When the plan lives in a spreadsheet, risk lives everywhere else

Ask a pharmaceutical operations leader how the global supply plan comes together, and the answer often sounds familiar.

Every two weeks, a planner extracts transactional data from the enterprise resource planning system, imports it into a complex Microsoft Excel workbook and manually adds the latest confirmations from contract manufacturing organizations. Those updates may come from email threads, PDFs, shared files or supplier spreadsheets. The planner then reconciles formulas, checks assumptions, and attempts to determine whether the resulting plan still reflects what is happening across the supply network.

This process may be familiar, but it is not sustainable.

A spreadsheet can offer useful short-term flexibility. It can also become a critical operational dependency that sits outside the organization’s system of record, lacks a reliable audit trail, and depends heavily on the knowledge of the person who built it.

When the plan lives in a spreadsheet, risk lives everywhere else.

Keep NetSuite. Retire the spreadsheet.

Reducing this risk does not necessarily require replacing the ERP system that finance, supply chain and operations teams already use. Nor does it require committing to a multiyear transformation before the organization can improve planning.

A more practical approach is to add a specialized, pharmaceutical planning layer to the existing ERP environment.

In the Sikich and PLAIO model, NetSuite remains the transactional system of record, while PLAIO provides an AI-enabled visual planning environment designed around the realities of pharmaceutical manufacturing. Sikich brings life sciences advisory experience, NetSuite implementation capabilities and GxP validation support to connect the platforms and help the organization establish a controlled planning process.

The goal is not to rebuild the technology foundation. It is to extend it with planning capabilities that reflect how pharmaceutical supply networks actually operate.

How the NetSuite and PLAIO connection works

PLAIO does not replace NetSuite or overwrite the transactions maintained within it. NetSuite continues to serve as the system of record for orders, inventory and financial information.

PLAIO receives the data required for planning, applies supply, demand and production logic, and returns approved orders to NetSuite. The connection uses PLAIO’s documented and versioned integration API. Records retain their NetSuite IDs, reducing the need to re-key or translate information as it moves between systems.

Information used to build the plan

The integration can provide the records a pharmaceutical supply plan depends on, including:

• Items, shelf life and minimum remaining shelf-life requirements
• Locations, including CMOs and vendors
• Customers and sales orders
• Open purchase orders and work orders
• Confirmed and actual dates and quantities used for on-time, in-full tracking
• Bills of materials and approved substitute components
• Lead times, minimum order quantities and order increments
• Batch-level inventory, lot numbers and expiration dates

Synchronizations are incremental, so only changed records need to move between platforms. Inventory can be provided as individual movements or as a complete snapshot, depending on the operating model.

Approved decisions flow back to NetSuite

Raw planning suggestions are not automatically converted into transactions.

A planner reviews each recommended purchase or production order in PLAIO. After approval, the recommendation enters a to-order queue with the approver documented. The integration then creates the corresponding purchase order or work order in NetSuite. When the order synchronizes back to PLAIO, it is linked to the recommendation that initiated it.

This structure preserves human oversight while creating a controlled connection between planning decisions and ERP transactions.

Integration activity remains traceable

Each inventory change records its originating system, the message that carried it and the credential used to submit it. Duplicate messages are applied only once. If a batch fails validation, the entire batch is rejected with row-level errors rather than partially loading unreliable information into the plan.

Together, these capabilities can help organizations:

• Replace manual entry, emailed reports and attachments with scheduled data synchronization
• Maintain an immutable history of planning changes for QA and regulatory review
• Use machine learning to reduce forecast distortion from one-time anomalies, stockouts or warehouse transfers
• Manage bills of materials, yields and other critical master data within a secure, structured environment rather than an unprotected shared workbook

The result is not simply a more sophisticated spreadsheet. It is a planning environment with stronger governance, traceability and control.

External manufacturing has changed the planning model

Pharmaceutical manufacturing increasingly depends on CMOs and CDMOs. The original draft cites estimates that outsourced providers represent 50% to 60% of worldwide pharmaceutical manufacturing volume and that the outsourced share of global pharmaceutical services spending grew from approximately 34% in 2014 to 49% in 2023.

The draft also notes that 75% to 80% of mid-market drug originators outsource at least one major manufacturing activity. A cited study of sterile injectable drugs found that New Drug Applications were twice as likely to involve outsourced manufacturing.

This shift creates a fundamental mismatch between the information an ERP records and the information planners need to make forward-looking decisions.

