From technology to data culture: management in focus
Becoming a data-driven company does not mean that IT introduces an analysis tool. Rather, it means that management takes responsibility for establishing a data culture and leads by example.
We advise and coach management, explain correlations and terms and show what it takes to implement analytics excellence.
Key benefits and points of contact for management-relevant analytics topics
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Contact person for management-relevant analytics topics
Questions and correlations in the field of analytics explained in management-friendly language. Our management consulting is technology-free - i.e. this consulting does not require SAP or Google.
Clarity regarding responsibility for analytics and the correct introduction of analytics
Management is clearly responsible for ensuring that analytics is introduced correctly. Based on this clarity, the necessary next steps can be identified and tackled so that a data-driven culture is established and analytics can be used to a greater extent.
Be prepared for bad times
In difficult times, quick access to reliable key figures and information is essential. The systems and employees must be ready for this. With our consulting approach, we point out the necessary steps.
Leading by example and being a role model
By gaining an understanding of the interrelationships and quick and easy access to information, management is put in a position where it can exemplify the culture of the data-driven company and thus set an example for employees.
What is management consulting for analytics?
Management consulting for analytics includes targeted support and advice for companies in all matters relating to the use and implementation of data analysis and technologies. The aim is to help companies to act in a data-driven manner and thus achieve their business goals more effectively.
These consulting services typically include:
1.
Strategic consulting: Developing a clear vision and strategy on how data can be used to gain competitive advantage or increase operational efficiency. This includes defining goals, determining the resources required and setting KPIs to measure success.
2.
Technology consulting: Evaluation and selection of suitable analytics tools and technologies that meet the company's specific requirements. This often includes advice on platforms, databases, software solutions and cloud services.
3.
Data management and governance: Development of strategies and guidelines for managing and securing data. This includes aspects such as data quality, data protection, compliance and data governance.
4.
Change management: Support with the implementation of new processes and technologies in the company. This includes training employees to promote acceptance and use of the new analysis capabilities.
5.
Analysis and insights: Helping to interpret data and generate insights. This includes conducting analyses to identify trends, create forecasts and make informed decisions.
6.
Continuous optimization: Monitoring and adjusting the analytics strategy over time to ensure it meets changing business needs and market conditions.
Through targeted management consulting for analytics, companies can not only use their data more effectively, but also promote a culture in which data-based decisions become the standard. This makes a significant contribution to strengthening competitiveness and promoting sustainable business growth.
Why do I need management consulting for analytics?
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You ask yourself the following questions: Do you want to generate information, knowledge or even new business areas from data? Do you want to become a data-driven company and initiate a cultural shift towards "data-based decisions"?
Bridging the gap between IT and management: understanding data-driven decisions
We not only speak the language of IT, but also that of management. Our approach includes explaining correlations and buzzwords, explaining their meaning and clarifying which measures are necessary to make your company truly data-driven.
Today, we have extensive technical analysis options and large amounts of data that make it possible to integrate transparency, control and decision support into all areas of your company. As your analytics partner, our aim is to show you what steps you need to take to benefit from these opportunities and how you can gain valuable insights from data.
Management consulting approach and strategic vision
The aim of our management consulting approach is to identify and explain correlations, discuss possible uses of technology and analytics and integrate them in a meaningful way. We attach great importance to a clear strategic vision for the use of analytics in the company.
Fit-gap analysis and data-related strategy
Understanding which steps are necessary for a successful introduction of analytics is also relevant for these topics. We define a clear strategy to achieve your goals with the help of data and conduct a thorough fit-gap analysis to identify necessary adjustments.
Importance of data quality and governance
In this step, we cover not only technical but also essential topics such as the role of employees
in processing results and ensuring data quality. Topics such as data governance are crucial for an effective data strategy.
From vision to reality: implementing a data-driven culture
A data-driven company is not created simply by implementing an analytics tool. Our consulting is technology-independent, as the tool is ultimately only a means to an end.
