Data: The Fuel for an SAP S/4HANA Implementation

Created on November 16, 2021
Last updated on May 6th, 2022 at 10:31 am by Kimberly Sharp

If SAP® S/4HANA® is your company’s digital transformation engine, your data is its fuel. Curating master data prior to your S/4HANA implementation project, not during it, is a crucial factor for a successful project. Beginning your journey with high-quality data and putting in place a data strategy that lives beyond your project will build the foundation that will ensure your data program’s longevity.

In this article we share the essential steps in building a data-driven program focused on achieving better business outcomes. Rizing’s approach to data management and governance is grounded in the belief that data starts and ends with people and is supported by technology.

What is data governance?

Data governance enables an organization to ensure that high data quality exists and moves seamlessly through all systems. We see many companies focus on system integration, but not always on the people and process side of the equation. Clearly defined data ownership, accountability, responsibilities, and escalation routes must exist throughout your company.

Governance stretches into business processes to ensure data is captured correctly, consistently, and efficiently. The best way to begin is to establish a data governance council.

Create a data-governance council

A data governance council is a varied group of employees whose purpose is to establish clear data definitions and develop comprehensive policies for their organization. The council assists in creating governing processes, establishing controls, and implementing technology related to the system of record.

A governance council ideally considers the role of employees and technology as it develops a framework for effective collaboration and project management between business units to ensure long-term vision and success.

Keep it sustainable

The execution of a properly established governance committee allows organizations to achieve a sustainable technology and data ecosystem. By slowing down and taking the time to build a sustainable data program and governing body, you’ll avoid of the pitfall of those who eagerly jump into data governance without a plan. Most often those programs simply fizzle out even if the data governance initiative isn’t overtly canceled.

A data governance council org chart

Below is a proposed organizational framework for an emerging data organization. Each role is an integral part in a data program’s success and should ideally be in place prior to initiating an SAP S/4HANA implementation project. By establishing this framework, early decision-making regarding the go-forward data model is considerably simpler.

A sample data governance org chart.

Here’s a closer look at the roles highlighted in the figure above.

  • An Executive Sponsor provides valuable insight regarding an organization’s strategic direction and assists with buy-in related to the council’s decisions.
  • Council Chair and Members are individuals with a diverse set of skills, knowledge, and experience who ensure that policies, rules, and standards are being followed – similar to a corporate board of directors.
  • Data Owners or Subject Matter Experts are the most knowledgeable members of the committee and the most impacted by data governance decisions. Having a cross-section of experts and stakeholders ensures buyin to the decision and prioritization process as well as decision-making informed by a comprehensive perspective on data.
  • Data Stewards are responsible for overseeing data creation and maintaining data which is required to conduct business while also working to ensure data meets rules and standards already in place.
  • IT and other support teams are best involved early to ensure that council decisions complement and integrate with strategic technology priorities. They also ensure business process decisions don’t cause conflicts – especially on larger initiatives.
  • Data Citizens are business users who create and consume data as part of their everyday responsibilities. Evolving into a data-driven culture is highly dependent on this group of individuals in your organization. This group must recognize the added value of establishing well-managed data policies and procedures and the critical role a data governance council plays in achieving that goal.

Develop a holistic data strategy

Graphic shows holistic data governance strategy.Cloud, big data, and social media are powering new opportunities for companies to leverage information-driven insights in real time to respond to customer preferences, identify operational efficiencies and in some cases, create completely new business models.

To achieve transformative business results, best-run businesses treat information as a corporate asset. Data is carefully managed, thoughtfully governed, strategically used and sensibly controlled.

Lifecycle of data

With a data governance council in place, it’s important to build an outcome-based data strategy for your company. We suggest developing a data strategy that encompasses the complete data lifecycle shown in this figure from SAP.

To optimize the use and cost of managing data, it’s important to understand that lifecycle. There are three things that happen with data. We:

  • Create it
  • Use it
  • Stop using it

By grouping data this way, we can easily discuss the costs and activities associated with each stage. A large data project, such as the move to SAP S/4HANA, requires us to be mindful of how we construct our data model and the data we move into it.

Prepping now makes life easier later

Information isn’t brought into an organization for a singular purpose, it’s required for many uses. Preparing information for all of its likely uses up-front makes it easier to repurpose the information later, during the active use stage.

Off-board data to save money

When information is no longer required it should be off-boarded in a manner that’s consistent with your organization’s pre-determined legal and business requirements. Most companies don’t follow this approach and unnecessarily spend millions of dollars each year maintaining outdated data and systems.

Elements of a comprehensive data strategy

A comprehensive data strategy should have technical components that support end-to-end data architecture and a sound roadmap for delivery. Take into consideration the following:

  • Data modeling – use business process maps and models to develop an understanding of required data movements.
  • Flexibility of platforms – build a flexible platform capable of responding quickly to evolving business requirements.
  • Data orchestration – maintain data in a single location with capabilities to enrich and govern data being distributed to other systems in your landscape.
  • Data quality – achieve high data quality with well-defined metadata, policies, rules, and standards.
  • Master data governance – evolve governance methods from passive to active by defining processes central to your critical data.
  • Retention and archiving – automating end-of-life data processes increases compliance while decreasing costs and risks associated with policies such as GDPR (Global Data Protection Requirements) and CCPA (California Consumer Privacy Act).
  • Analytics – rely on data warehousing capable of supporting a variety of analytics including BI (business intelligence), financial planning and predictive analytics, such as AI (artificial intelligence) and ML (machine learning).

Assess your data readiness

The best way to start your data journey is to understand where you are (the current state of your data) and where you want to end up. We do that by completing a capabilities assessment and mapping the results to your defined capabilities maturity model.

This exercise will define the dimensions and the underlying capabilities. It’s also important to capture observations and opportunities. Once the exercise is complete, you’ll have a summary document like this:

Data maturity model graphic.

Using a simple maturity model scale, from 1 (capability does not exist) to 5 (capability is leading or best practice), you’ll quickly gain an understanding of the health and quality of your data. The outcome of this exercise will aid you in determining what to tackle and when, as it relates to data cleansing and enrichment activities required for your project.

Benefits of data readiness

Gaining a better understanding of your data is always beneficial, however, completing this work up-front has the added benefits for your SAP S/4HANA implementation project. Benefits include:

  • More focused project scoping
  • Reduction in the time required to draft functional and technical specifications
  • Decreased blueprinting and development costs
  • Shorter testing cycles
  • Increased business adoption by introducing a higher degree of trusted data

Data readiness ensures project success

Data readiness involves much more than your data and technical platforms. It also includes elements of organizational design and business strategy to effectively prepare your company to move forward with its SAP S/4HANA implementation.

Taking the time to complete these steps prior to beginning your project can have a lasting and positive impact on your company.

Talk to a Rizing Expert

Whether you’re just getting started or are well on your way, we can help.