Managed data is the currency of success

The use of data impacts all aspects of supply chain, including inventory management, demand forecasting, logistics optimisation and supplier relations management.

But for data to be valuable, it must be clean, accessible and easily updatable. The absolute enemy of effective data management is silos, whereby data is stored in isolated systems or databases that make it difficult to share, access, or use said data effectively. Siloed data is the mother of inefficiency and missed opportunities.

If one department within a firm has access to certain data but others don’t, this might create a bottleneck in the supply chain – as if we need any more of those. 

To learn more about the problems of siloed data and how this can best be overcome, we asked an expert. Gregor Stühler is CEO and Co-Founder of Scoutbee, a global supplier intelligence tech provider. Here Stühler gives us the low-down on how businesses can leverage data to gain competitive advantage – and what they can expect to happen if they neglect the power of data.

How does access to data impact competitiveness?

Resilience is not ‘disaster response’. A company that is resilient is one that acts faster and better than its competition. If no company in the market is moving, you don’t need to move. But if they are moving – you must move faster and be smarter.

Every risk event brings the potential for a loss of market share. How you respond to these risk events determines your competitiveness. If a fast-moving consumer goods company experiences a disruption and can’t get its product to a retailer on time, they will lose shelf space to a competitor. This gives the competition a leg up and leads to missed revenue. Fast, reliable access to data and suppliers is crucial for successfully navigating disruptions and competing in the market.

How does siloed data affect upstream and downstream supply?

Data silos are an upstream problem. Upstream is related to strategic insights; downstream data comes from a contract-to-pay (C2P) system and can be operated independently from external sources. 

But companies need upstream data to strengthen downstream processes, as well as to develop proper negotiations and contracts, among other tasks. Clearer data at the downstream level alone, however, won’t significantly improve those processes if data silos are still blocking visibility at the supplier level.

Data gets siloed because it comes from hundreds of different systems, and in different formats. Companies can’t properly clean, normalise and render upstream data on their own to make it insightful and get a full picture of a supplier. It gets even more complex when third-party data is added to the mix.

Breaking down upstream data silos is a huge value driver for organisations. The visibility drives strategic supplier decisions. 

What are the main barriers to data transformation?

Unrealistic expectations. Breaking down silos is an urgent issue that can be solved with available technology, but cleaning data involves a considerable amount of hard work, yet people expect perfection on day one. But that’s too tall of an order. 

It’s a chicken and egg situation: you need to start somewhere. Make a habit of constantly using and cleaning data, then start using it to make decisions. Over time, your data will get stronger and the value you derive will grow exponentially.

How can you measure transformation success?

How fast companies realise the benefits of digital transformation depends on how they invest in – and train – their data. AI algorithms require vast amounts of trained data to drive value, which takes time. Every day that companies wait to build their data muscle, they fall farther behind.

Transformation success for downstream processes is easier to measure, as it usually relates back to the amount of time people save. The upstream impact is harder to measure but delivers much more powerful and strategic value, such as market competitiveness. 

From where does Scoutbee draw supplier data?

Our solutions draw from practically any data point and source that is relevant to organisations’ decision making. This includes: 

• Customers’ internal data and systems
• Third-party data
• Supplier websites
• Data available through supplier portals
• Scoutbee data based on tens of thousands of supplier scoutings
• Web crawlers that scour the Internet using ML models

Public data is very valuable, but it’s not what gives you strategic advantage. This comes from the combination of public data and internal data points. You then run deep analytics on that data to understand what is needed to optimise the supply chain.

How do you help customers tackle siloed data?

We provide a deep and holistic view of their suppliers, based on data that’s accurate, dynamic and enriched. We help customers find, extract and transform data, and then represent that as a knowledge graph. This graph uncovers hidden and complex relationships between entities, and enables procurement to make data-driven decisions, which drive the best outcomes for their business. It is highly flexible and new data points can be easily added as it becomes available. It’s not a one-off project, but a software solution that is constantly acquiring data.

Can businesses have data visibility without technology? 

Pre-digital, organisations would typically take one of two approaches: they would either tap into tech hubs in India, or hire interns to mine the data and create insights out of it. Neither approach is scalable or sustainable; the tech hubs and the interns are still both dealing with dirty data. They still have to aggregate, transform and accurately represent the data in order to run meaningful analytics.

The data pipeline issue is still there and prevents true visibility. With those approaches, it's impossible to draw deep conclusions in a short amount of time, which is detrimental in a risk scenario.