{"id":215,"date":"2020-02-25T07:57:00","date_gmt":"2020-02-25T07:57:00","guid":{"rendered":"https:\/\/blogs.zeiss.com\/intern\/tech\/?p=215"},"modified":"2020-02-25T14:29:27","modified_gmt":"2020-02-25T14:29:27","slug":"failing-learning-innovating","status":"publish","type":"post","link":"https:\/\/blogs.zeiss.com\/tech\/failing-learning-innovating\/","title":{"rendered":"Failing, Learning, Innovating"},"content":{"rendered":"\n

From startups in\nSilicon Valley to big tech companies and corporate innovation hubs: It seems\nthat \u201cfailing\u201d is widely accepted these days. Entrepreneurs celebrate \u201cFuckup\nnights\u201d and startup employees are excited about how they \u201cembrace failure\u201d. Sounds\nlike a relaxed way of working, right? No responsibility, no accountability, no consequences.\nThe opposite is the case. But let\u2019s start from the beginning.<\/p>\n\n\n\n

Today\u2019s business\nenvironments are characterized by a high level of uncertainty. Accelerating technological\nprogress, blurring industry boundaries, volatile markets and increasing\nregulation, to name only a few aspects. In this context, innovating means leaving\nthe familiar ground behind and entering unknown terrain. The more ambitious you\nare, the more radical your ideas are, the further you have to leave your\ncomfort zone. Past experience does not provide you with good guidance anymore and\ntraditional tools might no longer be appropriate. The consequences of your\nactions are highly uncertain. <\/p>\n\n\n\n

In this setup,\nfailure \u2013 in the sense that \u201cthings do not work out as intended\u201d \u2013 is unavoidable.\nWhat sets successful innovators apart from the average is how<\/em> they fail. Companies like Google or Amazon have strict mechanisms\nand metrics in place that ensure that they fail fast, cheap and \u2013 most important\n\u2013 that they extract as much relevant insights as possible out of failure. Some of\nthese companies advertise their \u201cfailure culture\u201d. However, even more, all of\nthem foster a strong \u201clearning culture\u201d. Navigating in uncertain terrain, they\nfocus on quickly learning everything they need to finally succeed. In fact, these\ncompanies compete on the rate of structured experimentation, learning, and\nacting on learnings. In doing so, they acknowledge that some ideas will not\nwork out, will fail. <\/p>\n\n\n\n

Harvard Professor Gary Pisano characterizes such learning cultures with two main elements (see Link<\/a>): First, a \u201ctolerance for failure, but no tolerance for incompetence,\u201d and second, a \u201cwillingness to experiment, but highly disciplined.\u201d A Google manager will accept failure if, despite reasonable assumptions and promising first customer feedback, the development of a new product is stopped once the success indicators turn red. At the same time, he will not accept failure due to sloppy market analysis, missing customer involvement or ignorance of technical problems. Also, he will drive experimentation with new product ideas, however, always in controlled and structured ways, directed to maximize relevant learning. <\/p>\n\n\n\n

At ZEISS Digital\nInnovation Partners, we also aim for a strong learning culture. And as a part\nof that, we accept that sometimes, things do not work out as initially planned.\n<\/p>\n\n\n\n

Every project is\nconducted with our partners form the ZEISS Business and starts with a product-\nor service idea. The first step is usually to identify underlying assumptions for\nsuccess, in the three dimensions feasibility (tech), desirability (customer\nneed) and viability (business). A critical assumption for a personalized\nproduct recommendation service would be the availability of necessary input\ndata for the recommendation engine (feasibility). Furthermore, customers would need\nto be interested in receiving respective recommendations in the first place\n(desirability). Finally, we would assume that the service benefits our business\n(viability). The next step is to validate the assumptions, for example by\nassessing the availability and quality of data, conducting interviews with\npotential customers and calculating a business case. Working in sprints, we timebox\nthis validation phase to focus on the essential questions. If we can confirm\nall assumption, we move on. If not, we might agree to stop our activities, or \u2013\nmuch more often the case \u2013 adjust the scope of the product \/ service according\nto what we have learnt. Similarly, we continue to iteratively build the\nproduct. Start with basic and most essential functionalities, test them with\npotential customers, incorporate our learnings. Formulating reasonable and\ntestable success indicators help to verify progress. After every iteration, an\nopen discussion is necessary regarding next steps \u2013 and at every point there\nneeds to be the possibility to stop the project or to significantly pivot if\nsuccess indicators are not met anymore. <\/p>\n\n\n\n

It is painful to realize that an innovation project that started promising turns out to not meet the expectations anymore. Agreeing to eventually stop it early on might feel like failure. However \u2013 and this is the whole point around a failure culture \u2013 it is okay, it is actually the only right thing to do. After acknowledging that the initial plan did not work out, there is the possibility to formulate a new product idea based on all the insights from the past weeks. The good thing: Now you start with a much better understanding of what you are doing and where you want to go. What has been unknown terrain three months ago is now familiar ground. For me, innovation is fun \u2013 but it is definitely not relaxed. It is hard work that requires high levels of commitment, discipline and critical thinking from everyone involved. In the end, I personally do not care if people celebrate failure or learning \u2013 as long as those are two sides of the same medal. What I do care about, however, is that people accept failures as a fact in innovation activities. As long as you learn from them, they are not bad at all. <\/p>\n\n\n\n

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\u00a9 Sergey Nivens – stock.adobe.com<\/div>\n \n\n \"Business\n <\/div>\n \n\n\n\n\n \n <\/figure>\n","protected":false},"excerpt":{"rendered":"

From startups in Silicon Valley to big tech companies and corporate innovation hubs: It seems that \u201cfailing\u201d is widely accepted these days. Entrepreneurs celebrate \u201cFuckup nights\u201d and startup employees are excited about how they \u201cembrace failure\u201d. Sounds like a relaxed way of working, right? No responsibility, no accountability, no consequences. The opposite is the case. But let\u2019s start from the beginning.<\/p>\n","protected":false},"author":9,"featured_media":217,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"advgb_blocks_editor_width":"","advgb_blocks_columns_visual_guide":"","footnotes":""},"categories":[6,22],"tags":[],"topics":[18],"class_list":["post-215","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business","category-innovation","topics-digital-business"],"acf":[],"yoast_head":"\nFailing, Learning, Innovating - Digital Innovation Partners<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/blogs.zeiss.com\/tech\/failing-learning-innovating\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Failing, Learning, Innovating - Digital Innovation Partners\" \/>\n<meta property=\"og:description\" content=\"From startups in Silicon Valley to big tech companies and corporate innovation hubs: It seems that \u201cfailing\u201d is widely accepted these days. Entrepreneurs celebrate \u201cFuckup nights\u201d and startup employees are excited about how they \u201cembrace failure\u201d. Sounds like a relaxed way of working, right? No responsibility, no accountability, no consequences. The opposite is the case. 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