Data Silos in Manufacturing: Challenges, Prospects and Risks

In the dynamic landscape of the manufacturing industry, data is a powerful asset that can drive innovation, efficiency, and competitiveness.

However, this invaluable resource often finds itself trapped within the confines of data silos, presenting a complex mix of challenges, opportunities, and risks.

In this article, we focus on the intricacies of data silos, exploring how they shape the industry's landscape.

We’ll unravel the challenges they pose, reveal the opportunities they hide, and dissect the risks they pose in an era where structured data integration and intelligence are the cornerstones of success.

Join us as we navigate the fascinating intersection of manufacturing and data, where the key to progress lies in breaking down barriers and unlocking the full potential of information.

In the article, we’ll be:

• Defining data silos in manufacturing
• Outlining the challenges of siloed data
• Focusing on GDPR and the risks associated with data silos
• Explaining the benefits of reducing data silos and unifying customer data

What are Data Silos in Manufacturing?

Data silos refer to the isolated storage or segregation of data within different departments or systems within a manufacturing organisation.

These isolated data repositories often materialise due to various factors, including legacy systems, departmental boundaries, and data management practices.

In manufacturing, data is generated and utilised across various functions such as production, quality control, inventory management, supply chain, and more.

When data is stored in separate silos, it means that each department or system has its own database or data storage that isn’t easily accessible or integrated with others.

As a result, data within one silo may not be readily available or visible to other departments or systems that could benefit from it.

Challenges of Siloed Data

While it’s theoretically possible to conduct business using a variety of spreadsheets and databases, adopting such approaches opens the gateway for several challenges that inhibit business performance.

Let’s explore some of the challenges which often manifest when working with siloed data.

Low Visibility of Supply Chain, Prospects and Customers

Siloed data in the manufacturing industry can impede the ability to gain a comprehensive view of the supply chain, prospects, and customers. This leads to a lack of visibility into critical aspects of manufacturing operations.

Supply Chain Visibility

When information related to inventory management, production scheduling, and supplier relationships are segregated into data silos, it can have a detrimental effect on supply chain visibility. This, in turn, poses significant challenges in effectively managing and optimising the supply chain.

For instance, inventory data stored separately may result in inaccuracies in stock levels, potentially leading to overstocking or understocking issues.

Additionally, without real-time access to demand forecasts, procurement data, and work capacity, efficient production scheduling becomes difficult.

Misalignment in Sales, Marketing and Customer Service

Sales, Marketing, and Customer Service all work with customer data. When this information is managed separately in each team, it puts a dent in delivering a seamless customer experience.

So much so that, according to LinkedIn, 60% of global respondents in a survey believed that misalignment between Sales and Marketing could damage financial performance.

For instance, if sales and marketing are working on a campaign, the representative who is reaching out to prospects should have access to the latest marketing insights. But if they don’t, it’s difficult for the salesperson to understand the context in which the lead was acquired and, therefore, won’t have full visibility on previous communications with marketing.

If the latest customer data isn’t widely available across all departments, it impacts the organisation's ability to understand customer behaviour and preferences, limiting opportunities for personalisation marketing and customer retention.

Moreover, when customer service representatives lack integrated access to historical customer data, it leads to inefficient issue resolution and customer frustration.

Operational Inefficiencies

Operational efficiency is another area affected by data silos. It’s difficult to generate accurate reports and analytics for informed decision-making when data is fragmented.  

Looking through reports from incomplete data sets poses several risks for organisations. It can lead to inefficient resource allocation since departments lack visibility into each other's activities. For instance, production may not align with sales forecasts.

Data inconsistencies and errors are common when different departments maintain separate records. But the cost implications that it can cause from order and delivery delays to financial reporting errors, will be an unwanted lay of complication for manufacturing businesses.

Additionally, the limited visibility into trends, opportunities, and potential issues due to data silos can result in missed opportunities for cost savings, process improvements, and revenue growth.

Reduced Cross-Sell/Upsell Opportunities

Data silos in the manufacturing industry can significantly hinder cross-selling and upselling opportunities. They create barriers to accessing comprehensive customer information and prevent companies from coordinating strategies effectively.

This is especially the case for Sales and Customer Success teams, who need to access the same customer data.

However, data silos mean they only have access to partial customer profiles, missing essential details such as purchase history, preferences, or interactions with other departments.

Therefore, identifying cross-selling or upselling opportunities becomes challenging without a holistic view of the customer journey.

With 99% of marketers saying personalised campaigns help advance their customer relationships, companies need to take advantage of the customer data they have to deliver this type of experience.

