August 23, 2024 Data Fuels Chip Manufacturing Market Success

Semiconductor manufacturers must improve demand forecasting, channel management, and pricing strategies to succeed in the volatile market.

Global semiconductor sales are surging, but more than 40% of industry leaders believe the market currently has or will have excess chip supply by the end of the year. Manufacturers must walk a fine line to balance supply and demand, which is no small feat in this volatile market.

According to Model N’s 2024 State of Revenue Report, executives at chip manufacturers said customer demand is one of the top variables impacting innovation this year. To brace for market fluctuations, nearly half of companies are focusing on process efficiency and cost reduction, compared to just 10% prioritizing product innovation.

The semiconductor industry faces economic pressures across the manufacturing lifecycle. Companies need the right tools and channel management strategies to optimize revenue in today’s market. Semiconductor manufacturers should improve demand forecasting, enhance pricing strategies, and build collaborative channel relationships.

Advanced analytics improve demand forecasting

Demand forecasting is especially difficult right now due to rapid technology advancements, complex and unpredictable supply chains, geopolitical and economic uncertainties, and dynamic customer needs. Manufacturers have countless variables to consider, from government regulations and interest rates to historical sales and current pricing structures. This data exists in disparate locations. Deciphering trends manually requires significant time and effort and often results in delayed or incomplete analyses that hinder forecast accuracy and company agility.

Integrating systems creates new opportunities for data and analytics to improve demand forecasting. Nearly 7 in 10 companies in the Model N survey plan to invest in advanced analytics for revenue management. When manufacturers can collectively evaluate all independent variables, they unlock powerful new insights to improve predictions.

Advanced analytics allow manufacturers to automate forecasting calculations. These algorithms handle large and complex datasets for a comprehensive view of demand drivers. Advanced analytics platforms use predictive modeling to identify even subtle market trends. These solutions streamline forecasting and enhance insights for production, pricing, R&D, and sales strategy development.

Use software to optimize channel management

Semiconductor manufacturers derive a large portion of their revenue from channels, yet many lack the necessary tools to manage channel revenue processes. Large channel ecosystems and vast product catalogs coupled with short product life cycles and numerous transactions make manual engagement impractical. As a result, companies face difficulties generating accurate and timely quotes, preventing overpayments, managing inventory, and gathering clean data.

Channel management software removes the complexities of working with the channel by automating many manual processes needed to manage an extensive partner ecosystem. With these platforms, companies can efficiently and effectively execute all aspects of the pricing lifecycle, including channel operations, incentive management, and sales execution.

These solutions also enhance channel relationships by standardizing channel partner communication and creating transparency. Manufacturers can collect additional data attributes beyond point-of-sale and inventory to better understand end-customer behavior. This information illuminates a more complete picture of the market, enabling faster and more strategic sales pivots, such as targeted incentive programs. A comprehensive incentive strategy strengthens channel relationships, encourages product prioritization, supports partner success, and increases sales. Being able to adjust incentives to market changes drives better performance.

Integrate data for better price management

Chip manufacturers must balance prices based on production costs, competition, market demand, order volume, and revenue goals — all of which change constantly. The right pricing strategy allows companies to hit margin targets while remaining competitive. The optimal pricing structure today will not look the same a year or even a quarter from now.

Manufacturers need sophisticated, dynamic pricing strategies to close deals and maintain profitability. Established list prices create a standardized pricing structure, but no one actually pays list prices. Businesses typically offer some combination of incentives, volume discounts, and rebates based on customer memberships and affiliations, size, pricing tiers, current agreements, and past performance. The result is a highly complex contract portfolio.

Amid this complexity, manual processes hinder effective quotes and contract execution. Spreadsheets often contain outdated or incorrect information, resulting in inaccurate quotes, and manually sorting through all the information leads to costly delays in quote approval. Additionally, using spreadsheets to build invoices for sophisticated contracts often generates unwanted billing and rebate payment errors.

Effective pricing requires channel, sales, and contract data, which often exist separately. Manually gathering this data limits the intricacy of pricing structures, leading to missed business opportunities. Model N’s survey revealed that only 27% of high-tech executives consistently use channel sales data to inform price management decisions.

Revenue management software removes pricing hurdles by automating data gathering and analysis. Finance and sales teams can create data-backed, segmented, and customized pricing guidelines to accelerate quote approvals and negotiations.

Once a manufacturer has consolidated the relevant data, machine learning can empower proactive adjustments to meet market conditions, identify strategic opportunities, and calculate the long-term impacts of a pricing strategy. In today’s competitive market, AI-powered price management gives manufacturers a significant business advantage.

The key to success is data. Automated data gathering and integration enable access to all critical information elements, and advanced analytics derive maximum value from the information. By leveraging data for demand forecasting, channel management, and pricing strategies, semiconductor manufacturers give themselves the necessary insight and agility to conquer the market.

About the Author
Gloria Kee is the Vice President of Product Management at Model N. For 15 years at Model N, Kee has spent her time focused on product management and with an in-depth understanding of implementing and designing innovative software across a variety of business challenges. She is committed to product innovation and development in the B2B space within the High Tech Industry.

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