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Seges

From data to business-critical insights

Effective data exploration with Watson

As many large organizations, SEGES struggled to get a complete overview of their data and how it is interlinked. Another challenge was to break the silo-thinking, forcing different stakeholders to join forces in finding the insights they could actually use. 

Bringing together field experts from across the organization, asking the right questions, and knowing how the technology works, allowed us to find the business-critical insights we were searching for. 

Industry:

Manufacturing

We delivered:

Digitalization advice

Technology:

Data insights, Digital transformation, Internet of things

The challenge

Agriculture is a global industry today, challenging farmers to reinvent their business to become more profitable and efficient than ever before. SEGES is owned by Danish farmers and is focused on driving innovation processes to secure the competitiveness of Danish agriculture.

SEGES collect massive amounts of data, containing detailed information about all aspects of Danish agriculture. Connecting data in the right way holds a huge and business-critical potential and can give Danish farmers a global competitive advantage. 

Data exploration: A search across organizational siloes

SEGES and Mjølner teamed up to explore the business potential hiding in SEGES’ organizational siloes of existing data. 

As many large organizations, SEGES struggled to get a complete overview of their data and how it is interlinked. Another challenge was to break the silo-thinking, forcing different stakeholders to join forces in finding the insights they could actually use. 

Bringing together field experts from across the organization, asking the right questions, and knowing how the technology works, allowed us to find the business critical insights we were searching for.

A focused approach and the use of Watson Analytics made it possible to visualize and spot trends in the data quickly. 



“The fact that we cannot give a 360-degree advice regarding a specific farm or an industry challenge, just because we do not know what data we have across the organization, is unacceptable in 2016. With Mjølner’s approach to data exploration and Watson Analytics, we were able to get really far in overcoming this challenge.”

Peter Enevoldsen, Head of Department, SEGES IT

Just ask!

It is no joke that we call this process data exploration. The only way to find out what insights your data is hiding is to find the questions you want answered and start asking. 

You need to make qualified guesses about which data could influence the questions you wish to answer. From here, it is an iterative process: Sorting out parameters and trying out new ones and so on. 

Start by asking some of the questions that already exist in the organization but are only answered by gut feeling – not facts. Gut feeling are often well put, other times they are simply wrong or different from the initial impression. Start by challenging some of your standard perceptions. 

Climate effects the milk production profits

By exploring SEGES’ existing data across organizational siloes, involving specific stakeholders, and asking the right questions, we were able to create business-critical insights. Insights that strengthen SEGES’ position as a leading agricultural advisor. One question we found and answered was this one:

  • How does climate and temperature affect the profits on milk production?

To answer the question, we needed information about milk, geography, weather, etc. With organizational and technical understanding and the use of Watson Analytics, we were able to connect the necessary data and present it visually in a short amount of time.

SEGES now has the insights on how climate parameters inflict the quality of the milk. These insights enable SEGES to provide Danish farmers with even better counselling and hereby help farmers stay competitive and economically viable.

PLUG ‘N’ PLAY? WE ARE GETTING THERE

In spite of what many analytics software vendors might tell you, the process of collecting data and refining it is still mostly manual. 

With SEGES, we went through a regular ETL (Extract, Transform, Load) process. Close collaboration with field experts was essential to get data coupled right, enabling us to answer questions in a new and better way. 

The Client

SEGES is owned by Danish farmers and is focused on driving innovation processes to secure the competitiveness of Danish agriculture. SEGES collects massive amounts of data, containing detailed information about all aspects of Danish agriculture. Connecting data in the right way holds a huge and business-critical potential and can give Danish farmers a global competitive advantage.

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