Decision-making support for the
THE PROJECT TEAM
TheaterLytics is a joint project of Paderborn University, Theater Paderborn (Theater Paderborn – Westfälische Kammerspiele GmbH) and OPTANO GmbH.
Paderborn University was represented by scientists from the Business Information System faculty, in particular by those specializing in digital markets and service management who conduct inter-disciplinary research at the SICP – Software Innovation Campus.
Theater Paderborn is a professional theater which provided the conceptual basis for the project. With 15 new theater productions in its main program, which are performed on three stages, the theater delights a total audience of approx. 65,000 with its varied program per season.
OPTANO GmbH applies its expertise in developing and implementing IT solutions to translate current research results into accessible user software.
Goals with regard to occupancy, visitors and sales can be achieved far better
Less time spent on planning at all
Improvement in resource utilization and less overload
The targets of cultural institutions can also be modelled and mathematically optimized.
In publicly funded cultural establishments such as Theater Paderborn- decisions need to be considered from several perspectives. On the one hand, the commercial objectives have to be observed and fulfilled. Decisions to this effect are, for instance, pricing or when to schedule premieres. On the other hand, creative decisions have to be made which may be in conflict with these targets. For example, which play to put on and which roles need to be filled. In addition, the theater has to fulfill a political-cultural task and cannot disregard current socio-political considerations.
Up until now all of these decisions at Theater Paderborn and in many other cultural establishents, have been gut decisions based on experience and specialist knowledge; i.e. the broad knowledge base has not been systematically processed. An important aspect of the project was to change this situation. Specialist knowledge should be formalized and be available in a decision-support system.
Furthermore, the results were to be processed and placed at the disposal of other cultural facilities.
The results of the project are a decision-support system on the one hand and a methodical modular system which makes acquired knowledge available to other cultural establishments.
The decision-support system performs systematic data processing and helps in choosing which play to put on, how to schedule premieres, how to schedule box office sales and controlling.
With the decision- support system all of the plays that have been read (and reviewed) in consideration for the next theatrical season are systematically recorded and retrieved. The longer this data pool grows, the more significance it will have for the dramaturgs’ work. Alongside their own asessments, the data from other theaters can also be retrieved in order to facilitate the search for possible plays.
The manual planning of premiere dates is a highly time-consuming as well as error-prone task. The dates depend on many conditions: The availability of the required actors and actresses (including those employed at the theater and freelancers), rehearsal phases which should not be too time-consuming, partiuclarly when the actors and actresses are performing in more than one play, and the availability of the appropriate stage. Being able to formalize these requirements so that mathematical optimization can be performed on them, was an important step in the project as many of these requirements may be clear to the human brain, however they must be exactly formulated for the algorithm.
Theater Paderborn sells tickets by means of a subscription system. Subscribers are offered tickets for certain plays and a small number of tickets can be purchased at the box office. In addition, plays are also put on for which tickets can be purchased directly from the box office. In this case the number and exact dates have to be determined.
The decision-support system disposes of a clear overview of the quantitative and qualitative assessments of the historical data of the plays that have already been put on. With the added option of being able to compare two similar plays the decision-making process on scheduling ticket sales for the general public is fed with data and therefore it functions far more easily.
Suitable KPIs were selected for evaluation in controlling and brought together in a structured overview. Here, the KPIs can be assessed and the right measures can be initiated. The success of this can be reviewed once again in the decision-support system.
During the project, an IT-tool was developed with the aim to support commercial and creative theater decisions. This tool was productively deployed for the first time in the current theatrical season. Thanks to the data-based analyses, valuable inisghts into visitor behavior and how the theater’s program can be designed could be gained. Being able to make accurate conclusions and make the relevant decisions based on these insights is now a learning process which is currently underway.
Other cultural institutions are also expected to benefit from these results in the future. Project results have been systematically summarized into guidelines on which courses of action can be taken and, for anybody who may be interested, this has been published on the Project website.
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Head of Solutions
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