Introducing Compelling New C-Suite Use Cases with SAP Data Warehouse Cloud.
Capturing The Performance Advantage Today — New C-Suite Performance Accelerator Use Cases For The Intelligent Enterprise With Intelligent Analytics and SAP Data Warehouse Cloud Innovations.
Dear Customer Please Note: Interested to follow along with your own use case scenario based on the model we develop for SAP Data Warehouse Cloud content distribution — please apply to Chris.Hearnshaw@aqoiagroup.com
Article Summary:
Introducing Compelling C-Suite Use Cases with SAP Data Warehouse Cloud.
Operations increasingly play a differentiating and interdependent role in overall business performance. Today enterprises are struggling to keep pace with change as businesses develop new operating models to capture new customer opportunities faster and more effectively than those of their competitors.
Technology-enabled growth secured through speed agility and a continuous stream of quick wins that free cash capacity and build competency is a massive driver for achieving the value of sustainable transformations along with broad enterprise engagement and active cost management.
Better cross-functional alignment and end-to-end views within and across markets and clusters, with improved orchestration, integration, and value capture, is a pressing issue for every C-Suite.
These drivers are playing out market by market beyond the line of sight of standards-based group systems. As the complexity and speed of business increases, unaddressed operations are a growing value trap. Analytics and technology endeavors underpinning functional and cross-functional teams have until now failed to identify friction and release this value, dragging results.
As a consequence, at the customer experience and operational execution interface, there remains a significant and growing low hanging untapped value pool to be captured and repurposed. Addressing this problem can not only help provide immediate relief to aggressive short term targets but give a foundation capability for sustainable, profitable growth with an accelerated pace of change.
We propose new analytics Use Cases underpinned by SAP Data Warehouse Cloud to enable timely new value release and a sustainable culture shift and capability. We will evaluate how SAP Data Warehouse Cloud performs in fulfilling these ambitions across the business, functional, technical, and commercial dimensions over alternative market options.
Can The New SAP Data Warehouse Cloud Help Your Organization Achieve Timely And Differentiated Enterprise Data Management Capabilities?
Important C-Suite Questions
- Can SAP Data Warehouse Cloud along with the Intelligent Enterprise Platform, become the engine for building out your Enterprise Digital Nervous System? It’s not just about the WHAT but more about the HOW. Connected intelligence is an essential requisite for being an intelligent-enterprise — HOW do we get there?
- With the recent leadership change and Tech-ed announcements, does SAP now have a modern executable “intelligent-enterprise” focus and platform vision to lead customers into the digital economy safely?
- Are SAP Data Warehouse Cloud in conjunction with the intelligent enterprise components like the Digital Core, Digital Platform and Intelligent Technologies a better integration option than alternative choices for accelerating your journey to being a sustainable data driven intelligent enterprise? Is the technology now accessible, scalable, sustainable and consumable, — today for solving your pressing analytical use case problems?
AQOIA, using advanced enterprise modeling capabilities to build out difficult to achieve relevant high-impact cross functional use cases using SAP Data Warehouse Cloud, will help accelerate your answers to these critical questions.
By demonstrating how well SAP’s latest innovations underpin sustainable C-Suite strategies, we will determine the business case to press forward with the intelligent enterprise ambitions. Organizations will clarify and accelerate their respective People Data and Technology-driven ambitions, roadmaps, and capabilities.
Why Your Analytics Programmes Struggle: The Issue Today With Enterprise Analytics and Business Intelligence
Specifically, driving profitable growth sustainably — one transaction at a time. Achieving current short-term business objectives, while securing a robust platform for future growth is the CEO imperative that is underserved by existing enterprise platform and analytics capabilities.
Every C-Suite knows, through hard lessons, there are know-how, data, and technology limitations. These effectively impede and frustrate the ambition of every forward-thinking data-driven enterprise struggling to compete with digital natives like Amazon.
The vast majority of analytics business case scenarios to-date have
- failed to materialize against expectation
- are unable to yield new impactful business results
- have not scaled into the enterprise
- …
The C-Suite and Sponsors of these analytics programs are disappointed with delivered capabilities. The very bedrock for digital transformations.
