From ERP to Intelligent Operations: Planning, AI and Telemetry in the Modern Supply Chain

Introduction

For years ERP systems existed primarily to record financial and operational transactions. Today the competitive advantage is no longer how accurately a business records the past but how effectively it anticipates and shapes the future.

Modern mid‑market companies face enterprise level complexity: volatile demand, margin pressure, regulatory requirements and customer expectations for reliability. The result is that operational success depends less on processing transactions and more on making confident decisions ahead of time.

Forecast Accuracy as a Financial Lever

Forecast accuracy is often treated as an operational metric, but it directly affects financial performance. Over forecasting ties cash up in inventory and creates waste. Under‑forecasting leads to missed sales and customer churn.

Industry data discussed at the event showed that a five percent improvement in forecast accuracy can produce roughly a 3.3 percent improvement in bottom‑line performance. “Gartner states that for every 5% improvement in forecast accuracy, a company can see a 3.3% improvement to its bottom line.” 

This demonstrates that planning is not an operational exercise buta financial strategy.

ERP, Planning & Industry Context

ERP platforms such as Microsoft Dynamics 365 Business Central provide operational control and data integrity.

Industry solutions such as Aptean Food & Beverage provide contextual understanding of manufacturing and distribution realities including shelf life, traceability and supply chain constraints.

Together they enable decision quality data rather than simply historical reporting. The goal becomes alignment between demand, production and supply rather than reconciliation after the fact.

Understanding Telemetry

Telemetry is the continuous capture of behavioural data, about how a system and business processes operate over time.

Unlike traditional reports which describe what happened after completion, telemetry observes how work flows through the organisation while it is occurring.

In practical terms telemetry records patterns such as:

• Where transactions slow down

• Which processes repeatedly fail or require intervention

• How forecasts deviate from actual consumption

• Where operational bottlenecks appear

Telemetry therefore becomes a feedback mechanism between planning assumptions and operational reality. ERP records the transaction, planning predicts the outcome, telemetry validates whether the prediction held true.

Using Telemetry for Operational Intelligence

When organisations analyse telemetry they move from reactive troubleshooting to proactive management.

Operations leaders can identify delays before customers feel them, planners can detect bias in forecasts, and finance can see operational causes behind margin variance.

Instead of monthly post mortems, teams operate a continuous improvement loop:

Observe -> Understand -> Decide -> Execute -> Learn

Telemetry provides the observation stage that most ERP implementations historically lacked.

AI and Prescriptive  Decision Making

The event emphasised that AI delivers value only when paired with industry context. Generic analytics surfaces patterns and contextual AI explains causes and recommends actions.

By combining telemetry feedback with planning models, systems evolve from predictive to prescriptive:
Not only forecasting what will happen but advising what should be done about it.

Final Thoughts

The role of ERP is evolving from ledger to operational platform. Planning defines intent, telemetry measures behaviour and AI drives improvement.

Organisations that integrate these capabilities will not merely operate efficiently but will learn faster than competitors; the future advantage lies in operational intelligence rather than transactional processing.

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