Logistics and Big Data

Germán HerreroHead of Transport Sector

Research and Innovation, Atos Spain

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01/05/2023Big Data &Logistics

Big Data is not only about sizeData diversity matters

BIG DATA

TraditionalStructured

Data

+ =

BIG SIZE

SOCIAL

OPEN

REAL TIME

MULTIMEDIA

LINKED/SHARED

UNSTRUCTURED

“EXHAUST”

SIZE matters here, but, as in many other areas in life, there is more …

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01/05/2023Big Data &Logistics

The 3+ V’s of Big Data

▶ 1. Volume (lots of data Zettabytes)▶ 2. Variety (complexity, dimensionality)▶ 3. Velocity (fast data) +

▶ 4. Veracity (truthfulness, curation)▶ 5. Venue (location)▶ 6. Vocabulary (semantics)▶ 7. Variability …

From “Understanding Big Data” by IBM

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Nothing new under the Sun?

The concept IS NOT new, but technology and tools ARE

▶ …but having data bigger requires different approaches:– techniques, tools, architectures

▶ …with an aim to solve new problems– …or old problems in a better way.

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Potential

▶ 10% efficiency gain = 100 B€ Cost Savings (EU)[ALICE ETP “Alliance for Logistics Innovation through Collaboration in Europe]

▶ IDC at BDVA research agenda -Transport & Logistics ranked 3rd in spending in data products/services - 500 B€ Data Market

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Big Data potential

▶ Big data and advanced analytics are being integrated into optimisation tools, demand forecasting, integrated business planning and supplier collaboration & risk analytics at a quickening pace.

Source: Deloitte Supply Chain Talent of the Future Findings from the 3rd Annual Supply Chain Survey

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01/05/2023Big Data &LogisticsBIG DATA IN LOGISTICS

WHAT THE HELL IS FOR

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Big Data in Supply Chain management▶ Big data is providing supplier networks with greater data accuracy, clarity, and

insights, leading to more contextual intelligence shared across supply chains.

▶ The scale, scope and depth of data supply chains are generating today is accelerating, providing ample data sets to drive contextual intelligence. 

▶ Source: Big Data Analytics in Supply Chain Management: Trends and Related Research. Presented at 6th International Conference on Operations and Supply Chain Management, Bali, 2014

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01/05/2023Big Data &Logistics

Big Data in Supply Chain management▶ Big data is providing supplier networks with greater data accuracy, clarity, and insights, leading

to more contextual intelligence shared across supply chains.

▶ The scale, scope and depth of data supply chains are generating today is accelerating, providing ample data sets to drive contextual intelligence. 

▶ Plotting the data sources by variety, volume and velocity by the relative level of structured/unstructured data, it’s clear that the majority of supply chain data is generated outside an enterprise.

▶ Forward-thinking manufacturers are looking at big data as a catalyst for greater collaboration. Enabling more complex supplier networks that focus on knowledge sharing and collaboration as the value-add over just completing transactions. 

▶ Advanced analytics forecasting, demand planning, sourcing, production and distribution. And the benefits extend across the chain:– Real time issues can be resolved faster, leading to better customer and supplier relationships– Inventory control can be optimized– Assets can be used more efficiently– Supply chain security – illegal/fraud trade

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Big Data in Delivery

▶ Fleet managers are already using routing SW to provide drivers efficient routes to save gas and money– But there is still some slack…

▶ New techniques in geoanalytical mapping and fast analysis of millions of data points lend new meaning to the phrase “data visualization.” Instead of making piecemeal changes, teams of data analysts centrally monitor routing patterns and readjust entire networks

▶ Traceability are by nature data-intensive, making big data’s contribution potentially significant.

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Conclusions

▶ In the next years, Logistics will be defined by a massive increase in contextual data — from precise, up-to-the-minute weather forecasts, to door-to-door tracking across all oceans and remote territories of the planet– Heterogeneous amounts of data

▶ Novel application scenarios for increasing efficiency, sustainability and user-friendliness of transport and logistics services

▶ Relevance/Impact: high, as confirmed by IDC

▶ Challenges:– Appropiate business cases – Business aspects are key• set priorities, identify opportunities, and determine the value proposition• Fear of losing data from logistic stakeholders

– Right questions are as important as right answers– Data scientists in Logistics

Thank you

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