The Eight Critical Elements for Successful Outsourcing – by Szymon Stadnik, Director of Business Service Center of Swiss FRISTA
Global Business Services in the digital age – Tom Bangemann, SVP Business Transformation at The Hackett Group
Digitization and Outsourcing in Insurance – Dr. Claudia Lang CEO & Co-Founder of Community Life GmbH, Germany
Successful Vendor Risk Management – Dr. Edward Renger, Head of Outsourcing Management OP-KOM, AXA Konzern AG
Many organizations, especially with matured business models, have to deal with legacy. Long time to production, nobody willing to support your system, chaos after leaving of engineers with critical system knowledge, hard to keep roadmap on time – sounds familiar?
Jan, CEO of J-Labs, a technology support company based in Poland and Munich as well as Michal, a Senior Software Engineer at J-Labs will shortly address legacy-related issues, covering business, technical and people related aspects. They will then give an overview of how to find ways out of this trap and will focus also on efficient and safe micro-services – both from technical and from business perspective. Both will also include a related client case from CircleK.
J-Labs is one of the outstanding mid-market technology support companies, based in Poland with activities and well known clients in Germany, that have demonstrated a high level of commitment and smart, individual software development services and solutions in our markets. I am very happy to have J-Labs sharing some of their experiences in a very critical area – legacy systems, said Stephan Fricke, from Outsourcing Verband.
Date and time: April 12th, 15:30 h
Jan Orzechowski, j-labs GmbH – Engineer, CEO and co-founder of j-labs, 250 people software development company, Forbes Diamond 2017 awarded. Working in IT industry for 20 years as Business Analyst, Project Manager, CTO and from 10 years as CEO. Computer sciences and economic studies alumni, combines technical background with business perspective. In j-labs responsible for general management, business development on DACH market, finance and administration areas. Startup’s Mentor in MIT Enterprise Forum accelerator. On weekends beekeeper and motobiker.
Michał Zaborowski, j-labs Gmbh – Senior Software Engineer with 20 years of experience, in different industries, but all the time close to development. Currently transforms legacy applications to cloud solutions, on AWS.
Technology can make a real difference for human beings but it is also constantly changing business. We would like to be part of this change because going forward it will proceed exponentially.
People tend to use machine learning and artificial intelligence as if they were synonyms – which is not correct. Machine learning (ML) is one very successful approach to the broader field of artificial intelligence (AI). I would like to elaborate more on machine learning and provide a few examples how this abstractive term can be translated into working technology such as computer vision, medical imaging and IoT.
ML can successfully support the video surveillance systems, from CCTV cameras footage, by automatic identification of suspicious or prohibited behaviours. Machine learning algorithms are used for basic purposes like classification of public space objects but also state of the art analysis like automatic anomalies detection – where system learns object behaviours directly from video streams and later, in operational mode, detects unexpected objects and behaviours. Detection raises alert, which is then processed by operators and public services. It helps to detect abnormalities quicker and make better decision to prevent them.
Presentation On April 13th at 11:30 by Adam Mirowski, Future Processing
About Adam Mirowski: Adam Mirowski, MSc, graduate of the School of Economics in Katowice (semester abroad at Nordhausen University of Applied Sciences in Thuringia). International working experience by companies like Norsk Hydro, Xerox, Johnson Matthey or j2Global. Since 2016 at Future Processing responsible for business development in the DACH Region.
Furthermore, ML can also increase the efficiency of medical imaging for patients suffering from cardiovascular diseases. This non-invasive method aims to help physicians better analyse 3D angiograms by revealing the 4th dimension: detailed information about flow conditions in the patient’s cardiovascular system. Advanced algorithms from computational physics, machine learning and image analysis will support clinicians in diagnosis and decision making.
Positive impact on people’s lives is not only limited to cardiology. Personalised oncology can also benefit from new and improved biomarkers extraction. The aim is to advance the diagnostic efficiency of dynamic contrast-enhanced imaging. The novel algorithms will enable physicians to extract and analyse new biomarkers. Advanced statistical tools will be useful to investigate biological correlates of the extracted image biomarkers. The purpose is to implement an innovative system and bring it into a day-to-day clinical practice to significantly improve cancer care.
Going forward, algorithms guarantee non-destructive and anonymous data gathering that helps to create targeted experience. Face recognition algorithms can easily provide statistical information about consumer base in commercial areas and public space. The retail industry is currently undergoing transformation process, resulting in greater attention to customer needs. Accurate customer profiling and understanding of their needs can give a significant competitive edge. Software using video footage to provide such profiling information as age and gender classification, counting people, and tracking people’s movement by assigning unique IDs and tracking reappearance on different cameras, will bring great value to the business.
ML can also work with data gathered from various sensors to calculate potential savings for instance predict future fuel consumption.
Many other examples are to be shared with participants of the conference. Some of them are:
- Automatic classification of roads and buildings on satellite images;
- Enhancing satellite image resolution to monitor climate changes,
- Air pollution analysis (especially detection of benzo(a)pyrene) from satellite images;
- Animal behaviour analysis based on ultrasound radars and skeleton reconstruction.
About Future Processing: Future Processing is an experienced IT services company specialising in solving business problems of industry leaders worldwide through the use of the latest technologies. We pride ourselves in the high level of technical expertise and an individualised approach to each project which result in the highest quality of our solutions. Since 2000, our team has grown to 900 people and includes some of the best software engineers in Poland. We are a Microsoft partner and an ISO 27001:2013-certified software developer who has won many awards, including the Global Sourcing Association’s Outsourcing Service Provider of the Year (2016).
Beyond providing software-related services, we work on a number of innovative projects involving machine learning in various fields – from medicine, to space projects, including commerce, industry and smart city solutions. We focus on solving real-life problems using both „conventional” machine learning approaches and deep learning, and on improving existent machine learning techniques. We also have our own products which include SmartFlow – a system used for monitoring waterworks infrastructure parameters, INTRA – a modern intranet platform and Adaptive Vision – machine vision software.
Contact: Future Processing Adam Mirowski, email@example.com , Tel. +48 605 446 665