <strong>to identify the relevant challenges from the user or customer perspective and to design innovative solutions<\/strong>. Data thinking extends this approach to aspects of data science to <strong>design data-driven solutions<\/strong>. Using the data strategy design method, the strategy consultancy Datentreiber provides <strong>free visualization tools<\/strong> (&#8220;canvas&#8221;) and a <strong>proven process<\/strong> to quickly <strong>identify the critical use cases<\/strong> in interdisciplinary teams (consisting of data science, IT, and engineering) and <strong>feasible solutions<\/strong>. The result of data thinking is a roadmap to increase the analytical maturity level of your own company as well as concrete concepts for the realization of initial solutions. Based on this data strategy, you can directly derive which resources &#8211; people, technologies and data sources \u2013 are actually needed.<\/p>\n<p>The one-day workshop &#8220;Data Thinking&#8221; offers <strong>a quick introduction to the topics of design thinking and data strategy<\/strong> based on <strong>numerous real-world examples and practical exercises<\/strong>. At the end of the day, you&#8217;ll be able to independently develop and evaluate data strategies and apply the canvas tools Data Strategy, Data Landscape, and Analytics Maturity with your team. The data strategy design method will help you <strong>to speed up your data-driven business and minimize risks and uncertainties as early as possible<\/strong>.<\/p>\n<h4 style=\"margin-top: 15px;\">Agenda:<\/h4>\n<table width=\"100%\" style=\"border-collapse: collapse; border: 1px solid #c0c0c0;\">\n<tr>\n<td width=\"120\" style=\"padding: 10px; border: 1px solid #c0c0c0; text-align: center; background-color: #dfdfdf;\">9:00 am<\/td>\n<td style=\"padding: 10px; border: 1px solid #c0c0c0; font-weight: bold;\">Presentation of agenda and introduction of participants<\/td>\n<\/tr>\n<tr>\n<td width=\"120\" style=\"padding: 10px; border: 1px solid #c0c0c0; text-align: center; background-color: #dfdfdf;\">9:15 am<\/td>\n<td style=\"padding: 10px; border: 1px solid #c0c0c0; font-weight: bold;\">Lecture I: Overview of data-driven business models and processes as well as deep dive into the method of data strategy design and the design thinking approach<\/td>\n<\/tr>\n<tr>\n<td width=\"120\" style=\"padding: 10px; border: 1px solid #c0c0c0; text-align: center; background-color: #dfdfdf;\">10:30 am<\/td>\n<td style=\"padding: 10px; border: 1px solid #c0c0c0; background-color: #dfdfdf;\">Break<\/td>\n<\/tr>\n<tr>\n<td width=\"120\" style=\"padding: 10px; border: 1px solid #c0c0c0; text-align: center; background-color: #dfdfdf;\">11:00 am<\/td>\n<td style=\"padding: 10px; border: 1px solid #c0c0c0; font-weight: bold;\">Practice I: Identify analytical use cases with the Business Model Canvas and prioritize them with the Analytical Maturity Canvas<\/td>\n<\/tr>\n<tr>\n<td width=\"120\" style=\"padding: 10px; border: 1px solid #c0c0c0; text-align: center; background-color: #dfdfdf;\">12:30 pm<\/td>\n<td style=\"padding: 10px; border: 1px solid #c0c0c0; background-color: #dfdfdf;\">Lunch<\/td>\n<\/tr>\n<tr>\n<td width=\"120\" style=\"padding: 10px; border: 1px solid #c0c0c0; text-align: center; background-color: #dfdfdf;\">1:30 pm<\/td>\n<td style=\"padding: 10px; border: 1px solid #c0c0c0; font-weight: bold;\">Practice II: Concretize user &#038; customer needs with the Value Proposition Canvas as well as specify analytical solutions with the Data Strategy Canvas<\/td>\n<\/tr>\n<tr>\n<td width=\"120\" style=\"padding: 10px; border: 1px solid #c0c0c0; text-align: center; background-color: #dfdfdf;\">3:00 pm<\/td>\n<td style=\"padding: 10px; border: 1px solid #c0c0c0; background-color: #dfdfdf;\">Break<\/td>\n<\/tr>\n<tr>\n<td width=\"120\" style=\"padding: 10px; border: 1px solid #c0c0c0; text-align: center; background-color: #dfdfdf;\">3:30 pm<\/td>\n<td style=\"padding: 10px; border: 1px solid #c0c0c0; font-weight: bold;\">Practice III: Explore data sources and gaps with the Data Landscape Canvas and define a    roadmap for implementing the analytical solutions<\/td>\n<\/tr>\n<tr>\n<td width=\"120\" style=\"padding: 10px; border: 1px solid #c0c0c0; text-align: center; background-color: #dfdfdf;\">4:45 pm<\/td>\n<td style=\"padding: 10px; border: 1px solid #c0c0c0; font-weight: bold;\">Open feedback and Q&#038;A session<\/td>\n<\/tr>\n<tr>\n<td width=\"120\" style=\"padding: 10px; border: 1px solid #c0c0c0; text-align: center; background-color: #dfdfdf;\">5:00 pm<\/td>\n<td style=\"padding: 10px; border: 1px solid #c0c0c0; background-color: #dfdfdf;\">End<\/td>\n<\/tr>\n<\/table>\n<h4 style=\"margin-top: 15px;\">Trainer:<\/h4>\n<p>With his strategy consultancy <a href=\"https:\/\/www.datentreiber.de\/\" rel=\"noopener noreferrer\" target=\"_blank\">Datentreiber<\/a>, Martin Szugat supports companies in their digital transformation <strong>to data-driven business models and processes<\/strong> with strategy workshops, consulting and seminars. His clients include companies such as <strong>ProSiebenSat1, Nestl\u00e9, TecAlliance, S\u00fcddeutsche Zeitung and GfK<\/strong>. His approach to data strategy design is applied by a wide range of companies across industries and disciplines <strong>to design analytical solutions<\/strong> for their own business or their clients <strong>and to develop successful data strategies<\/strong>.