Endeavors to build a unified enterprise data fabric to serve deep insights in volatile conditions leave a myriad of disjointed point solutions. Expensive shadow IT spring up in response, driving overlap in technology, administrative overhead, and a growing pool of disparate, disconnected inaccessible datasets. Data chaos leads to poor augmented decision and automation capability — a far cry from the data-driven “Intelligent Enterprise” imperative.
Securing continuous intelligence capabilities through mastery of data via an enterprise data platform is not only a foundation for digital transformation but a source of sustainable competitive advantage. Organizations that gain the upper hand over their competitors, as we have seen with Amazon for example, will inevitably win the day.
Introducing The Enhanced SAP Intelligent Enterprise Journey With SAP Data Warehouse Cloud And AQOIA Intelligent Analytics Suite
SAP has built a platform and vision for the Intelligent Enterprise to accomplish this ambition:
The key question is, as noted above, HOW do we best get here? With applied knowledge, the source of competitive advantage — what’s the smart way? Can we accelerate the adoption of applied analytics at scale to enable an organization to become an Intelligent Enterprise? How can we better leverage Legacy systems, S/4 HANA, C/4 HANA, Success Factors, and any other SAP and 3rd party operational system like SalesForce to maximise value of the operational transaction layer to drive intelligent analytics value?
AQOIA as part of our Intelligent Enterprise Enablement Framework has developed advanced analytical models to compliment Operational and Experience data, that can include what we call Temporal data. Specially curated T (Temporal) data brings together and sets into context the WHY (Experience Data) and the WHAT (Operations Data) of enterprise activity with the HOW (Temporal Data)?
Curated T Data helps answer the essential yet difficult and nuanced HOW “do these relate” questions that naturally follow the WHAT and the WHY before targeted action is taken. For example — which customers products services and experiences are yielding most growth and profitability factoring all operational activities. These essential questions traditionally take up an analysts time to answer badly. Better clarity beyond the line-of-sight of traditional joined datasets is necessary to inform intelligent choices to yield sustainable growth and smart cuts. T data has proven to yield significant performance results over untreated or analyst curated datasets.
Once the HOW is established it’s possible to take key decisions around directing critical resource allocation to optimize, maximise and multiply enterprise results sustainably with a very high precision. T Data futher enhances AI Augmentation and Automation capabilities through improving deep pattern detection scenarios impossible for humans alone to detect.
Data Driven Enterprise — Mastery Of Data, Talent, Technology, The Pillar Of Competitive Advantage In The Digital Economy
Data is the differentiating fuel of the Intelligent Enterprise. The Enterprise Data Platform is the engine that powers it. Artificial Intelligence, Augmentation, and Automation the services that consume it. Applied talent the capability that differentiates it. Every organization is and will endeavor to make more and better use of their ever-expanding data-trove as they seek to gain the “insight-advantage.”
With advancing Industry 4.0 to Society 5.0 challenges ahead, the bar is set to rise higher. The driver to become increasingly sophisticated integral and dynamic people data and technology-driven brokers are table stakes for sustainable business growth and leadership.
Can We Better Address the CEO Challenge With SAP Data Warehouse Cloud?
Can the introduction of SAP Data Warehouse Cloud with xTo Data into your enterprise’s technology landscape today help with your specific CEO Challenge, for example:
- Break the traditional business utility and enterprise technology deadlock that holds back and constrains impactful and sustainable analytics initatives.
- Boost existing inflight data-driven strategies, sustainable growth, and profitably targets in an accelerated non-invasive way to give your teams the market edge?
- Introduce a step change to driving better, faster, and more sustainable analytical data-driven business outcomes?
- Extend and compete with existing and alternative options from established actors who specialize in the enterprise data management arena?
For those many organizations striving to reach the apex of the intelligent enterprise maturity curve, capable of leapfrogging digital and analytics leaders like Amazon, these are non-trivial questions.
The Execution Challenge To Now: The Enterprise Data Management Arena Is Crowded, And SAP Was A Laggard In Hybrid BI Environments
Many traditional enterprises with an unwieldy ever-expanding technology footprint are today struggling for good reason. SAP offerings have fallen well short of enabling ambitious data-driven enterprises to project advanced data management capabilities beyond the core SAP ERP and Business Warehouse layer. Other technology actors for this purpose, have assumed the leadership role as the natural builders of the necessary and much broader farther reaching and complex “enterprise-data-fabric.”