But, if data is not readily available, marketing teams will find it challenging to tailor their campaigns to existing customers' needs or preferences. This can result in missed opportunities to suggest complementary products or services that align with customer needs.

With cross-selling in manufacturing often arising when customers purchase products that complement what they already have, siloed data can prevent you from identifying patterns of triggers that will segue into add-on sales opportunities. This is likely due to the relevant sales data being isolated from marketing or customer service departments.

Moreover, departments working in isolation may not effectively collaborate on cross-selling or upselling strategies. For example, the Sales team might not be aware of special promotions or bundled offerings that the marketing team is running, which leads to missed opportunities.

Inconsistent communication can further exacerbate the issue. Customers may receive inconsistent messages or offers from different departments, causing confusion and potentially causing them to overlook cross-selling or upselling possibilities.

To overcome these challenges and enhance cross-selling and upselling opportunities, manufacturing organisations should prioritise breaking down data silos and implementing integrated data management systems.

This involves integrating data from various departments and systems to create a unified customer view, utilising advanced analytics to identify opportunities, fostering cross-functional collaboration, implementing robust CRM systems, and personalising marketing messages and recommendations based on individual customer data and behaviour.

By addressing data silos and fostering a more collaborative and data-driven approach, manufacturing companies can unlock greater potential for cross-selling and upselling, ultimately benefiting both the organisation and its customers.

Inability to Track Attribution

Data silos in the manufacturing industry can interfere with the ability to effectively track attribution.

Firstly, manufacturing companies generate data from multiple sources, including production, sales, marketing, and supply chain. When companies use siloed data, it becomes challenging to connect and analyse these separate data points to understand how different touchpoints contribute to specific outcomes, such as a sale.

Furthermore, data integration is often lacking in siloed environments. This absence of integration makes it difficult to link customer interactions across different stages of the sales and marketing funnel.

Consequently, manufacturing firms may struggle to attribute sales or other outcomes to specific marketing campaigns or customer interactions if data from these activities is isolated.

Another issue arises from the limited visibility into the customer journey. Siloed data restricts access to the data that tracks customer interactions from the initial contact through various touchpoints to the final purchase decision. This makes it difficult to what interactions or marketing campaigns led to the eventual sale.

In addition, analysing siloed data can be cumbersome and time-consuming. Manufacturers may lack the tools and processes necessary to consolidate data from various departments and systems effectively. This can result in delayed or inaccurate attribution analysis.

Moreover, data silos may prevent the implementation of advanced attribution models. These models consider multiple touchpoints and interactions in the customer journey to assign attribution accurately. Siloed data will lead to less accurate attribution models that fail to capture the complexity of customer interactions.

The consequences of these challenges are significant. Manufacturing companies may make inaccurate decisions due to their inability to track attribution effectively. This results in inefficient allocation of resources missed opportunities for optimising strategies, and challenges in providing a seamless and personalised customer experience.

To address these issues and enhance attribution tracking, manufacturing companies should prioritise breaking down data silos and implementing integrated data management solutions.

This entails integrating data from various departments and systems to create a unified view of customer interactions and touchpoints, implementing advanced analytics and attribution modelling, fostering collaboration between departments, and investing in appropriate technology and tools for efficient data consolidation and analysis.

By addressing data silos and enhancing attribution tracking, manufacturing firms can gain valuable insights into customer journeys, optimise marketing efforts, and make data-driven decisions that drive growth and efficiency in their operations.

GDPR and the Risks Associated with Data Silos

Data silos can pose significant risks in the context of the General Data Protection Regulation (GDPR).

These can have serious legal and financial consequences for organisations, especially UK organisations.

Having an all-in-one suite such as HubSpot can support removing siloed data, protecting teams, and businesses, and avoiding associated risks, including:

Data Inaccuracies and Incompleteness

Siloed data often leads to inconsistencies and gaps in the information held by different departments.

Under GDPR, individuals have the right to access their data and have it corrected if it's inaccurate or incomplete. Siloed data makes it challenging to maintain accurate records and respond promptly to data subject requests, potentially resulting in non-compliance.

Data Security and Breach Response

GDPR requires organisations to implement appropriate security measures to protect personal data from breaches.

However, when data is fragmented, it is difficult to implement comprehensive security protocols and timely breach response strategies across the entire organisation.

This can lead to delays in reporting breaches to the Information Commissioner's Office (ICO) and affected individuals, potentially resulting in GDPR fines. 

Consent Management

GDPR mandates that organisations obtain clear and informed consent for processing personal data, and individuals have the right to withdraw their consent at any time.

