Counting the cost of a poor production process

For finance professionals in manufacturing, the ongoing battle to balance the books and control costs is often marred by inefficiencies in the production process.

Delays, quality issues, and mismanaged resources all combine to make the manufacturing CFO's job extremely difficult. These issues eat into the bottom line and make accurate financial predictions impossible.

This is compounded by the fact that driving efficiency in these areas is not the responsibility of finance teams, creating a frustrating disconnect between financial necessity and production line reality.

In this article, we’ll show how a data-driven approach drives cost savings, bridges the gap across business functions and eliminates expensive process inefficiencies.

The true cost of production inefficiencies

Despite continuous improvement being such a foundational part of manufacturing, effective data management remains a significant challenge across the industry.

This affects finance leaders as much as it does production line managers, leading to fragmented financial visibility across the full scope of manufacturing operations.

For CFOs, key financial data is often held in siloed systems that don’t communicate with each other. Data inconsistencies between ERP, MES, and supply chain systems make tracking real-time cost fluctuations difficult, leading to inaccurate forecasting and sub-optimal budgeting decisions.

In addition to the risk of initial human error from manual data entry, these siloed financial data streams require constant manual intervention to structure financial data for reporting purposes.

This means that many finance teams spend time cross-referencing Excel sheets and compiling month-ends by hand rather than working proactively to save costs.

Manufacturing’s data problem goes far beyond finance

We’ve explained how traditional financial data management can hamper accounting efforts, but what about its effect on the shop floor?

The scourge of manual data collection causes a host of expensive issues for the production operation itself. This means that despite completely different business functions, finance and manufacturing teams face challenges that stem from the same root cause.

This can manifest in several ways, all contributing to unnecessary costs. Let’s look at the key financial risks involved in traditional production processes before looking at how you can leverage data to solve these cross-departmental problems.

1. Delays and downtime

Even minor production delays, when frequent enough, can become a massive hidden cost in manufacturing. Costs are incurred every time a production line experiences unplanned stoppages due to machine failures, supply chain disruptions, or labour inefficiencies.

This might result in lost production time, late order penalties, or increased overtime expenses to compensate for lost time and meet deadlines. Beyond the direct losses, this downtime can also compound other financial issues, such as reduced asset utilisation rates and equipment depreciation.

The solution to these issues is predictive maintenance and smart workforce planning. However, with data that’s inaccessible, siloed, and not real-time, these issues are often only recognised at the end of shifts or production runs when costs have already been incurred.

2. Poor quality control and waste

A production process with quality control gaps will invariably lead to defects, waste, and rework.

Every defective product that needs to be scrapped or reprocessed translates to increased material costs through wasted raw supplies, higher energy consumption through longer runs, and inefficient use of labour.

This is before considering the considerable financial impact of reputational damage if poor-quality products reach retailers and customers, leading to recalls and lost contracts.

However, even if issues like machinery faults can be proactively mitigated, having quality control data that needs to be manually collected can lead to costly inconsistencies due to human error and formatting issues. For instance, defect reports can be inaccurate or incomplete, leading to misleading cost analyses and incorrect supplier chargebacks, significantly eroding profitability.

3. Inventory mismanagement and supply chain bottlenecks

Without data from every business function working together seamlessly, getting Just In Time (JIT) manufacturing right is extremely difficult.

This inefficiency can have a knock-on financial effect, leading to inventory problems that strain cash flow due to a misalignment between demand forecasting, supply chain management, and real-time production data. This causes:

• Overstocking, which ties up working capital in excess inventory.

• Stock shortages that lead to production halts and missed customer deadlines.

• Expedited shipping costs, as manufacturers rush to acquire materials (at premium rates) to avoid stoppages.

4. Misallocated labour and resource utilisation

An inefficient production process doesn’t just waste materials—it also wastes time.

This time translates to cost, whichever way you slice it, leaving manufacturing companies that don’t have access to real-time data and insights contending with:

• Overstaffed production lines during periods of low demand
• Underutilised skilled workers and suboptimal productivity.
• Time wasted on error-prone manual data collection

For finance leaders, this means paying for labour that simply isn’t generating maximum value.

