Building Success: Using CRM to Improve Manufacturing Demand Forecasting

Building Success: Using CRM to Improve Manufacturing Demand Forecasting

WHAT WE'LL COVER:

The Manufacturing Industry: Taking a Look Under the Hood

According to our most recent survey , 59% of manufacturing enterprises struggle with the lack of accurate data in manufacturing demand forecasting with 37% having difficulty integrating data from multiple sources. In comparison, 30% of the respondents identify the high cost of adequate technology and tools as the main impediment in effectively carrying out demand forecasting tasks. While sales forecasting can pose challenges regardless of the industry, manufacturers struggle with this aspect more than the average enterprise because of the complexity and length of the sales cycles and the multitude of tech solutions used daily to operate. However, many demand forecasting struggles can be counteracted with the help of a robust CRM and, ideally, a seamless integration between legacy ERPs and new CRM solutions.

4 Modern Issues Manufacturers Face

Demand Forecasting Challenges

However, accurate sales forecasting is critical for manufacturing enterprises, as future sales projections can serve as a starting point for making correct decisions about production volumes, adapting to buyer preferences, and market evolution. To overcome demand forecasting challenges in manufacturing, we first need to understand the most prominent bottlenecks enterprises in the field struggle with.

1. The Spreadsheet Reign

According to our most recent survey, 77% of the respondents claim they are struggling with the company-wide use of spreadsheets, which doesn’t allow them to carry out effective sales forecasting. Many have argued that this tends to happen because many enterprises have a history of using such systems and solutions. They even go as far as outsourcing ERP data into spreadsheets and using the spreadsheets as a reference.

2. Lack of Executive Support and Training

Organizational change is almost impossible when met with a lack of executive support and initiatives. For companies to switch from legacy spreadsheet-based systems to modern, robust solutions, a significant proportion of the decision-makers and stakeholders within the organization must champion such projects. In this case, the lack of support is mainly caused by reluctance regarding the effectiveness of CRMs and CRM & ERP integrations.

Many salespeople also have advanced spreadsheet manipulation skills and less experience navigating modern tech solutions, so they think their old approaches are more effective. However, proper training and support can quickly overcome this impediment, especially if companies carefully select their CRM and ERP vendors.

3. Lack of Budget Allocated to Tech Stack Enhancements

Spreadsheets are virtually free of cost, so for many enterprises in the industry, justifying such expenses doesn’t come easy. It’s not just about the ROI; it’s also about the perceived time it takes to implement and adopt CRM solutions. In reality, spreadsheets lack the capabilities of a CRM product in terms of demand forecasting capabilities and accuracy, posing risks when it comes to revenue generation and data-backed strategic decisions.

After all, some of the biggest challenges demand forecasting poses are human error and bias . The best way to overcome bias and human error is to rely more on CRM and ERP data and less on educated guesses and spreadsheets.

Sales Intent Data & Demand Forecasting, Critical for Manufacturing Growth

Sales intelligence tools have recently gained attention from many enterprises, including manufacturing. According to this data , in 2023, almost 43% of salespeople claimed they used sales intelligence tools and intent data in their processes. The sales reps use in their endeavors the following data sets:

  • Customer buying patterns
  • Customer behavior
  • Customer preferences

It comes as no surprise that these data sets are usually hosted within CRM tools. A lack of proper insights into this data (and back-office data to correlate it with) is damaging manufacturers’ ability to make accurate projections about sales and demand.

But why is having a seamless connection between your ERP and CRM solutions nowadays seen as the holy grail of manufacturing success? It can completely change how organizations carry out their operations, from demand forecasting to supply chain management and customer success.

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Sales Intent Data

Sales intent data is one of the biggest game-changers we have recently witnessed in the business landscape. With this CRM data, sales teams have access to what products in their portfolios raise their accounts’ interest, as well as contact info from key people within the targeted organizations. Such capabilities allow enterprises to quickly spot where legitimate interest is shown by their accounts, proactively engage with them, and act upon their level of interest. But where does this data come from?

  • First-party data: data from your company’s channels, such as email, form fills, and website analytics, (all hosted by your CRM) designates first-party intent.
  • Second-party data: data that originates from secondary sources that are related to you. Think of a review website where you have an official profile. These data sets designate second-party intent.
  • Third-party data: Here, we can mention all sorts of data sources, such as ads, web search results, and so forth. These data sets designate third-party intent.

It’s worth mentioning that in the presence of advanced tools and applications, companies have also shifted their strategies from purely transactional to customer-focused strategies. CRM-generated intent scores are critical in such scenarios because, with the help of AI, they offer a clear overview of which accounts are most likely to convert, boosting conversion rates and lowering manual labor. Intent data is also the cornerstone of accurate demand forecasts, allowing you to investigate legitimate interests, identify trends, and plan for the future.

Demand Forecasting

With the help of advanced analytics capabilities, such as predictive analytics and data sets corroborated from both ERP and CRM systems , manufacturing enterprises can increase the accuracy of their demand forecasting projections.

In the context of complete data, companies can predict market evolution, proactively adapt their strategies, and incorporate risk reduction measures as they identify unfavorable market dynamics.

Once CRM and ERP data is collected and cleansed, enterprises can investigate demand forecasting models that match their own scenarios and needs.

Wrapping It Up

Although manufacturing growth is conditioned by a series of external factors, companies that leverage modern technological solutions (sales force automation, revenue intelligence, and sales enablement tools) seem to have a competitive advantage in the face of companies that rely on outdated business models. Fortunately, with just CRM and ERP integrations available, enterprises have been proven to operate more efficiently, spot market trends and evolutions on a whim, and reduce risk significantly, thanks to access to large data volumes from complete and complex internal and external sources.

Modern tech solutions allow enterprises to track customer interactions across all channels, whether social media, email, phone, or even video call conferences. This gives companies accurate insight into customer sentiment and conversion likelihood.

CRM tools equipped with predictive analytics offer access to accurate internal data and account for external information gathered through multiple channels, helping businesses generate even more accurate forecasts and pertinent strategic decisions.

If you’re curious to learn more about how CRM solutions can help your manufacturing business thrive in competitive markets, download the full report by The Manufacturer & SugarCRM: Unlocking Manufacturing Growth: Harnessing Accurate Sales Forecasts for Profitability and Competitive Edge , or for a more condensed, bite-sized version, the Infographic .

by Mihaela-Cristina Chiurtu

Originally published on SugarCRM .

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