Data Challenges

Data Challenges We Have Solved | Novon Data Consulting Australia

Challenge 01

Helping Finance Teams Get Control of Management Reporting

Finance teams across banking, superannuation, retail and manufacturing consistently tell us the same thing. Their management reporting takes too long, involves too many manual steps and produces numbers that different parts of the business argue about every month.

The root cause is almost always the same. Data sits in multiple systems, nobody owns the definitions and the report is built by hand in spreadsheets that have been passed around for years. By the time the numbers reach the executive team they are already out of date.

Novon fixes this by working with finance and data teams together. We map the data sources, agree on definitions, build governed data pipelines and deliver automated reports that finance teams can trust and executives can act on.

Reporting cycles reduced from weeks to hours in multiple client engagements

Single source of truth established for all key financial metrics

Manual spreadsheet processes eliminated and replaced with governed pipelines

Finance and data teams aligned on definitions for the first time

Typical Outcomes

80% Reduction in time spent preparing reports

1 Single source of truth for all financial data

0 Manual spreadsheet steps in the final process

Real-time Access to financial data for decision makers

Challenge 02

Reducing the Time It Takes to Close End of Month Accounting

Month end close is one of the most painful recurring processes in any finance function. Teams work long hours pulling data from systems that do not talk to each other, reconciling numbers that should already match and producing reports that are out of date the moment they are finished.

We have worked with finance teams across multiple sectors to dramatically reduce the time and effort involved in month end close. In most cases the problem is not the accounting. It is the data infrastructure underneath it.

When the data flows are automated, the reconciliations are built into the pipeline and the definitions are agreed upfront, month end becomes a much simpler process. Our clients consistently tell us it is one of the highest value things we do for them.

Month end close timelines cut by up to 60 percent in client engagements

Automated reconciliation processes replacing days of manual work

Finance teams freed up to focus on analysis rather than data preparation

Audit trails and data lineage built into every step of the process

Typical Outcomes

60% Reduction in month end close duration

100% Automated reconciliation across key accounts

Days Saved per month end cycle on average

Full Audit trail and data lineage from source to report

Challenge 03

Implementing Microsoft Purview Across Complex Enterprise Environments

Microsoft Purview is one of the most capable data governance and compliance platforms available today. It can scan, classify and catalogue data assets across your entire environment and give you visibility over where sensitive data lives and how it is being used.

But implementing it well requires more than a technical deployment. You need to define your data domains, agree on your classification taxonomy, configure your scanning rules and integrate Purview into the way your teams actually work. Without that groundwork the tool delivers very little.

Novon has implemented Microsoft Purview for several complex organisations. We handle the full implementation from initial scoping and design through to configuration, integration with your existing data platforms and training for the people who will run it day to day.

Full data catalogue established across all major enterprise data assets

Sensitive data classified and governed in line with regulatory requirements

Data lineage visible from source systems through to reporting and analytics

Teams trained and confident in using Purview as part of their daily work

What We Deliver

Full Enterprise data catalogue across all assets

Auto Sensitive data classification and policy enforcement

E2E Data lineage from source to consumption

Live Compliance monitoring across your data estate

Challenge 04

Running Data Governance and Data Quality Programmes That Actually Stick

Most data governance programmes fail. Not because the intent was wrong but because they are treated as a technology project rather than a business change. Tools get deployed, policies get written and then nothing changes because nobody owns the data and nobody is accountable for quality.

Novon takes a different approach. We start with the business problem. What decisions is bad data preventing you from making? What regulatory obligations is poor data quality putting at risk? Once we understand that we work backwards to define the governance model, the data quality rules and the ownership structure that will fix it.

We have run data governance and data quality programmes for some of Australia's largest organisations.In every case the measure of success is not whether the tools are deployed. It is whether the quality of data has actually improved and whether the business can see it.

Data ownership and accountability established across all critical data domains

Measurable improvement in data quality scores across key data sets

Governance frameworks embedded into business processes not just documentation

Regulatory reporting accuracy improved and audit risk reduced

What We Deliver

95%+ Data quality scores achieved across critical domains

100% Data ownership assigned across all key domains

Clear Accountability model with business data stewards

Live Data quality dashboards visible to the business

It's all data, the business changes but the data is the same

Other Data Challenges We Solve

Here are some of the other areas where our senior consultants regularly deliver outcomes for clients.

Data Strategy and Roadmaps

Helping leadership teams define where they want to get to with data and building a practical, prioritised roadmap to get there without wasting budget on the wrong things first.

Cloud Data Platform Migration

Moving organisations off legacy on-premise data warehouses and onto modern cloud platforms including Snowflake, Databricks, Azure Synapse and BigQuery with minimal disruption to the business.

Data Engineering and Pipeline Build

Building the data pipelines, ETL processes and integration layers that connect source systems, transform data into usable formats and keep everything running reliably at scale.

AI Readiness Assessments

Giving organisations an honest view of where their data stands today and what needs to change before AI initiatives can deliver reliable, trustworthy outcomes at scale.

Get Started