#datacleansingprocessinjust12 weeks

Data the New Gold

Data is the backbone of corporate success in the current world of Artificial Intelligence [AI] and Machine Learning [ML]. AI models are trained on massive datasets before they can function effectively. However, the data feeding the AI needs to be clean and hygienic. Bad data is quietly draining revenue from businesses globally.

As per a report on Forbes, Gartner assessed that wasted resources and lost opportunities due to poor data quality cost organizations $12.9 million every year, while Harvard Business Review estimated that bad data costs the US economy $3 trillion annually.

How Bad Data Affects Businesses Globally?

Bad data leads to crucial inaccuracies that impact business decisions and customer experience. Most organizations today are adopting AI for operational and performance efficiency without ensuring that they have a strong foundation. Today, a whopping 94% of organizations are unsure of the reliability and accuracy of their customer and prospect data.

Bad data impacts every aspect of your business, including strategic business decisions. In fact, Uber had once reported losing approximately $509 million due to wrong driver and rider incentive data.

Accelerated Clean Data for Business Velocity

Clean data sets the foundation for digital transformation. In fact, there are some specific attributes that denote that your data is clean. Imagine making a critical decision on a merger or determining the pricing before a product launch, and you find that the AI-driven module is trained on incorrect data inputs. The decision becomes, at best, delayed till you rectify the data or, at worst, flawed. In the current fast-moving business world, every second counts.

This gap is where master data governance frameworks become significant, as they utilize formal policies to ensure that the data used is clean. The C-suite executives today understand the significance of clean data, which helps in making accurate decisions, strengthening positioning, and controlling the narrative. Whether it’s digital transformation or readiness for S/4HANA migration, compliance, or supporting analytics for strategic decision making, clean data is a competitive differentiator.

Many organizations overlook the data cleansing process till it messes up their operational efficiency. Then they want to expedite the process to make up for the lost time. The complete process, including de-duplication, correcting structural issues, handling missing data, and validation, takes time. However, to make your business agile, you must clean the data and do that fast.

To accelerate this clean-up, we are offering an accelerated data cleansing process in just 12 weeks.

What Is the “12-Week” Plan?

Our claim of accelerating the process of data cleansing in just 12 weeks is not based on an arbitrary number without an actionable strategy. It is founded on a repeatable, tested implementation pattern. The following is the result of implementing the plan:

Profile and baseline a master data object (e.g., materials, vendors, customers).

Define governance rules with business owners.

Cleanse and enrich existing records using AI and accelerators.

Validate changes through iterative testing and reconciliation.

Train users and roll out dashboards for ongoing monitoring.

This step-by-step workflow achieves real business outcomes within weeks by utilizing a combination of automation, pre-built accelerators, and business-led workflows.

The SimpleMDG Implementation Playbook

Our typical 12-week data cleansing approach has the following structured workflow:

Weeks 1–2: Discovery and Profiling – Pain points are categorized, and data is profiled after aligning with business priorities.

Weeks 3–5: Rule Definition and Sandbox Validation – Business users configure governance rules in a no-code environment and validate against test data.

Weeks 6–9: Cleansing and Enrichment – Automated de-duplication, AI-assisted suggestions, and enrichment with reference data.

Weeks 10–11: User Testing and Sign-Off – Business owners approve outcomes after evaluating results and validating the source systems.

Week 12: Go-Live and Training – Governance goes live with dashboards and ongoing monitoring processes.

We engage business users from early in the program to avoid any bottlenecks and ensure program adoption from day one.

The Technology Behind the Speed

We achieve our aggressive 12-week timeline by utilizing a precise combination of three critical technology pillars, including the following:

Pre-Built Accelerators – We provide 90+ templates for vendor, customer, material, and finance objects to ensure that organizations don’t start from scratch. Rules and workflows are configured, not coded.

AI-Assisted Cleansing – Machine learning models are trained to detect fuzzy duplicates, suggest merges, and auto-fill missing attributes. Thus, months of manual work are achieved within days.

No-Code Governance – Facilitate business users to configure validations directly through a user-friendly interface. It reduces IT bottlenecks and accelerates deployment.

These pillars work collectively and compress time-to-value without sacrificing quality or control.

Business Outcomes of Fast-Paced Data Cleansing

Accelerated data cleansing works wonders for your business, increasing efficiency, speeding up time-to-market, and improving decision-making. The agility and efficiency of your business are based on clean, reliable data.

Faster decision making – When your reports are based on clean data, making strategic decisions becomes faster and more accurate as you no longer lose time in debugging through possible errors in the data.

Better analytics – Clean data helps in retrieving specific actionable insights.

Improved customer confidence – Accurate customer data drives better engagement, improves experience, and builds customer trust.

Operational efficiency – Automated workflows and processes minimize errors and improve efficiency.

Drive AI-led automation – The smartness or intelligence of AI is mainly dependent on the quality of the data. Cleaner data helps in better predictions.

Compliance – Clean data helps you eliminate audit pressure and comply confidently with regulations.

Clean data is essential for running an agile business that can respond fast to market shifts and ever-changing customer demands. Learn how it impacts different operational functions and ensures that all your strategic initiatives deliver measurable value.

Final Thoughts

To sum it up, bad data quietly erodes your revenue and intensifies the demands of a fiercely competitive business landscape. The longer you take to cleanse your data, the higher your cost of operations. Today, 40% of business objectives fail to deliver the desired outcome because of incorrect data. Prioritize data cleansing for business agility, innovation, and sustainable growth that helps you stay ahead of the competition.Request a Demo to see SimpleMDG in action to clean up your organizational data and provide measurable business value.