{"id":37,"date":"2021-04-05T18:03:30","date_gmt":"2021-04-05T18:03:30","guid":{"rendered":"http:\/\/lucanus.dk\/?page_id=37"},"modified":"2021-04-05T18:03:30","modified_gmt":"2021-04-05T18:03:30","slug":"insights-big-data-analysis","status":"publish","type":"page","link":"https:\/\/lucanus.dk\/?page_id=37","title":{"rendered":"Insights & Big Data Analysis"},"content":{"rendered":"\n

We turn big data<\/strong> and advanced analytics<\/strong> into business. Everybody is talking about big data but many big data analysis lack a clear business purpose. Often we see that the insight and information gather with big data is difficult to transform into viable business plans and efficient operation. <\/p>\n\n\n\n

At Lucanus we analyse data with the purpose of transforming your operations and workflows and support your business plans and investments. Our insight is always based on a deep understanding of the cost drivers and business process of the operation in scope and we are therefore able to keep focus on the parameters that actually can be altered and data that has an impact on the analysis.<\/p>\n\n\n\n

When working with big data and advanced analytics you often find that the final goal is easy to define, but the data path leading towards the goal can be crooked and difficult. At Lucanus we have success with identifying alternative data that can describe the problem in scope, instead of spending lots of time and money on deploying new sensors, datapoints, field studies or have employees to report new records.<\/p>\n\n\n\n

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CASE: 12% reduction in nurse time spend on walking at acute bed ward and ICU (Intensive Care Unit)<\/h2>\n\n\n\n

On of the biggest cost drivers at a hospital is actually distance even though many hospitalorganizations aren’t fully aware of that. So by reducing distance for the employees you make substantial saving and improve patient experience.<\/p>\n\n\n\n

By using the existing wi-fi together with RTLS (Real Time Location System) we together with Hitachi Social Innovation analysed how the employees walked 24\/7 at the acute bed ward and the ICU at a Danish university hospital. And just by changing how a few critical rooms is located to each other at almost all hospital wards in the world, we reduced the distance the nurses walk during a shift with 12% – without changing their rutines or how and when they work.<\/p>\n\n\n\n

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30 strongest connections between the rooms at the acute bed ward.<\/strong>\u00a0Picture: Hitachi Social Innovation.<\/p>\n\n\n\n

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Simulation of optimal room layout at the acute bed ward.<\/strong> Picture: Hitachi Social Innovation.<\/p>\n\n\n\n

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CASE: Location Based Task Management<\/h2>\n\n\n\n

Many facilities management and service organizations lack a clear and updated picture of all the tasks the handle every day. And it is an almost unmanageable project of digitize everything they do – and subsequently keep the information up to date with the employees reporting how many hours they have worked on specific tasks every day.<\/p>\n\n\n\n

By\u00a0harvesting location data from GPS fleet management software installed in\u00a0the vehicles or the employees mobile phones we are\u00a0able to determine at a high degree which task they have been doing and how\u00a0long\u00a0time it took via GPS pattern recognition. And then\u00a0automatically\u00a0load the tasks into the task management system.<\/p>\n\n\n\n

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Location data for\u00a0empty trash cans in the park.<\/strong>\u00a0Picture: Lucanus.<\/p>\n\n\n\n

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Location data for snow clearing in the park.<\/strong>\u00a0Picture: Lucanus.<\/p>\n\n\n\n

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Normal distribution of task time.<\/strong>\u00a0Picture: Lucanus.<\/p>\n\n\n\n

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Further analysis shows potential for optimization by doing the task in the morning if possible. <\/strong>Picture: Lucanus.<\/p>\n\n\n\n

Location Based Task Management can also be used as a basis for invoicing the costumer, procurement of services or maintenance planning, as it is quite easy to determine how many kilometeres of road that have been cleared for snow, hectares of lawns moved, pumpstations worked on ect.<\/p>\n","protected":false},"excerpt":{"rendered":"

We turn big data and advanced analytics into business. Everybody is talking about big data but many big data analysis lack a clear business purpose. Often we see that the insight and information gather with big data is difficult to transform into viable business plans and efficient operation.  At Lucanus we analyse data with the purpose of transforming your […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-37","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/lucanus.dk\/index.php?rest_route=\/wp\/v2\/pages\/37","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lucanus.dk\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/lucanus.dk\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/lucanus.dk\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/lucanus.dk\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=37"}],"version-history":[{"count":1,"href":"https:\/\/lucanus.dk\/index.php?rest_route=\/wp\/v2\/pages\/37\/revisions"}],"predecessor-version":[{"id":44,"href":"https:\/\/lucanus.dk\/index.php?rest_route=\/wp\/v2\/pages\/37\/revisions\/44"}],"wp:attachment":[{"href":"https:\/\/lucanus.dk\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=37"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}