Dansk Forening for Data Management. Knowit. Dansk forening for Data Management Robotics Automating routine assignments/tasks

Transcription

1 Dansk Forening for Data Management Dansk forening for Data Management Robotics Automating routine assignments/tasks Knowit

2 1. Introduction to Knowit 2. Robotics paradigm 3. Live demo 4. Discussion 5. Wrap up

3 Johnny René Jensen Principal Consultant Lars Krogshede Principal Consultant

4 Knowit is a consultancy firm that creates unique customer value by offering digital and cross-functional solutions. Luleå Örnsköldsvik Umeå Knowit has around 2,000 consultants and operate global but is based in the Nordics. Serves customers across line of business, across industries as well as small and large organizations Robotics (and SAS) Center of Excellence in Copenhagen, Malmo, Stockholm, Oslo og Helsinki Bergen Stavanger Arendal Kristiansand Oslo Borlänge Sandviken Örebro Gothenburg Jönköping Sundsvall Gävle Linköping Uppsala Stockholm (HQ) Helsinki Tallinn Copenhagen Malmö

5 Analytics: Degree of sophistication Buzzwords and BS Bingo Decisio n support systems Nonlinear programming Linear programming 9/3/2018 Knowit Deep learning Image analytics Artificial intelligence Neural networks Operations research Data Visulization Yield Management Anticipatory analytics Machine learning Forecasting Expert systems Heuristic problem solving Predictive modeling Risk modeling Monte Carlo Simulations Ad hoc reporting Real-time analytics Video analysis Speech recognition Discrete event simulation Data mining Statistical analysis Text mining Alerting Management Information systems Advanced analytics Business intelligence Web search Data cubes/ drill down Volume/complexity of data Social media monitoring User activity tracking Telematics Web Crawling Block chain Credit scoring Operation intelligence Knowledge discovery Web analytics Crowd scourcing Data Clusters Natural language processing Sentiment analysis Cloud storage Standard Data Data Data Lakes reporting marts Warehouses ??? Robotic Process Automation Industry 4.0 Big Data Now and future??? Internet of things??? The names changes but the name of the game remains the same: Improve the bussiness! 5

6

7 What is RPA? Application of technology that allows to configure computer software or a robot to capture and interpret existing applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems A non-physical robot Software tool Tools that can replace human work at the keyboardinterface level and perform repetitive tasks reliably Can do if, then logic 9/3/2018 Knowit 7

8 Vendors / software

9 Few repetitions Many repetitions Robotics (robots) are good at Rule based automation (total or partly) Bulk handling / repetitions (large scale) Quick fix System bridge Surveillance (e.g. Web or Mail) Error handling Test typically Automated with macro s Small volume Robotic Proces Automation Difficult to define automation rules Simple Complex 9

10 What is RPA not? Not (just) a new software investment Not Artificial Intelligence Not NLP (natural language processing) Not an analytics tool Not a means to make people unemployed Not software embedded in a physical robot Not a chatbot or a virtual personal assistant However: You can INTEGRATE all of these to RPA 9/3/2018 Knowit 10

11 Tasks in Clinical Development / Data Management Routine data extracts from ecrf-systems, transferred to e.g. SAS to generate reports Monitor serious adverse events entered into ecrf-systems to detect new updates as they occur. As an alternative to API, where API is not available, is too expensive or is formatting data differently than UI Other areas where ecrf-system does not provide required oversight possibilities

12 Live demo Automate retrieval of data from ecrf system

13 3 minutes 2 and 2 Which task/process comes to your mind, suitable for automation? 9/3/

14 1 Start with boring processes that most people hate!

15 5 10% Avoid to automate processes carried out rarely 10% 50% 40% 60% 20% 20% 82% 8%

16 Important! Focus on working smarter not harder!

17 Ask yourself Are there processes that are vulnerable to human error? Are there processes that have regular peak periods? Are there process areas where process throughput time is crucial? Are there processes that need more traceability? Are there areas where speed is key to end user?

18 Johnny René Jensen Principal Consultant Lars Krogshede Principal Consultant

19