Data silos can harm a business’s ability to track and manage consent across all systems and departments, making it difficult to ensure compliance with consent-related GDPR requirements.

Data Portability

GDPR grants individuals the right to request the transfer of their data from one organisation to another.

Siloed data can obstruct the seamless transfer of data between departments or systems, making it challenging to fulfil data portability requests within the specified timeframes.

Subject Access Requests (SARs)

Under GDPR, individuals have the right to submit SARs to access their data. Siloed data can result in delayed or incomplete responses to SARs, as the relevant data may be spread across various systems or departments. This can lead to GDPR non-compliance and potential fines.

Data Protection Impact Assessments (DPIAs)

When processing personal data for high-risk activities, organisations are required to conduct DPIAs to assess and mitigate data protection risks.

Siloed data can hinder the comprehensive assessment of data protection risks, potentially resulting in inadequate DPIAs and non-compliance with GDPR requirements.

Data Minimisation

GDPR emphasises the principle of data minimisation, which means organisations should only collect and retain personal data that’s necessary for the intended purpose.

Siloed data may lead to data redundancy and over-retention, violating the data minimisation principle and exposing organisations to GDPR non-compliance risks.

To mitigate these GDPR risks associated with siloed data, organisations should prioritise data integration and centralisation efforts.

By implementing unified data management strategies and systems, organisations can enhance their ability to manage and protect personal data effectively, ensuring compliance with GDPR and reducing the potential for fines and legal repercussions.

Benefits of Reducing Data Silos and Unifying Customer Data

Organisations invest in data integration and analytics solutions to break down these data silos.

This involves creating a unified data environment where data from different sources and departments can be integrated, analysed, and shared across the organisation.

Breaking down manufacturing data silos can lead to improved efficiency, data accuracy, and better decision-making in the manufacturing process.

Complete Visibility Over Multiple Data Sets/Companies

Unifying customer data and disassembling siloed data within the context of managing multiple data sets or companies offers a broad perspective that would otherwise remain fragmented. It involves centralising data into a single repository, where information from various sources is organised cohesively.

This central repository facilitates the creation of holistic customer profiles, containing a 360-degree view of each client, including their interactions, preferences, and purchase history across different data sets or companies.

Moreover, it supports the correlation of data across various entities, allowing connections between customer behaviours and interactions in different aspects of the business to become clear.

Various benefits can be attributed to accessing and analysing data from different sources, including:

• Cross-sell and upsell opportunities.
• Streamlined marketing efforts.
• Improved analytics.
• Optimised resource allocation.
• Regulatory compliance.
• Enhanced customer service.

This leads to more informed decision-making and a more customer-centric approach. Ultimately, this approach enhances competitiveness, customer satisfaction, and data security.

Clear Map of Supply Chain and Existing Relationships

Consolidating data from various sources and breaking down silos helps manufacturing companies create a centralised data hub that serves as a comprehensive repository. This hub houses critical information related to customers, suppliers, production, inventory and logistics, allowing for a unified view of the entire supply chain.

Additionally, with all the data stored centrally, you have a comprehensive view of your customers, suppliers and other stakeholders involved in the supply chain.

This includes entire logs of interactions, transactions, and engagement across different aspects of the business, giving you a clear understanding of each person’s role and relationships within the supply chain.

With data stored centrally, it becomes possible to map interactions across various touchpoints, including tracing the flow of materials, products and information throughout the supply chain.

Furthermore, integrated data provides a foundation for advanced analytics and supply chain optimisation. This means manufacturers can attain insights into supply and demand patterns, lead times, inventory levels, and supplier performance. Having a holistic view of your data allows for better decision-making and enhances overall supply chain efficiency while minimising disruption.

A clear map of relationships and interactions enables manufacturers to identify bottlenecks, inefficiencies or potential disruptions in the supply chain and take timely corrective actions to mitigate risks.

As for supplier relationship management, manufacturers can track supplier performance on both production and procurement to identify solutions to optimise them.

As mentioned previously, siloed data makes GDPR compliance challenging. However, the introduction of centralised data management streamlines compliance with these regulations and ensures your data handling practices are consistent and transparent across the supply chain, reducing compliance risks.

Centralising both customer and supplier data and removing data silos in the manufacturing industry, offers a consolidated view of the supply chain and existing relationships.

This helps you make better strategic decisions in terms of sourcing, production planning, inventory management, customer engagement as well as enhancing supplier relations.

Map The Entire Customer Journey

By centralising customer data, manufacturers gain a holistic perspective of customer interactions, preferences and behaviours across different touchpoints right from initial engagement with a product or service to post-purchase support and feedback.

