Analytics Use Case A0 (47" x 33") synthetic paper (EN)
Why Analytics Use Case?
Many analytics projects fail due to a lack of user acceptance because they do not meet the needs of the users and consequently the benefits of the solution are not clear. The analytics use case canvas helps you to identify the relevant use cases for analytics solutions, to concretise them in terms of the functional scope and to evaluate them in terms of their benefits. With the help of the canvas, you can analyse the relevant needs and goals of potential users and design solutions that have a high degree of solution-problem fit. The analytics use case canvas is based on the well-known value proposition canvas and adapts it for analytical questions.
Analytics is about analysing data and "analysing" means "separating things". Data analytics is about using software tools to separate relevant information from the data. Information in turn serves to answer specific questions or to test hypotheses. In an economic context, these questions and assumptions play a critical role in decision-making: is this the right action. Does this action lead to the desired result? Does this result contribute to the achievement of the target?
An analytics solution is therefore useful if it provides information that helps users to achieve their targets:
data → analytic → information → decision → action → result → target
Analytische Lösungen können sowohl bei der einfachen datengetriebenen Entscheidungsfindung („Data-Driven Decision Making“) als auch bei der Optimierung und Automatisierung von komplexen datengetriebenen Prozessen unterstützen: denn ein Prozess ist eine Folge von Entscheidungen und Aktionen. Aus der Verknüpfung mehrerer datengetriebener Prozesse entstehen datengetriebene Produkte und datengetriebene Geschäftsmodelle. Auch bei dem Entwurf von Prozessen, Produkten und Geschäftsmodellen hilft das Analytik-Anwendungsfall Canvas.
What is Analytics Use Case?
The analytics use case canvas has two sides: the user is on the right and the solution and its benefits for the user are on the left. The canvas thus maps the structure of a use case:
1. What is the user`s problem?
2. What is the solution from the user's point of view?
3. What is the benefit for the user?
The user's problem arises from the set (business) goals and expected (work) results: to achieve these goals, he must perform certain results. For this, he has to perform certain actions and make the right decisions accordingly. In doing so, he is hindered by certain problems and risks on the one hand, and on the other hand he desires certain help and incentives. Only when we have understood this complex interplay of goals & results, decisions & actions, problems & risks ("pains") as well as helps & incentives ("gains"), can we design analytical solutions with a utility value for the user.
This in turn is done on the left-hand side: an analytical solution consists of information and functions provided by the solution to solve the Pains, generate the Gains and help the user make better decisions, take the right actions, efficiently perform their results and effectively achieve their goals. Based on the functions and information, the benefits can be derived accordingly and a comparison with the right side, i.e. the user needs, can be made.
How to Analytics Use Case?
Put the user in the centre of the right-hand side: which user roles are there and for which user do you want to concretise the use case. Write the role, for example "Marketing Manager", on a blue Stattys Note.
Specify the goals & results and decisions & actions.
Then you turn your attention to the user's objectives and results. For example, goal achievement agreements or OKR directories (OKR: Objectives & Key Results) can help you here. Next are the decisions and actions: which decisions can and may the user make and which actions can and may the user carry out? Write the points on your own blue Stattys Notes and place the slips of paper in the appropriate field.
Analyze the Pains & Gains.
For Pains & Gains, use red and green Stattys Notes. Place the notes near the goals & results or decisions & actions that are linked to the pain or gain.
Design and concretize solutions.
Develop ideas on how to help the user using data and analytics and collect them on blue sticky notes in the Solution box. Before rushing to commit to an idea, ask yourself what alternative solutions are available. Only after you have discussed the ideas, focus on one solution approach and flesh it out: what information does the solution provide? What functions does the solution offer? Write the answers on blue slips of paper.
Evaluate the benefits.
What is the benefit of each of the information and functions? Write these down on green sticky notes and place them in the Benefits field. Finally, compare the left and right sides: which benefits (and thus indirectly the information and functions) actually fulfil a need (pain or gain) of the user? Which Pains & Gains are covered by the solution? In short: how high is the problem-solution fit? You may have to choose an alternative solution approach, rethink the current solution or combine several solutions in one application or system.
You can find more information at Datentreiber.
|Size||118,9 x 84,1 cm (49" x 33")|
|Material||Synthetic paper 210 g/m²|
|Weight in kg||0.21|
|Delivery||We do our best to send within 0-2 days with DHL or Deutsche Post|
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