The blog series helps reporting, analytics, and enterprise data platform leaders, along with SAP system owners to objectively evaluate SAP Data Warehouse Clouds’ potential to accelerate and improve sustainable business outcomes as they journey towards becoming an intelligent enterprise.
We will achieve this by developing an advanced use case based on AQOIA Intelligent Analytics Suite for SAP Data Warehouse Cloud.
We will put SAP Data Warehouse Cloud through its paces. In the process, we will short circuit your learning curve to drive better, faster, and more sustainable performance outcomes. The process will help set in context the quality of your evaluation to meet present and future needs.
Over the coming weeks of the beta program, we will develop a proven, very advanced analytical use case featuring T data on SAP Data Warehouse Cloud to objectively:
- describe what you need to know that most people don’t know
- define what you need to do that most people don’t do
- explain how to go about doing things that most people don’t know how to do
to drive advanced analytics success.
In the process, we anticipate, you will, throughout the series, acquire the grounding knowledge and tools to accelerate your journey to becoming an intelligent enterprise.
We have developed cutting edge analytical scenarios set well beyond the boundaries of traditional enterprise data warehouse capabilities:
- Curating data from multiple data sources to build Bottom-Up Outside In Learn Lead Local Leverage Global datasets
- Drive innovation and investments with Market, and Customer leadership
- Extract cashable benefits from growth and improving existing operations with X-Functional collaboration. Our production models can yield more than 1% of revenues to the bottom line
- Glocal Market to Group Integrated Analytics to enrich current enterprise data scenarios
- AI Timewarping algorithms to drive advanced “ThroughTime” and ThoughtTime curated datasets
We aim to validate executing these capabilities against SAP Data Warehouse Cloud.
SAP Data Warehouse Cloud Enterprise Evaluation With T Data Blog Schedule:
Blog 1: Achieving the CEO Challenge — What’s needed?
A background introduction to the business challenges becoming an Industry 4.0 to Society 5.0 sustainable data-driven intelligent enterprise, and what we can do about it. The problem has never been more significant or more important — an exploration of the parameters that constitute success we recommend exploring. Whilst the focus on this series about the underpinning technology and data capabilities, there is a critical people and culture dimension we will address by providing new levels of transparency.
Blog 2: Advanced Analytics Use Case Deep Dive
We will explore detail around the analytics use case we have chosen for SAP DW Cloud. In this context, elaborate on the challenges current clients have from a business functional and technical perspective and how T Data can better help address these within and cross functional challenges. We will set out how we anticipate to address them with SAP Data Warehouse Cloud scenarios.
Blog 3: Building The T Model — What Are We Learning So Far
A discussion around the key themes introduced in the first two blogs executing the use case and how we are making out in addressing them against our generic Enterprise Data Management Evaluation Framework.
Blog 4: Preparing The T Model For Show Casing. Expectations?
A review of the final model fitted into the SAP Datawarehouse Cloud Landscape with a synopsis of how well the solution architecture supports our use case, along with challenges, opportunities, and roadmap items.
Blog 5: Showcasing — Sponsors Stakeholders Engineers
A review of the showcasing results by stakeholder community with feedback on the usability and utility of the Use case across the various stakeholder groups. Are we a step closer to becoming an intelligent enterprise and achieving the CEO challenge?
Blog 6: How Do We Execute A Real Use Case Pilot?
Approach, Effort, Phasing, Commercials, and use case recommendations based on our learnings and feedback. What is SAP Data Warehouse Cloud good for, and how can you make the most use from it?
Blog 7: Introducing Your SAP Data Warehouse Cloud Pilot Evaluation Accelerators
Sample project plans tools and checklists along with IAS SAP delivered content and connections to SAP Analytics Cloud to aid your SAP Data Warehouse evaluation. Our IAS advanced analytical scenario will help solve a complex problem aligned with current business priorities.
Some Critical Questions BI Analytics and SAP Owners Are Asking We Expect To Answer Regarding SAP Data Warehouse Cloud
As we progress through the Beta program with the above Use Case Scenario, we will seek to clarify some timely and crucial questions Client strategy teams are asking as they build towards becoming a data-driven Intelligent Enterprise:
Some Commercial Questions
- I have spent millions on BW, BO, Tableau, etc. What is this bringing new to the table, and how do I leverage those millions I have already paid.
