With supply chain technology rapidly advancing in all sectors, it's easier to collect and analyse data. However, the more information a company accumulates, the more likely it will create bottlenecks in using this data.
This is known as a supply chain data silo. When this appears, analysing and collecting data becomes obsolete as almost nobody can review and use the information to make sound business decisions.
Despite even the best intentions of analysing and using all supply chain data, the issue remains that there is so much of it, and some are useful for specific supply chain stakeholders whilst some are more relevant to others.
What are supply chain data silos?
A supply chain data silo is a buildup of supply chain data that may or may not have been analysed but has been obtained. Meaning that whilst the data has been collected, it is either inaccessible or has not been reviewed.
A supply chain data silo occurs when a batch of information is only accessible by a specific organisation or department. Given the involvement of different parties, organisations often end up with various data sources that can be challenging to manage and sync with other teams.
Why do supply chain data silos occur?
When supply chain data is unreviewed, it can lead to more significant problems for logistics, retail, manufacturing, supply chain and transportation companies, ranging from lost business opportunities, revenue, or costly fees.
Inconsistent and incomplete supply chain data will lead to flawed decision-making and cause costly errors and delays to supply chains - thus causing a headache for suppliers and consumers.
For instance, the Natural Resources Defense Fund (NRDF) reportedly wastes 40% of food produced in the United States, costing approximately $218 billion annually. Part of the waste is due to a lack of data collection, which results in data siloing. What information is collected isn't reviewed, analysed, or shared with the right people in time for the NRDF to make better-informed decisions.
But this problem isn't only applicable to one industry sector. Supply chain data siloing is an issue across all supply chain sectors and heavily impacts logistics, retail, manufacturing and transportation companies.
Modern supply chains are under pressure to make reactive decisions on the spot, especially lately, concerning the COVID-19 pandemic and shipping lane bottlenecks, not to mention war and conflict in 2022. Thus, having correct information based on the accurate, current data available to supply chain stakeholders will mean the difference between a successful and failing supply chain business.
When supply chain data is unreviewed, it can create lost opportunities, revenue, and even expensive fees that will impact your bottom line. In addition to these losses, companies can inadvertently make poor business decisions without the proper information resulting in further damages.
There are four primary reasons that data silos occur.
1. Lack of an internal network
Companies fail to manage an internal network in which they can communicate between their departments. Numerous departments rely on different information to function. This information is kept in overlapping, often inconsistent records, resulting in significant inefficiencies.
Without a cohesive internal data network, departments make contradicting decisions, and poor choices are made, creating more data silos. Data continues to back up as more information is collected and left idle, worsening the silo.
2. Technical infrastructure does not scale with the company
When a company grows rapidly and fails to scale its infrastructure accordingly, departments collect data ad hoc. Without proper planning on how to scale, legacy infrastructure becomes overwhelmed and creates further supply chain data siloing. Not only does this slow data processing, but it can also create a significant backlog for data managers and IT.
3. Poor organisational structure
Restrictive access control systems contribute to poorly shared data amongst others who may need it. Whilst it is essential to protect your information, supply chain data must be accessible within the organisation to be shared and reviewed to prevent a silo. If team members cannot work together to move data, it will inevitably get caught up in a silo.
4. High interoperability between partners
Organisations don't wish to share all their data, so they create replicable data in case they need it for a piece of the supply chain journey. To do this, they make their own platforms and systems that do not integrate with other supply chain parties, thus building up more data that will go unused.
It is often the last point that is the most damaging yet the most likely to be remedied amongst supply chains. A standardisation of supply chain data is what is needed to avoid supply chain data siloing.
How to avoid supply chain data silos
The first step in avoiding supply chain data silos is preparing a strategy of reimagining how you want your supply chain, logistics, manufacturing, retail or transportation company to modernise.
Another way to help prevent data silos is by implementing supply chain management tools.
First and foremost is to collect and review the data you have. Although companies may believe you have too much, the more, the better.
Collecting data allows an organisation's decision-makers to better understand their industry and business. Supply chain parties must collect data during manufacturing, packing, transportation, and distribution processes.
This data will provide supply chain stakeholders with a holistic oversight of their organisation and sector, ensuring they can identify bottlenecks and determine which solutions are needed for each silo.
More data means more knowledge, enabling decision-makers to assess vulnerable areas and strengthen them.
Additionally, more data between departments and other parties can reduce miscommunication, or in other worse, ensure that the supply chain data is not duplicated and thus amended as it moves from one organisation to another.
So, whilst data collection is crucial, organisations must be collecting the correct data. Too much inaccurate or duplicated data builds up in the silo.
Once supply chain data is collected, stakeholders must analyse it and distribute the findings to the appropriate teams and partners. If this is not done, the supply chain data collection is wasted, causing a silo to develop. A solution to ensure delivery to the proper channels is using a supply chain management platform.
These platforms help companies collect data and distribute that data in real-time. By having data delivered immediately, companies optimise their processes from beginning to end. However, each company uses its own supply chain management platform; there is a risk of inaccurate data, inoperability and no standardisation of which data is the correct information.
Centralised data integration
Data integration is an alternative source of application integration and an equally beneficial avoidance of silos. All data will be shared and analysed across the company in a centralised data warehouse.
Data integration is beneficial in making all supply chain data accessible for analytics and business intelligence systems whilst preventing data silos. However, because all data is processed centrally, it does not eliminate the possibility of inaccurate or replicated data from other supply chain parties.
An optimal way to avoid supply chain data silos is through application standardisation. Application standardisation is the enabling independently designed applications to work together cohesively through one standardised protocol.
A significant contributor to supply chain data silos is the replication or contradiction of data sets, often caused by multiple sources of information from several parties. Once one organisation integrates its company's existing applications, its systems will verify that data is original and accurate and original, reducing the amount of unnecessary data that causes a silo.
One application standardisation method uses a blockchain protocol that facilitates a set of rules that all parties cannot amend. Companies can build their integrations and applications onto the protocol, only sharing the relevant data with different supply stakeholders along the supply chain journey, from manufacturer to consumer.
Addressing supply chain data silos
By addressing supply chain data silos, companies set themselves up for success. When a company can eliminate bottlenecks, ensure products arrive on time and in good condition and strengthen their bottom line, the company's overall health benefits.
Whilst not all companies can afford to fully automate their supply chain with advanced technology, keeping the status quo is costly. Even a frequent manual evaluation of your company's supply chain can save you time and money in the long run.
Remember that communication between departments through every supply chain step is the key to ensuring data silos don't harm your business.
Integrated silos positively impact supply chains
Managing silos is a real challenge facing supply chain stakeholders, manufacturers and logistics companies. Supply chains require a human and financial investment for companies. They can have irreversible consequences in case of error or delay. But when new technologies are created and integrations standardised for all its third parties, the risks are negligible, and the benefits are genuine.
Companies with an integrated supply chain increase their flexibility to adjust to client requests, competitors' actions, and events within the industry. They also reduce waste and lower costs. Overall, an integrated supply chain is gaining an advantage over the competition and tangible business benefits.