Overview: Key topics in management consulting for analytics
The following table shows the key areas that are of crucial importance in management consulting for analytics. These areas form the basis for the successful introduction and integration of analytics in companies. Each field addresses specific aspects, from the strategic alignment of the data & analytics strategy to ensuring data quality and integration into existing company processes . The table provides an overview of the key steps and measures that are necessary for the effective use of data and the realization of a data-driven company.
| Subject area | Description Subject area |
|---|---|
| Understanding the company and data | An in-depth understanding of the organization is crucial in order to clarify requirements and expectations. This includes the current status of analytics usage, the system landscape and the customer's organizational structure. |
| Strategic alignment of data & analytics | Aligning the data & analytics strategy with the business objectives is essential for success. The aim is to establish an analytics culture that transforms the company into a "data-driven business". |
| Data Governance | A structured data governance process ensures efficient handling of data through clear rules on data ownership, data management and access rights. |
| Organization and competencies | The definition of roles, responsibilities and competencies is crucial for the development and prioritization of analytics projects. It is important to ensure that the company has the necessary resources and skills to use data effectively. |
| Architecture and infrastructure | A solid data architecture, including databases, analysis tools and data warehouses, forms the basis for a robust technological infrastructure. |
| Ensuring data quality | Ensuring high data quality is essential for precise and reliable analytics results. This includes measures to ensure the consistency, accuracy and timeliness of data as well as the definition of ownership and lifecycle processes for data objects. |
| Building a data culture | A data culture is promoted through training, marketing and communication to ensure that employees understand the new technologies and processes and can use them effectively. |
| Integration into existing processes | The seamless integration of data & analytics into existing business processes ensures that the insights gained offer direct added value for the company. |
| Scalability and flexibility | Solutions and concepts should be designed in such a way that they are scalable and can be quickly adapted to the company's changing requirements. |
| Standardization and documentation | The creation of a glossary and the documentation of terms and key figures promotes a uniform understanding within the organization. This includes the definition of data as a product and the definition of ownership. |
These topics form the cornerstones for the successful introduction of analytics in companies and must be continuously reviewed and adapted to meet evolving requirements.
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Your contact for the topic of management consulting for analytics
"Analytics is not just a technology, but a strategic decision. Our consultancy enables management teams not only to understand data, but also to use it in a targeted way to promote a data-driven culture and thus sustainably increase the company's success."
- roger.heckly@s-peers.com
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Roger Heckly
Customer Success Executive
- roger.heckly@s-peers.com
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Important questions about management consulting for analytics
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Certain questions play a central role in our analytics management consulting. Here are answers to some frequently asked questions to help you realize the full potential of analytics, foster a data-driven culture and support strategic decision-making.
A sparring partner in management consulting for analytics is critical to provide strategic insights, cut through complexities and support the development of a data-driven culture. This partner provides an external perspective and subject matter expertise that can help identify challenges and develop effective solutions tailored to the organization's specific needs.
The responsibility for analytics clearly lies with management. It is crucial that managers recognize and actively promote the strategic importance of analytics. They should ensure that analytics is not just seen as a technology project, but as a central component of the corporate strategy.
Yes, a coaching approach in management consulting for analytics can be designed to be technology agnostic. This means that the consulting is not dependent on specific technology platforms such as SAP or Google, but focuses on fundamental principles and methods to optimize analytics use and strategy.
A data-driven culture is implemented through several measures, including the promotion of data literacy and awareness throughout the organization, the integration of data into decision-making processes, management support for data-driven initiatives and the establishment of clear processes for data analysis and use.
This can be achieved by establishing clear guidelines and processes for data collection, analysis and use, providing training and awareness for data-based decision making and actively encouraging managers to use data in their decisions.
With a self-service BI approach, aspects such as data quality assurance, user-friendliness of the BI tools, employee training in the use of the tools, access and security guidelines and support from a central analytics team must be taken into account.
AI / AI Analytics can help create a competitive advantage by identifying complex data patterns, generating predictions and recommendations, automating processes and providing insights that enable fast and accurate decisions. By using these technologies, companies can react more agilely and proactively to market changes and develop innovative solutions.
KNOWLEDGE
Things to know about Analytics Reporting
Success stories
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Success stories
The success story highlights the challenges and initial situation of a project at the CSS Group dealing with the budget and projection process. Previously, these processes were carried out manually using Excel files, which led to time losses, susceptibility to errors and inaccurate planning. The aim of the project was to improve this process, enable precise planning and carry out efficient extrapolation.
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Success stories
Starrag AG was faced with the challenge of automating manual processes in the finance department, in particular the time-consuming preparation of monthly reporting. The decision was made to implement the SAP Analytics Cloud (SAC), supported by the expertise of s-peers AG.
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Past events, Events, General
Companies such as AXA Switzerland face various challenges on the road to transformation into a data-driven company. In addition to technological aspects such as the integration of data platforms and the associated tools...
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INFORMATION
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The SAP Analytics Cloud (SAC): Future-oriented reporting
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SAP Datasphere - The future of data warehousing
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Planning with SAP - increasing success with cross-departmental planning
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References
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