When manufacturing occurred primarily inside company-owned facilities, the ERP’s master production schedule could follow activity on the internal shop floor. In an outsourced network, much of the decision-critical information resides elsewhere:

• Confirmed production and campaign windows
• Actual yield variances
• Quality-release dates
• Raw-material availability at the CMO
• Supplier constraints and revised delivery commitments

That information often arrives through emails, spreadsheets, PDFs and external systems rather than through the ERP.

Building alternative internal capacity is rarely a practical response. The original draft cites estimates that a pharmaceutical manufacturing facility can cost as much as $2 billion and require five to 10 years to become fully operational.

The challenge, therefore, is not simply poor data entry. It is an architectural issue.

ERP platforms are designed primarily to record financial and material events. They are not always designed to model shifting commercial forecasts, shelf-life requirements, constrained external capacity and dependencies across a multisite manufacturing network.

Attempting to represent that network in a two-dimensional workbook may create the appearance of a plan without fully representing the operational reality behind it.

Why spreadsheet workarounds become systemic risks

Planners do not rely on spreadsheets because they are resistant to change. They rely on them because spreadsheets are immediate and flexible.

When a commercial team revises a launch forecast or a supplier reports a delay, a planner can add a formula, adjust a buffer or create a new scenario without opening an IT ticket or waiting for a formal software change.

That flexibility solves an immediate problem. Over time, however, the workaround may become the process.

As the product portfolio and CMO network grow, planning workbooks accumulate macros, nested lookups, custom calculations and undocumented assumptions. They often become highly personalized systems that only one or two people understand.

The original draft cites research indicating that operations employees spend an average of 3.6 hours per week correcting spreadsheet errors, equivalent to more than 22 workdays annually. It also cites studies suggesting that approximately 88% of spreadsheets contain errors and that errors may occur in 0.8% to 1.8% of formula cells in operational workbooks.

In a GxP-regulated environment, even a single broken formula can carry consequences well beyond administrative rework.

A spreadsheet rarely provides an automated, defensible record showing:

• Who changed a safety-stock target
• Why a yield assumption was modified
• When a forecast signal was overridden
• Which version supported a planning decision
• Whether the revised assumption received the appropriate review

Without this traceability, it is difficult to create a repeatable and audit-ready planning process.

There is also a significant continuity risk. If the individual who created and maintains the primary planning workbook is unavailable or leaves the organization, the company may temporarily lose the knowledge required to operate the planning cycle.

The issue is not that spreadsheets are inherently ineffective. It is that they are being asked to perform a role for which they were not designed: governing a complex, regulated and increasingly external manufacturing network.

Does structure mean losing flexibility?

A common concern is that specialized planning software will be too rigid to accommodate the daily exceptions planners handle in Excel.

That concern is understandable. Pharmaceutical supply planning rarely follows a perfect sequence. Batches slip. Yields vary. Quality releases move. Suppliers miss dates. Forecasts change.

Moving to a structured platform should not eliminate human judgment. It should give planners a safer environment in which to apply that judgment.

PLAIO combines automated constraint validation with a visual user interface and exception-management capabilities. Planners retain the ability to assess and adjust the plan, while changes are supported by structured data and an automated history.

The objective is not to automate the planner out of the process. It is to let planners spend less time reconciling information and more time evaluating options.

Rethinking the validation burden

Many pharmaceutical operations leaders recognize the risks created by spreadsheet-based planning but still defer implementing a dedicated platform.

One reason is the anticipated Computer System Validation workload.

Traditional enterprise software deployments often involved custom point-to-point integrations, significant infrastructure investments and extensive Installation Qualification, Operational Qualification and Performance Qualification documentation. Against that backdrop, continuing to manage the process in Excel can appear to be the lower-risk choice.

Modern software-as-a-service architectures change that calculation.

A specialized planning platform can sit alongside an existing ERP and connect through a documented integration contract rather than custom code. The ERP continues to maintain transactions, financial reporting and inventory records. The planning layer is validated for its defined intended use without requiring the organization to rebuild or revalidate the underlying system of record.

The original draft cites projected growth in the U.S. CMO and CDMO market from $83.1 billion in 2025 to $149.4 billion by 2032. As outsourced manufacturing grows, this layered architecture can provide pharmaceutical organizations with a more focused path to improving planning without destabilizing the transactional foundation.

Managing SaaS updates in a validated environment

Another concern is that routine cloud updates could disrupt the organization’s validated state.

This risk should be addressed through platform architecture, supplier controls and change management rather than treated as an unavoidable consequence of SaaS.

