The focus group, that has been conducted with domain experts in the fields social security and institutional question on local and regional level has proven one more time, that strategic planning is fundamental important. For its success, the focus group advised to fund long-term digitisations strategies adequately, as this is essential for the implementation of new tasks.
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The Big Policy Canvas Knowledge Base is a state-of-the-art, online and dynamic repository that functions as an accumulator uniting all the knowledge produced during the project. It is structured along the three dimensions of needs, trends and assets and furthermore offers a mapping among them by defining how they are interconnected and how they influence each other.
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Evaluation represents a separate stage in the policy cycle, but has to be pointed out as an own need in public administration. Evaluation decides whether a policy will be finished, modified and/or continued. At the same time, it can inform about results and consequences (intended and not intended). Only if policies are evaluated, potential improvement will be identified and at best implemented. In this context, it should be emphasised that a policy is never completed and is always evolving. This makes a qualitative and regular evaluation essential.
Public management has to react to changes in national and global contexts. A current key driver for changes can be seen in the Europeanisation, which affects the level of member states, caused by EU integration processes. Successful administrative action in the multilevel European system requires adjustments, ensuring efficient dealing with European objectives.
It is most important to take into account the state-specific circumstances, as well as local and regional specificities. For example, the German public administration differs fundamentally from public administration in other countries. Solutions that were identified as right and expedient for one country are not automatically useful in another. The possibilities of implementation will vary due to diverse traditions and organisational cultures.
Public administration has many opportunities to protect the environment and reduce its negative impact on it. There is a lot of potential in minimising energy, paper and water consumption, as well as waste production in public institutions. Because of the administration's role model function, it is necessary to take responsibility, and in consequence, to develop and establish environmental awareness. Environmental protection is a priority topic in recent years, which also needs to be addressed by the public administration.
A relevant but also critical factor in public management is the staff. It is important to recruit junior staff and specialists, which can manage the given challenges and have the necessary skills and technical knowledge to promote the digital transformation. Particularly in view of the demographic developments, it seems essential to recruit new staff and retain them in the long term.
In addition to recruiting new employees, personnel development should not be neglected. Existing personnel should be trained to help them handle the challenge of new technologies and consequently changes in organisational environment. Personnel development measures have to be established to support employees’ acceptance and the acquisition of competences connected to ICT, preparing them for possible challenges.
Public sector has to deliver services to citizens despite resource constraints and budgetary pressures. Because of this personnel and financial limitations, available resources must be used as cost saving and valuable as possible.
In 2001, the industry analyst Douglas Laney at Gartner described data management challenges along the three dimensions volumes, velocity and variety in the E-commerce branch. Volumes stands for the quite huge increase of volumes of data, Velocity for increased point-of-interaction speed and the pace of data generated by interactions and used to support interactions. Data Variety means variety of incompatible data formats, non-aligned data structures and inconsistent data semantics. This 3-V-model has been widely used attempting to define big data since this publication in 2001. 
Predictive analytics brings together advanced analytics capabilities. It extracts information from existing data sets in order to determine patterns and predict future impacts and trends. It forecasts what might happen in the future with an acceptable level of reliability, and includes what-if scenarios and risk assessments.
Data analytics encompasses techniques such as regression analysis, pattern matching, forecasting, multivariate statistics, predictive modelling and forecasting.