How smart is your algorithm? Tea and Talent 8 October 2020 Name Email* In order to tailor the online Tea and Talent event to your interests, we would like to ask you a few questions beforehand.What is the name of the organisation that you work for?* What is your current position in this organisation?* How important is data analysis for your organisation?* Very Important Important Somewhat Important Not Important What kind of data analytic applications are most common/desired in your organization? (multiple answers possible)* Select All Marketing (e.g. sales forecasts, customer segmentation) Finance (e.g. revenue management, transaction analysis, risk management) Operations (e.g. stock and warehouse management) What do you consider to be the biggest data challenge for your organization?* Lack of analytical/statistical expertise Lack of programming/software expertise Data collection and/or processing Interpreting outcomes of data analyses Which kind of data does your organization (wish to) analyse? (multiple answers possible)* Select All Data for many “units” (e.g. customers) for which no clear relation is there (e.g. customers all decide independently on what they buy). Time series: data that is recorded over time (e.g. sales figures of a product in each week of the last two years) Spatial data: data across different regions/areas with interactions between areas (e.g. sales from stores in different locations) Text data: written text from which information needs to be extracted (e.g. customer reviews) Which software, if any, is currently used in your organisation for data analysis? (multiple answers possible)* None Eviews Excel Python R SAS SPSS Other What is the main goal of your current/desired data analysis?* Predictions (e.g. forecasting future sales, predicting preferences of a new customer) Classifying events (e.g. determining whether a prospect will become a buyer, establishing “profiles” of clients) Establishing cause and effect (e.g. which elements resulted in the success/failure of your marketing campaign, which characteristics make clients act the way they do) Scenario-analysis (e.g. what happens to sales if you increase prices, how effective is an advertising campaign) For your data, which type of analysis do you think is more useful?* Machine learning and artificial intelligence Statistics Both What is the difference?