In the PLAIO model, the planning platform operates as a decision-support layer rather than the financial system of record. Its integration contract is versioned and pinned for each customer, so a platform release does not silently change the interface against which the NetSuite connection was validated.

This makes updates a controlled validation activity rather than a reason to avoid modernization altogether.

Three capabilities to expect from a modern planning platform

Moving beyond spreadsheets should not mean purchasing a more expensive generic data grid. A modern pharmaceutical planning platform needs to reflect the physical, regulatory and commercial rules that shape supply decisions.

Three capabilities are particularly important.

1. Connect commercial and supply commitments

In a spreadsheet-based environment, commercial forecasts, CMO commitments and raw-material lead times may be managed in separate files owned by different teams.

A modern planning engine brings those signals into one dynamic model. When an affiliate updates a forecast or an API supplier changes a shipment date, the effect should flow through the plan to packaging campaigns, inventory positions and customer orders.

This shared planning surface can also improve sales and operations planning meetings. Instead of reconciling competing files, commercial and manufacturing teams can evaluate a common set of current information and focus on the decisions that require attention.

This need becomes more important as pharmaceutical contract manufacturing continues to expand. The original draft cites projections that the market will exceed $200 billion by 2032.

2. Model real-world pharmaceutical constraints

A plan that assumes unlimited capacity, perfect yield and interchangeable inventory is not an executable plan.

Pharmaceutical planning must account for constraints such as:

• Country-specific remaining shelf-life requirements
• Minimum order quantities
• Batch-size and order-increment rules
• Supplier and production lead times
• Approved alternate components
• Manufacturing capacity
• Yield assumptions
• Quality-release timing

For example, one country might require 18 months of remaining shelf life at import, while another accepts 12 months. A purpose-built planning platform can apply those market-specific rules when matching available batches to demand, helping reduce rejected shipments and unnecessary expiration write-offs.

3. Evaluate scenarios quickly

When an API supplier reports a quality failure or a CMO cancels a packaging slot, leadership may need to assess several alternatives during a single S&OP discussion.

A modern planning layer allows the team to model scenarios such as:

• Moving a production run
• Switching to an approved alternate supplier
• Changing a packaging campaign
• Pulling a product launch forward
• Reallocating available inventory
• Prioritizing specific markets or customer orders

The platform can calculate the projected effects on capacity, inventory and on-time, in-full delivery performance. That speed allows S&OP teams to move from reactive reconciliation toward proactive risk management.

A practical diagnostic for your current planning process

Organizations do not need to wait for a major disruption to evaluate whether spreadsheet-based planning has become a liability.

Start with five questions.

1. How dependent are you on one person?

If the planner who built and maintains the primary workbook left tomorrow, could another team member run the next S&OP cycle without immediate training or disruption?

2. How much time goes into reconciliation?

Does the planning team spend more than 20 hours per month extracting reports, copying data, reconciling CMO emails and checking formulas?

3. Are shelf-life issues contributing to inventory losses?

Has inventory been written off because short-dated batches were not identified and allocated to an appropriate market in time?

4. How quickly can you model a disruption?

When a supplier delay occurs, can the team see the net effect on inventory and customer deliveries across the product portfolio in less than 10 minutes?

5. Can you demonstrate complete traceability?

Can the organization produce an automated record showing who changed a planning assumption, when it changed and why it changed for a GxP or FDA systems review?

If the answers reveal gaps in two or more areas, the workbook may have become an operational single point of failure. At that point, the risk of maintaining the current process may be greater than the effort required to modernize it.

From operational firefighting to proactive control

Moving away from spreadsheets does not need to be disruptive.

The transition is most effective when teams can bring forward the knowledge embedded in their existing planning process, map familiar information into the new environment and compare system recommendations with current methods.

PLAIO is designed to import existing spreadsheets, enabling planners to map current data structures and build confidence in the platform’s recommendations over time.

As trust develops, planners can spend less time locating attachments, checking formulas and coordinating updates. They can spend more time assessing risk, evaluating scenarios and advising the business.

If a global supply plan resides in a workbook owned by one person, the organization’s risk is distributed across inboxes, files and hard drives. Consolidating that process into a secure, traceable and controlled planning environment provides a stronger foundation for growth.

Sikich and PLAIO help life sciences organizations build that foundation without replacing the ERP systems they already depend on. Together, the teams combine life sciences advisory, NetSuite expertise, GxP validation support and pharmaceutical planning technology to help organizations move from fragmented planning toward greater visibility and control.

Book a 30-minute conversation with Sikich and PLAIO to explore how a modern planning layer could support your NetSuite environment and outsourced manufacturing network.