<\/p>\n<p>Prior to Datentreiber, Martin Szugat was a partner and managing director of SnipClip, an agency for social media marketing &#038; analytics solutions. The bioinformatics graduate has researched machine learning and data mining and worked as a freelance specialist author and IT consultant. Since 2014, he has served as program director for the Predictive Analytics World conferences in Germany.<\/p>\n<p>Examples of presentation documents as well as video recordings of lectures can be found here (in German):<\/p>\n<ul>\n<li><a target=\"_blank\" href=\"https:\/\/slideslive.com\/38901196\" rel=\"noopener noreferrer\">https:\/\/slideslive.com\/38901196<\/a><\/li>\n<li><a target=\"_blank\" href=\"https:\/\/slideshare.com\/datentreiber\" rel=\"noopener noreferrer\">https:\/\/slideshare.com\/datentreiber<\/a><\/li>\n<li><a target=\"_blank\" href=\"https:\/\/youtu.be\/DNuV_7LaVi0\" rel=\"noopener noreferrer\">https:\/\/youtu.be\/DNuV_7LaVi0<\/a><\/li>\n<li><a target=\"_blank\" href=\"https:\/\/youtu.be\/TcRMQL5Ys04\" rel=\"noopener noreferrer\">https:\/\/youtu.be\/TcRMQL5Ys04<\/a><\/li>\n<li><a target=\"_blank\" href=\"https:\/\/youtu.be\/rzaqqmrVJEA\" rel=\"noopener noreferrer\">https:\/\/youtu.be\/rzaqqmrVJEA<\/a><\/li>\n<\/ul>\n<h4 style=\"margin-top: 15px;\">Testimonials<\/h4>\n<p>&#8220;The workshop day with Datentreiber was an absolute win for all employees of our agency. The many insights and perspectives on the topics of digital and social have allowed views to be rethought and sustainably increased awareness in dealing with data.&#8221;<\/p>\n<p> &#8211; <strong>Tobias Sp\u00f6rer<\/strong>, Managing Director of elbkind GmbH<\/p>\n<p style=\"margin-top: 25px;\">&#8220;In his workshops, Martin Szugat builds bridges in the diverse potentials of data usage. He was a great motivator to enhance our consulting services in the field of business design and customer experience strategy.\u201c<\/p>\n<p> &#8211; <strong>Ron Hofer<\/strong>, Managing Director &#038; Founder, USEEDS &deg; GmbH<\/p>\n<p style=\"margin-top: 25px;\">&#8220;As specialists in customer analysis, we help our clients to generate valuable insights from data. Martin Szugat explained his methods and models to our colleagues during a two-day workshop. The canvas method is an excellent amendment to integrate design thinking into our consulting approach.\u201c<\/p>\n<p> &#8211; <strong>Cecilia Floridi<\/strong>, Managing Director of DataLab. GmbH<\/p>\n<div style=\"clear: both;\"><\/div>\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>The following workshop with Martin Szugat will be held in German. Workshop: Data Thinking with Martin Szugat Wednesday, 20 November, 2019 9:00 am &#8211; 5:00 pm Estrel Hotel Berlin Included are two coffee breaks, lunch and soft drinks during the conference The workshop places are limited \u2013 secure your space <a class=\"\" href=\"https:\/\/previous.predictiveanalyticsworld.de\/en\/workshops\/data-thinking-for-marketing-sales-mit-martin-szugat\/\">&#8230;&nbsp;weiter lesen<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":3284,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/previous.predictiveanalyticsworld.de\/en\/wp-json\/wp\/v2\/pages\/3902"}],"collection":[{"href":"https:\/\/previous.predictiveanalyticsworld.de\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/previous.predictiveanalyticsworld.de\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/previous.predictiveanalyticsworld.de\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/previous.predictiveanalyticsworld.de\/en\/wp-json\/wp\/v2\/comments?post=3902"}],"version-history":[{"count":5,"href":"https:\/\/previous.predictiveanalyticsworld.de\/en\/wp-json\/wp\/v2\/pages\/3902\/revisions"}],"predecessor-version":[{"id":4004,"href":"https:\/\/previous.predictiveanalyticsworld.de\/en\/wp-json\/wp\/v2\/pages\/3902\/revisions\/4004"}],"up":[{"embeddable":true,"href":"https:\/\/previous.predictiveanalyticsworld.de\/en\/wp-json\/wp\/v2\/pages\/3284"}],"wp:attachment":[{"href":"https:\/\/previous.predictiveanalyticsworld.de\/en\/wp-json\/wp\/v2\/media?parent=3902"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}