Armed with this information, manufacturers can identify trends and patterns in customer behaviour. Insights gained from this analysis help in tailoring products, services and marketing strategies to align with customer preferences and anticipate their evolving needs along the journey. They also pinpoint key moments of engagement, identify pain points, and recognise opportunities for improvement throughout the customer journey.

Plus, when manufacturers have access to real-time data integration, they can respond promptly to changing conditions and provide agile customer support throughout the entire journey.

Furthermore, when different departments can access and analyse the same data, it helps to nurture a collaborative environment to enable teams to work cohesively at every stage of the journey.

This comprehensive understanding empowers manufacturers to provide a seamless and personalised customer experience, optimise their operations, and make data-driven decisions that enhance customer satisfaction and competitiveness.

Make data-driven decisions

As mentioned, by consolidating data from various sources and eliminating data silos, manufacturers gain a comprehensive view of their customers. This includes understanding customer interactions, behaviours, preferences, and history across different touchpoints. This knowledge serves as a solid foundation for informed decision-making.

Integrated data ensures that analytical processes are based on a complete and accurate dataset. This accuracy is essential for generating meaningful insights and making reliable predictions. Data silos can lead to incomplete or inconsistent data, potentially resulting in flawed analytics and suboptimal decision-making.

Unified customer data allows companies to identify trends and patterns in customer behaviour. By analysing data across the entire customer journey, businesses can uncover valuable insights into what drives customer actions, such as purchase decisions. These insights allow companies to adjust their strategies to align with customer preferences and market dynamics.

Removing data silos helps companies personalise their interactions with customers. By understanding individual preferences and past behaviours, businesses can tailor marketing messages, product recommendations, and customer service interactions. This level of personalisation enhances the customer experience and drives more profitable results.

Aligning data often involves real-time or near-real-time data integration. This means that companies can access the most up-to-date information about customer interactions and market trends. Real-time analysis enables businesses to respond swiftly to changing conditions and make timely decisions.

Unified data promotes cross-functional collaboration within an organisation. When departments have access to the same data, teams can work together to interpret insights and develop strategies collaboratively. This collaborative approach results in well-rounded decisions that consider various perspectives.

Data-driven decisions help allocate resources more efficiently. By analysing customer data, companies can identify areas where investments yield the highest returns. For example, marketing budgets can be allocated to channels that generate the most leads or sales.

Unified data enables better risk assessment and mitigation. By analysing customer data, companies can identify potential risks and develop strategies to mitigate them. This proactive approach reduces the likelihood of costly setbacks.

Aligns teams

Reducing data silos and unifying customers helps manufacturing companies align their teams. The process fosters a shared understanding and collaborative approach across the organisation, promoting team alignment in several key ways.

• Access to shared data: Customer data provides all teams with a comprehensive view of customer interactions, preferences and behaviours. This shared understanding of customers helps teams align their efforts to meet customer needs and expectations consistently:

When teams access the same information from a common data source, it eliminates discrepancies. This fosters trust among teams since everyone is relying on the same accurate data for decision-making.

• Better Communication: When teams have access to the data, communication between departments becomes more efficient and effective. Marketing, sales, production, and customer support teams can exchange insights and feedback based on a shared understanding of customer needs and challenges.
• Efficient workflow: Teams can streamline processes when they have access to unified data. For instance, sales and production teams can better coordinate inventory levels and manufacturing schedules based on real-time customer demand data.
• Consistent customer messaging: Marketing and sales teams can ensure consistent messaging and personalised customer interactions by using unified data. This alignment in messaging enhances the customer experience and builds trust with customers.

Unified data encourages data-driven decision-making across teams. When everyone has access to the same data, decisions become more transparent and are based on a shared understanding of customer insights and market dynamics. Plus, teams from different departments can collaborate seamlessly and allocate resources more efficiently on initiatives that require a multifaceted approach, such as launching a new product or entering a new market. 

Embrace Data-Driven Practices and Prepare for the Future

In the ever-evolving landscape of the manufacturing industry, data silos emerge as formidable obstacles, laden with risks and challenges that can impede progress.

However, using a CRM system such as HubSpot can transform these challenges into exciting opportunities.

By breaking down these silos and embracing the power of unified data, manufacturing companies can mitigate risks, unlock new avenues for innovation, and streamline operations.

While it may initially seem challenging, adopting a clear vision and demonstrating a commitment to data integration can help companies navigate these obstacles and emerge stronger, more agile, and better equipped to thrive in an increasingly data-driven world.