Companies are under endless pressure to uncover new avenues of value while balancing a conflicting and uncertain global supply chain. One potential solution? An enhanced Margin Optimization engine that enables organizations to simulate and align around margin growth as a core business strategy.

In the following, we’ve outlined how organizations can increase synergy between the business and sourcing strategies with forward-looking, intelligent market insights. With this cross-functional solution, companies that apply the right mix of data, visual analytics and AI models can deliver better decision making for predictive cost and margin analysis – saving time and money for a competitive edge and better stakeholder experience.

Industry gap

The challenge of delivering on a successful margin management strategy

For many organizations, it is a constant struggle to make sales at the right price for the best margin – especially under an ever-changing global economy. Consider this all-too-common scenario: for Product X, raw material costs have risen by 30 percent. Lead-times are extended by 60 days, which impacts manufacturing through increased planning, impacts to inventory and stock-outs. All these factors drive up costs. Simultaneously, a similar product from the competition is driving down price. To compete, the sales team must sell at historically low margins (e.g., 10percent) to win business.

With the necessary data and insights often spread between functions, individuals and unique software solutions, organizations face friction that slows down response times and negatively impacts margins in the process. Sales teams face an inability to set a pricing floor and struggle to stay competitive and profitable. But with so many competing factors, how can companies best align to reach better margins?

A next gen approach

Drive intelligent decision making with analytics

Despite the importance of margin management, there are few available solutions that can both provide insightin to costs and make intelligent recommendations for selling price. Most tools in the market can deliver one but do not consider the other. With data residing in siloed and disparate ecosystems, employees that enact margin management must do so manually and tediously, working between teams and creating delays at acost to business and effective collaboration.

Unencumbered by such issues, our vision fornext generation Margin Optimization includes a solution for data, modeling, scalability and alerts from a single source of truth approach.

Data

Aggregate costs (historical andpredictive), market indices and global economic fluctuations, and inventory supply and demand.

Modeling

Harness insights enabled by intelligent projections or recommendations.

Scalability

Scale to include all products and BOMs. Thesmart engine has the ability to continuously expand to new services and systems.

Alerts

Bring in real-time notifications to empower teams to take action at the best possible point.

Applying intelligence

A robust solution for cross-functional margin optimization

Today’s rapidly evolving technology landscape offers new solutions powered by intelligent, data-driven capabilities. At Aligned Automation, we have determined a new approach to margin optimization that enables rapid data-driven decision making around cost, selling price and overall competitiveness – all within one single source of truth.

Moving beyond simply aggregating data, the solution utilizes AI/ML to dive into cross-sections and create models that show how to maintain and scale margins in high-pressure environments. More than asales tactic or a procurement concern alone, Margin Optimization has the potential to become a cohesive and enterprise-wide strategic tool.

Use Case #1

Cost transparency & analysis

Stay competitive with leading technology. With numerous cost sources, it is impractical to rely on an even an expert human analyst to work through often thousands of data points at pace. Use the cost analysis tool to rapidly access historical data of raw material costs and their variations over time. The tool defines granular details around total costs at the Bill of Material (BOM) level with a view of planned vs. actual dollar value. External Market Index data points are then used to build the projections for the total cost at Finished Goods. View projections and moregranular reports based on that data to gain insight and make strategic decisions.

For example, users can isolate which raw materials consistently cost more – thereby hindering margins – and consider whether to find a new vendor or replacement raw material for the product. 

Use Case #2

Pricing optimization

Enable rapid and informed decision making for a pricing strategy based on favorable margins. With a deep view into historical and projected costs, access readily available data for pricing recommendations to be made within hours instead of days. With faster turn around times, sales teams can rapidly respond to inquiries and win contracts. For teams with readily accessible competitive data, the tool could also create amix model that strategically combines dynamic pricing with margin optimization.With this functionality, sales teams may be offered a target price range,allowing for competitive flexibility while still meeting margin goals.

Use case #3

Sales & operations insights

Gain deep insights into the supply chainfor Sales and Operations. Connect data between orders, inventory and procurement sourcing for high efficiency and high margin results. Teams can compare the number of orders against current raw materials, how much must be sourced, cost fluctuations and future projections. More than data visibility, the tool offers visual analytics to inform strategic decision making across the value chain.

Use case #4

Budgeting & forecasting

Accelerate highly accurate and strategic budget planning through the Budgeting tool, which integrates past, projected and actual budgets for a comprehensive view into an ideal budget scenario. Automated and smart technology reduce the risk for human error and the time necessary to compile recommendations.

Cross-functional integration advantages

Margin optimization is an enterprise-wide strategy, spanning across functions, including marketing, business development, procurement and asset management. The infographics below provide detailed scenario examples for how each function may benefit from access to Margin Optimization tools.

Procurement

Through the Margin Optimization Engine, procurement can analyze impact, such as supply chain shortages, within a few minutes and gain understanding of severity. This eliminates the need for SAP(COM/PLM) and continuous emails.

Consider this scenario:

Worldwide container shortages lead to significant cost increases in raw materials.

Through the MO Engine, teams can quickly understand impact on profitability of relevant finished goods.

As a result, time is saved by eliminating the need to request info from other functions.

Business Analysts

It can take >30-minutes to pull data for20 different finished goods. The Margin Optimization Tool extracts data in a manner of seconds, allowing analysts to do more high value work.

Consider this scenario:

Time is limited in SAP for analysis andother platforms, inhibiting collaboration.

MO Engine helps determine what is driving cost discrepancies in standard materials.

The data provides links from materials to finished goods & extracted data enables collaboration with Marketing.

Asset Manager

Inventory management is a common pain point across industries. In the case of monitoring materials closely, the Margin Optimization Engine allows asset managers real-time access to what is in stockand what can be used.

Consider this scenario:

In instances where there is a production issue or raw material issue, the MO Engine helps identify the problem.

It also provides enhanced visibility intothe standard value, as well as the actual usage of products.

Easy access to cost data saves asset managers significant time analyzing data.

Marketing Managers

The tool rapidly answers questions that lead to more informed decisions. The forward-looking features enables opportunities for cost savings when looking at historicals and predictions.

Consider this scenario:

• Raw material costs are increasing, but marketing is unsure how to capture changes.
• MO Engine opens options of cost positions across all suppliers.
• The tool provides information on which recipes were impacted, what is interchangeable and what was done historically.