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Improving SAP Analytics Cloud user acceptance

In a previous post, How to effectively measure user adoption in SAP Analytics Cloud, we showed how you can measure user adoption. But what can you do if acceptance is low? In this article, we present solutions based on our years of experience.

User acceptance

Requirements facilitation

It all starts with gathering the requirements. If user acceptance is low, it may indicate that the current solution was developed without considering the user requirements.

To achieve a high level of user acceptance, it is crucial to develop a solution that fulfils the actual needs of the users. In a traditional waterfall approach, the requirements are only recorded at the beginning of the project. This leads to a rather superficial understanding of the requirements, as users often only describe the symptoms and ignore the actual problems. In addition, the information needs of users can change during development, whether due to suggestions for improvement from users, process adjustments or reorganisations within the company. You should therefore invest time in analysing the requirements and incorporate regular feedback loops.

In order to create solutions that are tailored to the specific needs of the respective target group, you need to ensure the right composition of the team. Experience has shown that a mix of technical and business experts leads to the best results. Only professionals are able to anticipate requirements, implement best practices and avoid common pitfalls.

In addition, short release cycles enable quick feedback to ensure that the right solution is developed. Agile project management approaches include feedback processes in which users can regularly share their experiences and suggestions for improvement. In this way, the solution can be continuously improved.

Above all, it is important to involve future users as early as possible in the development of the reports to ensure that they provide the desired information and fulfil the specific needs of the individual departments. Make sure that the reports created not only visualise data, but also provide clear and actionable insights. You need to link the reports to specific business objectives and show how the insights they provide can help you make better decisions. Involving users at an early stage also has another advantage: participation. The fact that future users accompany and actively shape the development process increases acceptance and trust in the new application.

User experience

A user-focused interface is essential to increase engagement. An intuitive user interface with clear navigation makes it much easier to use. Frequently used functions or reports should be prominently displayed to make them easier for users to access and more efficient to use. Orientation towards existing, frequently used tools helps to reduce the learning curve and improve usability.

For example, you should design your dashboards in such a way that they are easy to navigate. Use clear headings, meaningful labelling and a logical arrangement of elements. A picture is worth a thousand words. You should therefore use appealing and easy-to-understand data visualisations to convey complex information more easily. Use an appealing visual design with graphics and diagrams that emphasise the most important findings. Also make sure you use a consistent colour scheme to help users find their way around the reports more quickly. Comprehensible and appealing visualisation starts with a design guide. This sets out the basic rules for designing reports and dashboards. A well thought-out design guide makes development easier. It also ensures that reports and dashboards have a high recognition value over time and across different software solutions and are accessible to users.

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Customisation

To increase the relevance of the reports for daily work, you should enable users to personalise them according to their individual requirements. There are several approaches here. It starts early in the design phase. The architecture of the solution must be flexible enough to anticipate future adjustments and be able to implement them quickly. Use variables and free characteristics wherever possible.

With the help of so-called free characteristics, the user can change the layout of the reports using a predefined number of characteristics. Free characteristics therefore offer the possibility to design reports dynamically. This means that changing business requirements can be covered without having to rebuild the entire report. Thanks to free characteristics, users can customise the reports to their personal needs and preferences, which increases the usability and relevance of these reports.

Variables make it possible to adapt reports dynamically. The displayed data is updated automatically without having to edit the entire report manually. The changes in the variable affect the entire report and the data basis remains consistent. Which brings us to the next point.

Confidence in the data

In order for users to utilize the reports, they must trust the data presented. So make sure that the reports always contain reliable and up-to-date data. Only then can users rely on the data basis to make informed decisions. Trust in the accuracy and timeliness of the data is therefore crucial for utilisation.

If, on the other hand, the data turns out to be untrustworthy, users have to manually verify the information presented, which increases the effort required on their side. Incorrect data undermines trust and leads to users no longer using the reports and looking for alternative sources of information.


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Technical finesse

The effort required on the user side represents an initial hurdle to using the solution that needs to be overcome. Therefore, interaction with the user should be made as smooth as possible. It is therefore important to rely on automation and minimise manual steps for the user.

A solidly built business intelligence (BI) solution works smoothly and delivers reliable results in real time. In addition, a technically sophisticated architecture enables users to work without delays, even with growing data volumes. High-performance solutions increase user satisfaction. Slow or unreliable tools, on the other hand, lead to frustration and reduced user acceptance.

In addition, a well thought-out and technically mature solution minimises the likelihood of bugs or data errors. Users expect BI tools to be highly reliable. Technical defects, on the other hand, which lead to incorrect reports or data loss, drastically reduce user acceptance.

Mobile optimisation

Our working world is becoming increasingly full of different devices. Users have long been consuming their information not only on the big screen, but also on smartphones, tablets and laptops while on the move. The developed solution should be accessible on as many devices and platforms as possible in order to increase user acceptance. Therefore, make sure that the reports are easily accessible on mobile devices. Thanks to mobile optimisation, SAP Analytics Cloud can also be used on the go, which increases acceptance. Don't worry, not every dashboard needs to be fully usable on a smartphone, but the most important insights should be visible and easy to understand, regardless of screen size.

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Training and courses

Unfortunately, there is often no budget left for training at the end of the project. However, training for end users is essential to promote their understanding of the functions and possibilities of SAP Analytics Cloud. Targeted training reduces users' uncertainties and increases their willingness to use the system. You should therefore plan for comprehensive training that covers both basic analysis techniques and advanced functions.

Communication and Change Management

To increase user acceptance, you must regularly inform users about the advantages and benefits of the solution. Accompany users as they switch to the new solution and help them integrate it into their daily work processes. Examples of how other users have benefited from the solutions can increase motivation. You should also encourage dialogue between users, this can be done via power users or an internal forum.

SAC user acceptance - Our Summary

A holistic approach is required to sustainably increase user acceptance. This begins with the collecting of requirements and ranges from the development of an intuitive user interface to the provision of training. A successful business intelligence solution must not only be technically mature, the human component also plays a central role. A high level of acceptance can be achieved through close co-operation with users, regular feedback and continuous improvement. With a little effort and patience, you can also rebuild trust that has already been lost and convince users of new technical solutions in the long term.

This in turn requires strong implementation partners with the necessary expertise. If you have any questions on this or other topics, please do not hesitate to contact us.

Learn all about SAC

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Rafael

Rafael Sachs has been working as an SAP BW and BO consultant in various industries in Germany and abroad since 2013. He covers the range from requirements management to implementation. His core competencies are tailor-made solutions in the front-end area and the professional design of the company's own software NextTables. In his spare time he is a restless hiker, dog tamer and hobby cook.

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Improving SAP Analytics Cloud user acceptance
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Blog - NextLytics AG 

Welcome to our blog. In this section we regularly report on news and background information on topics such as SAP Business Intelligence (BI), SAP Dashboarding with Lumira Designer or SAP Analytics Cloud, Machine Learning with SAP BW, Data Science and Planning with SAP Business Planning and Consolidation (BPC), SAP Integrated Planning (IP) and SAC Planning and much more.

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