Organizations today have an abundance of data available – data about customers, suppliers, employees, equipment, plant operations, purchasing, sales, external market intelligence, economic data, etc. The ability to harness this data and combine it with additional external sources of information (i.e. weather data and member data) would better position the organization to identify trends more quickly, enhance decision making, and improve future-focused business planning activities.
Most organizations are still in the infancy stage when it comes to analyzing and monetizing the abundance of data available. Companies that leverage data and analytics have a significant advantage over competition!
However most organizations are not able to drive value out of their data assets due to the following key challenges — not aligning data initiatives to business outcomes, siloed data, lack of trust in data, lack of data governance, and approaching data as a technology problem.
These can be colossal challenges to overcome. Managing data as an enterprise asset requires a comprehensive approach at different lifecycle stages to create business value out of data.
On the other hand, Analytics technologies have evolved rapidly over the last decade - with notable advancements in Modern Data warehousing, Data Lakes, IoT, Predictive Analytics, Augmented Intelligence with Machine Learning, and Embedded Analytics on SAP S/4HANA Platform. Organizations now have a unique opportunity to leverage these analytics technologies to rethink businesses processes from scratch and transform decision making within the organization, integrate analytics deeper within business applications and deliver contextualized insights that drive action. As companies start embracing analytics, it is imperative for organizations to develop best-in-class analytics capabilities in order to remain highly competitive and continue to grow in the marketplace.
Short-term tactics will bring your organization temporary results, but to compete in the long-term, you need more than a quick fix
— you need an effective business analytics strategy!
In an increasingly competitive market, analytics can be the engine for developing differentiating business capabilities. However, most organizations struggle to put together a coherent strategy to combine people, processes and technology to drive business value with data and analytics.
Existing business processes rely on business reporting and struggle to outline the value proposition for analytics.
Difficulty in overcoming the organizational comfort with traditional reporting processes.
Aligning with the business stakeholders to develop an analytics vision for the organization.
Challenges related to data access, data quality and data harmonization are barriers to leveraging analytics effectively.
Key decisions on making a call on incremental improvements versus radical change in approach to analytics will have an impact on how to leverage.
It is imperative that organizations take a fresh approach to data and analytics. It is critical to design, demonstrate and deliver business value through market-making and market-leading data and analytics strategies. These strategies must be sustainable and scale with business ambitions that are underpinned by data management. They must push the frontiers of the possible. Business ambitions should be made actionable by analytics that generates value for the enterprise and ecosystem by transforming data into business outcomes. Increasingly, these analytics will evolve through artificial intelligence — a transformative technology that drives sustainable competitive advantage.
To envision an intelligent enterprise, data must be considered as a strategic asset rather than the means to run day-to-day operations. Any DnA strategy and roadmap initiative need to start with a comprehensive review of the business context – Understanding of the business goals and objectives, assessing the current state – an audit of existing usage/capabilities/tools in the organization, envisioning the future state. A DnA strategy documents transformational recommendations and plans that empower the organization to leap from
A mindful and systematized rollout of the strategy is important for a seamless transformation ensuring coordination and communication among the business functions and the capabilities. An effective analytics roadmap should help in articulating the business benefits of the strategy by offering incremental value through quick wins while keeping the focus on the broader long-term strategic vision. The strategy should also identify the risks in implementation of the strategy and outline a plan for mitigating the risks.
If I had asked people what they wanted, they would have said: FASTER HORSES
-- Henry Ford
We offer Design Thinking for Business Analytics—a diagnostic & collaborative approach to assist you in creating a simple, effective analytics strategy and roadmap to capitalize on the value of your enterprise data! We help develop a roadmap for how data, technology, organizational culture, processes and people come together to bring about business value.
Through a structured methodology, Applexus will work with your business and technical stakeholders to define your Analytics Vision and Roadmap can create a well-thought-out roadmap for a successful Business Analytics solution that can drive the enterprise. Putting in place the necessary organizational structure, processes and best-in-class technologies will allow your organization to uncover new opportunities, mitigate risks, and take actions based upon real-time data; providing for a clear competitive advantage.
- Customized assessment and strategy workshops to help plan, deploy and optimize analytics investments
- Design and delivery of embedded insights for SAP business processes
S/4HANA Starter Pack
- Unified data and analytics solution in a multi-cloud SaaS environment
SAP Datasphere Migration
- Rapid deployment of focused analytics packaged solutions
- Visualization design, use case development and implementation
SAP Analytics Cloud
- Design of modern organization community and processes