Symrise

Tasting sweet success in eliminating workflow inefficiencies and improving business decisions with IBM SPSS
Situation: 

Comprising of two major divisions, Scent & Care and Flavour & Nutrition, Symrise is one of the top 5 companies in the global flavours and fragrances market. With impressive research and development capabilities, it transforms inspired concepts into market reality. Symrise not only combines science and sensation; it maximizes synergies in business and capabilities to deliver outstanding customer service through consumer insights knowledge.

Research and development forms a key part of Symrise’s operations. Yet clients’ needs differ greatly from country to country and region to region. In order to help clients anticipate, surprise and delight their customers, Symrise needs to tailor its products to its clients’ needs, depending on the geographical markets that the client chooses to tackle.

Challenges: 

To achieve this, Symrise had a few key concerns:

  • How to determine exactly what combination of products would work best for each country?
  • How to deal with the vast amounts of data being collected efficiently to reduce the time taken to produce analyses?
  • How can the numerous complex combinations of competitors,geographical locations, market segments and products be handled effectively?
Solution: 

Addressing these needs meant that Symrise needed a solution that was intuitive to use, robust and capable of handling complex relationships. IBM SPSS Statistics and IBM SPSS Modeler provided a viable, cost-effective and efficient solution for this purpose.

Using the software, Symrise now processes the large amounts of data being collected and produces predictive models to anticipate the right product mix for each country based on the consumer preferences and market competition.

Results: 

Through this initiative, Symrise:

  • Improved the speed and ease with which data was being analyzed
  • Gained the ability to predict the needs of specific markets despite the presence of numerous complex factors
  • Could present complex findings in easy-to-understand formats to improve the decision-making process

Improved the speed and ease with which data was being analyzed

Much time was spent on data preparation in the past by keying into the system directly by Symrise researchers. Compounded by the complexity of the relationships that needed to be analyzed, researchers had to spend much time figuring out how to best deal with the data. The solution’s visual workflow interface helps Symrise researchers to visualize the relationships to be explored in a much shorter time.

Gained the ability to predict the needs of specific markets despite the presence of numerous complex factors With numerous factors affecting the product mix in each country, one of the most difficult tasks was for Symrise researchers to determine the likelihood of the success of each product mix in each territory. Combining the use of various analysis techniques in IBM SPSS Modeler, the Symrise team now produces predictive models which help them to identify the key markets for each combination of products. Product combinations are now targeted specifically for each country, allowing Symrise to respond to the needs in each market.

Could present complex findings in easy-to-understand formats to improve the decision-making process As a leading global producer of fragrances, flavours and cosmetic ingredients, the Symrise research team constantly presents numerous findings to aid the decision-making process. The use of IBM SPSS Modeler’s rich visualization tools helps Symrise to present these insightful findings in a digestible format, easing and speeding up the product decisions within Symrise. These time savings through predictive modelling are essential to the company’s ability to react to market changes swiftly.

Product

Product : 
Predictive Analytics