A Peek at SAP’s Own Internal Enterprise Data Management and Analytics Journey

The global economy is in the middle of the digital transformation, and we at SAP advise our customers on their transformation journey. However, SAP itself is also undergoing a huge transition towards a new era. The big change is the move of the software industry from on premise to cloud software. With this came a massive change in the underlying business models, so the questions we needed to answer suddenly were very different – much more across the different areas which used to live in silos before. This cast a spotlight on how the different datasets were managed, governed, secured, and structured to support steering, analytics, processes, and business outcomes. It became evident that a cohesive strategy was necessary to avoid gridlock, and moreover, it became obvious that we needed to change something if we wanted to be successful in a rapidly changing market.

At SAP, we addressed these challenges within our own enterprise environment by creating a holistic enterprise data & analytics strategy that brings together data, processes, analytics, and business purpose across corporate domains.

 

The Importance of an Enterprise Data & Analytics Strategy

Data and analytics do not exist in a vacuum. Analytics relies heavily on the underlying data. And data, in turn, is impacted by business processes, systems, and people, and vice versa. And business decisions in turn rely on actionable insights from analytics. This complex relationship should always be well-oiled and well-connected with the broader enterprise strategy to ensure overall business outcomes.

Without an enterprise-wide data & analytics strategy, companies risk making decisions too slowly, with bad or partial data; missing out on crucial insights needed for an informed business strategy; and being out of compliance with data privacy mandates. Orchestrating and automating data flows across silos is also difficult without a comprehensive outcome-driven data strategy.

According to 2018 research by NewVantage Partners, a majority of companies still lack an enterprise data strategy. Asked who has responsibility for such a strategy, 39% of respondents said Chief Data Officers had primary responsibility, 37% said other C-level executives, and 24% said there was no single point of accountability.

 

Practicing what we Preach

To adopt to our new business requirements, we must become an intelligent enterprise – which is no different from our guidance to our customers. This requires a foundation of clean, trusted, and well-managed data throughout the enterprise that is structured to serve business outcomes. It means using data to drive automated decision-making; providing efficient, user-friendly business processes; and enabling insights to drive business success.

To this effect, SAP combined enterprise analytics and enterprise data management groups into a single entity because we saw that these efforts have become inextricably bound together. We needed this tighter collaboration to expand our focus: ensuring that all data is clean and governed and that business objectives and rules are digitized and turned into processes to drive better business outcomes.

Let us share our learnings using a concrete example relating to the most important KPI in cloud companies: the renewal rate. Renewals is a critical key performance indicator (KPI) that tells management how each solution pillar is doing. Here is how we fuel the process of renewal management as a true testimonial of how the intelligent enterprise should run.

By applying our data strategy to the various datasets around the factors that impact renewals, we are now able to keep track of all of the stages customers go through from purchase to go live to renewal and by that leverage the data for a business driven outcome, in our case to improve renewal rates.  Data is available on how many customers have licensed particular products, how many have implemented and how many have not, how many implementations failed, why they failed, how the software is being used, etc. Customer experience data is also included to gauge how well customers enjoy using the software and have derived clear benefits.

We can apply data patterns to customers that are up for renewal to see how likely it will be that they will renew based on machine learning algorithms. We can see if the customer isn’t using the software or if they have opened numerous service tickets. These insights presented in a smart way let us proactively address issues before customers churn. Turning data into business becomes very tangible here.

 

Agile Control and Insight for Enterprise Data

Using SAP’s latest and greatest technologies, our organization is helping SAP to achieve the goal to become a more intelligent enterprise through four major building blocks:

  • Ensure data is clean, governed, and trusted within the enterprise
  • Connect and bring data together wherever it resides into one data platform with automation, orchestration, and full transparency to provide a single source of truth
  • Give data purpose through a central business definition catalog and include business objectives and rules — all abstracted from technical dependencies
  • Make data consumption as easy as breathing, and provide a world-class experience to everybody who needs data in the right manner from shop floor to the boardroom

 

 

Take Control of Your Data and Leverage It!

Data governance must ensure the compliant execution of all data management activities and the alignment with the business and the process world. At the same time, we have the flexibility and agility to decide where and how deep to govern. This is important, especially in situations when we have to work quick; for example, to integrate a newly acquired company.
Adhering to new regulations such as the General Data Protection Regulation (GDPR) in Europe, is another reason to be able to understand where your data is and how to provide full transparency.

SAP views data and analytics as the raw materials that will help steer the business through opportunities and challenges. The intelligent enterprise must be agile and operate in real-time. It can rapidly adapt to changes by leveraging trusted data through the revolutionary use of advanced analytics. And we strive to make the data consumption experience even easier in the future. You can already ask a chatbot your questions instead of finding the answers yourself. And soon you won’t even have to ask anymore; the system will alert you to problems, insights, and opportunities.

  • It all starts with data and the power of an enterprise-wide data & analytics strategy. We would love to engage with you at SAPPHIRE. Here is a brochure for CDO/CAO attendees that highlights a curated set of activities all around data strategy at SAPPHIRE: https://d.dam.sap.com/a/6ntxFYz

 

 

If you can’t make it to SAPPHIRE, check out these assets:

 

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