Data-driven workforce optimisation can combat this, but it’s impossible to get right unless shop-floor leadership have a top-down holistic view of operations across every area of production. Without this, staffing rarely aligns perfectly with real-time production needs.

5. Weak supplier and customer relationships

Poor data management can cause inefficiencies that extend beyond the production line. Delays, quality issues, and inconsistent order fulfilment can also threaten supplier and customer relationships.

This can make it more difficult to negotiate with suppliers, as unreliable demand forecasts lead to erratic purchasing behaviour that can erode relationships over time.

Continuous improvement efforts are stalled due to outdated data. Both quantity and quality issues can also impact relationships with customers and retailers.

At best, this can result in contract penalties for failing to meet agreed service levels. At worst, delivery and defects can lead to a complete loss of customer trust.

From a financial point of view, protecting these supplier and customer relationships will be a top priority for CFOs, maintaining long-term contracts and avoiding lasting revenue damage.

How finance leaders can drive cost savings through data

To overcome these financial risks, CFOs need to advocate a shift from reactive problem-solving to a data-driven approach that enhances visibility, reduces costs, and increases operational efficiency.

The benefit of this is twofold. Firstly, financial operations like reporting and forecasting can be completely transformed with real-time dashboards, reporting automation, and predictive analytics.

The benefits of automatic data collection and real-time data also extend to the production line, taking information from machinery, sensors, and productivity software to empower managers in tackling the challenges we’ve already outlined.

Let’s take 5Y as an example. The 5Y platform acts as a centralised data lake, integrating ERP, MES, financial systems, and everything in between to eliminate silos and provide real-time insights into production costs, procurement trends, and efficiency bottlenecks.

With every tool and system across the business automatically feeding data into a single source of truth, stakeholders at every level can gain an unparalleled understanding of efficiency and cost. This naturally drives collaboration and bridges interdepartmental communication gaps.

Departments don’t need to chase each other for information, and finance teams don’t need to hear about costly mistakes down the line after quick action could have mitigated their financial impact.

As well as being a cutting-edge unified data lakehouse, 5Y is also built on the Microsoft Azure architecture. That means it works with all of your existing tools as well as any new ones you might implement.

For finance teams specifically, this includes seamless integrations with Microsoft Dynamics 365 Finance, Quickbooks, and Microsoft Dynamics 365 Business Central.

For the production line, it means anything, including: Machine Monitoring, Manufacturing Execution Systems (MES), Quality Management Systems (QMS), and Warehouse Management Systems (WMS)

With all data stored in one place and 80% of industry-leading dashboards and reports ready out-of-the-box, 5Y offers a truly holistic view of your financial operations, including:

• General ledger reports: The easy way to see a complete record of your business’s financial transactions
• Budgeting analysis: Examine current and historical cash flow, analyse future demand and make accurate financial forecasts.
• Procurement reports: Use core metrics and KPIs to better understand and optimise your organisation’s procurement process.
• Sales insights & analysis: Discover customer behaviour and sales trends and use the data to make informed decisions.
• Creditor & debtor dashboards: Understand what’s due, who needs paying and other cash flow-related KPIs.
• Financial health dashboards: See key financial KPIs and metrics at a glance to track your organisation’s financial health.

These powerful tools allow CFOs and finance teams to spend less time creating reports and more time analysing to make proactive decisions and save costs.

5Y is also built from the ground up to enhance compliance readiness, offering standardised, audit-ready financial data to significantly reduce your manual reconciliation efforts.

Unlike expensive custom-builds or white elephant in-house solutions, 5Y can deploy and start generating actionable financial insights in as little as 60 days, 50% faster than the competition.*

Meanwhile, the subscription model means there are no massive upfront fees, and your organisation gets exactly what it pays for.

Redefining the role of CFO’s to drive continuous improvement

It might not seem like the job of finance leaders to champion a data-driven future, but the costs of inefficient production processes are simply too risky to ignore.

With the benefits of unified data management clear, CFOs in companies relying on outdated practices need to be the voice of reason and articulate the impact of disconnected, siloed data to strategic leaders.

Read our whitepaper to learn more about how to make the case for data analytics and reduce manufacturing costs.

*50% faster implementation and 50% reduction in engineering costs are based on our observed averages across typical client projects. Actual results may vary depending on project scope, data quality, and unique business requirements.