- How can you best go about evaluating and testing SAP Data Warehouse Cloud for your use cases?
- What does this cost to develop test build and operate? What are the commercial dimensions and parameters for a pilot and scaled deployment?
Some Business Questions
- We have spent a fortune on analytics efforts and so far we are very disappointed in the results. Not just related to SAP. We are very cautious about making yet another investment to evaluate technical and functional capabilities?
- To what extent can SAP Data Warehouse Cloud help us address the people dimension of Analytics? We all know success is about broad user adoption and this is why most enterprise Analytics initiatives fail. How can SAP Data Warehouse Cloud help us address this challenge?
- Does SAP Data Warehouse Cloud solve our analytical challenges and problems in a new way better than alternatives?
- Can I get high impact results better faster and more sustainably than alternative approaches?
- How does SAP Data Warehouse Cloud add value towards solving the Enterprise Data Management challenges faced by all of SAP’s customers?
- Is there a transition path from where I am to this?
- Am I not safer going down a HANA|BW4/HANA route as I have 20 BW developers who understand how that works?
- How can we help migration and adoption to SAP S/4 to achieve scalability and agility?
- How can new sources of rich curated data curated through SAP Data Warehouse Cloud “change my enterprise culture” to data-driven, through increased transparency and reliability?
- How does SAP Data Warehouse Cloud stack up against Power BI to support advanced use cases?
- Can SAP with the release of SAP Data Warehouse Cloud finally be considered a “player” in the Enterprise Data Management space?
- Can SAP Data Warehouse Cloud meet the full range of requirements needed by a modern enterprise data management capability?
- Can SAP Data Warehouse Cloud better enable a hybrid SAP landscape over alternative presently preferred options?
- How does SAP Data Warehouse Cloud sit with and operate with SAP’s other business intelligence options and scenarios from the perspective of building an enterprise data management layer and modern digital fabric?
- How does SAP Data Warehouse Cloud fit in with the rest of the SAP Stack present and future?
- Can SAP Data Warehouse Cloud compete effectively in a large, deep established, and crowded space?
- What use cases and scenarios are best for SAP Data Warehouse Cloud?
- How does this align with the roadmap and vision for SAP’s Intelligent Enterprise capability and platform?
Some Functional Questions
- Oh no, not another SAP solution! What is different about this from BW4/HANA — Which you already told me was the way forward. We’re mixing SAP data and non-SAP Data, along with SAP BW’s structure, governance, and master data harmonization capabilities?
- Why Cloud, isn’t it enough for me to create my Enterprise Data Warehouse in house and access via Cloud e.g., SAP Analytics Cloud
- SAP always say you can mix data but is never as easy as they say, what makes this any different?
- How do we better enhance an enterprise data platform with SAP and non-SAP data Sources like SalesForce?
- How do we publish and manage data to various types of data consumers from executive c-suite, business analysts to a machine to AI?
- How do we service the various management groups that require different views and flavors from a curated, authoritative dataset?
Some Technical Questions
- How easy is it to run and operate SAP Data Warehouse Cloud in a production landscape?
- Do I need to recreate all my reports from scratch…can you put any other reporting tools on it?
- SAP Data Warehouse Cloud is new technology, how robust is this to support workable use cases today?
- How do we bring the operational data layer in context to allow an analytical layer to be used on top to produce actionable insights sustainability?
- How do we manage and see data cataloging concerning master data reference data and hierarchies to support complex self-service scenarios from an authoritative published dataset?
- How do we explore complex data lineage?
- How do we manage security and access rights for complex scenarios?
- What are the EDM integration capabilities on the inbound outbound curation and presentation layers with SAP Cloud, SAP Transaction Engines, Third-Party systems?
- How can we support Enterprise Data Management like capture curate and consume workflows, SAP non-SAP sources, Operational and Analytical sources?
- Who can see the data, whats the persistence and approach curating advanced data flows from source to target of various data sources to destination
- What does performance look like (load/query) when scaling large complex datasets (e.g big data profitability with many users and dynamic interactions).
- What is the admin and upkeep like making changes to the underlying models and Users?
If you have any questions, comments, or things you would like for us to explore through this series, please let us know.
