Business runs on data. Every decision, every customer interaction, every supply chain adjustment depends on the assumption that the data behind it is accurate and reliable. But the reality is different. In fact, 67% of data and analytics professionals admit they don’t fully trust the data they use for everyday decision-making.
That trust gap has consequences. Slow decision-making. Compliance risks. Costly inefficiencies. And with AI now fueling core business processes, the stakes are only higher. Poor-quality, inconsistent data leads to wrong answers, and undermines confidence in the systems that leaders are betting their business on.
That’s why data integrity has become a board-level concern. It’s not only about data quality – the accuracy, completeness, and timeliness of data – but also about ensuring that data remains consistent and unaltered throughout its lifecycle. In other words, data plus process equals integrity.
Automation can be one of the most powerful levers to close that gap – but only when it’s built on a foundation of strong data quality. Without quality, you simply automate bad data faster, particularly in your SAP® environments.
Automation Supports Agility, Speed, and Trust
Manual data processes don’t scale. In SAP environments alone, a single material record can contain more than 300 elements. Multiplied across thousands of products, customers, or suppliers, the complexity is staggering.
Not to mention, when you factor in process complexity – often involving dozens of interdependent steps – and organizational complexity across multiple departments and systems, the challenges multiply further.
That’s why automation is now essential to business performance. In our surveys with SAP users, more than half (55%) cite automation as important to their digital transformation initiatives. By reducing manual entry, enforcing standards, and embedding governance, automation directly supports the three imperatives that we hear time and time again from modern businesses:
- Be more agile – the ability to adapt quickly to disruption, whether that’s a supply chain breakdown, a new regulatory requirement, or a fast-moving competitor.
- Move faster – keeping pace with business that moves in hours, not weeks, without simply adding more people.
- Improve data integrity – ensuring that the data fueling these decisions can be relied upon with confidence.
Today, automation is about so much more than efficiency. When paired with high-quality data, it creates the conditions for faster, more confident decision-making in an environment where the pace of change keeps accelerating.
Building a Complete Data Integrity Journey
Think of data integrity as a journey with multiple entry points, intersecting routes, and checkpoints along the way.
Every journey is unique, and yours is going to depend on your unique needs and pace. But from an automation standpoint with SAP teams, it generally seems to follow a fairly standard order.
- Generate – capture data correctly at the start, validating against SAP or other systems before it enters production.
- Integrate – connect data across systems like SAP and Salesforce without introducing inconsistencies.
- Catalog & govern – maintain visibility into what data exists, where it lives, and how it flows.
- Cleanse & validate – remove duplicates, enforce formats, and resolve errors automatically.
- Enrich – augment records with missing details (like verified addresses, geocodes, and industry classifications).
- Monitor – continuously check the health of data across environments to catch issues before they spread.
- Activate & analyze – put trusted data to work for analytics, AI, and operational decision-making.
But here’s what you need to remember: automation alone doesn’t guarantee integrity. Without strong data quality, automating flawed processes only accelerates bad data.
The real breakthrough comes from treating data and process as inseparable. Governance, standards, and stewardship must be embedded into workflows so that automation reinforces, rather than undermines, trust.
From Maturity to Confidence: The Strategic Payoff
From our work with organizations, we’ve seen a clear progression in the automation maturity journey. This breaks down into five “maturity levels,” and you’ll find that what you value grows and changes as your automation maturity level increases.
Here’s how those five levels break down, at a glance:
Level 1: Automation means manual effort saved: value equals cost of manual effort saved by automation. For example, eliminating repetitive data entry frees your teams from tedious tasks while cutting down on human error.
Level 2: Automation means faster business processes: value equals efficiency produced by business process automation. Think of customer onboarding times shrinking from weeks to hours, accelerating revenue recognition and improving customer experience.
Level 3: Automation means better business outcomes: value is defined specifically by business outcome relative to the use case. You should see higher data quality, reduced compliance risk, and more reliable forecasting as automation improves integrity at scale.
Level 4: Automation means business agility: value equals business decision-making speed. You’re able to pivot quickly in response to supply chain disruption or market shifts, supported by data you can trust.
Level 5: Automation means organizational optimization: value equals maximum operational business outcomes. At this stage, automation part of your operating model, enabling continuous improvement across processes, systems, and people.
The higher you climb through these levels, the more profound the impact on your business. At level five, you’ve created a shift that delivers the ultimate payoff: confidence.
When you know your data is consistent, accurate, and trustworthy, you can:
- Move faster without sacrificing control
- Reduce compliance and audit risks
- Free teams from tedious manual tasks
- Enhance customer experiences through speed and accuracy
- Gain a competitive edge by acting decisively on insights
Case Studies: Automation in Action
Real-world results show what’s possible when automation and data integrity come together. These organizations used Precisely Automate solutions to streamline critical processes, reduce error, and accelerate growth:
- Customer onboarding at scale – One enterprise cut its customer creation process from 144 hours to just six. Faster onboarding meant faster revenue recognition and a dramatically improved customer experience.
- Manufacturing agility – A specialty metals company reduced its vendor qualification process from 2.5 years to three months. By automating manual collection and entry steps, it not only accelerated time-to-market but also reshaped its customer relationships.
- Global product launches – A beverage company moved from error-prone Excel workbooks to automated workflows. The result: cutting time-to-market for new products in half while scaling from regional to global distribution.
These examples highlight how organizations are applying automation in practical ways to achieve transformational outcomes. In every case, data quality was foundational – automation then amplified the value by ensuring that trusted data flowed into critical business processes, which resulted in better decisions, faster execution, and stronger customer relationships.
Staying Ahead Among Growing Complexities
There’s a quote I often like to return to, from Justin Trudeau: “The pace of change has never been this fast, but it will never be this slow again.” That captures the reality for every enterprise today.
Data volumes are exploding. AI adoption is accelerating. Business environments shift daily. The only way to keep up is to start with strong data quality, then apply automation to strengthen integrity and cut complexity across data, process, and organization.
Because in the end, trusted data is going to be your foundation for successful digital transformation.
For more on how leading organizations are tackling these challenges, I invite you to watch our recent webinar with TDWI: Automating Data Integrity: Ensuring Trust in an Era of Complexity.
