SPSS Modeler: putting predictive analytics at the core of business operations

Effective use of data in business requires efficient tools. For this reason, when Houston Analytics founder Antti Syväniemi was developing his vision for making analytics part of everyday decision-making, it was clear to him that IBM SPSS Modeler should be the foundation for the analytics company’s operations. This would enable rapidly accumulating data to be used in ways that would benefit business operations and help companies be more competitive.

Houston Analytics was founded in October 2013, and right from the start cooperation with IBM was an important element in the company’s success. Thanks to SPSS Modeler, the start-up company took off quickly. Within three weeks, the company had won an advanced analytics contract with an international food industry operator. Operations gained momentum during 2014 and the company’s customer base grew rapidly, with new clients including a leading operator in heavy industry.   Houston gained success by providing the combination of market-leading technology – Modeler and the rest of the IBM SPSS family – with expert skills in helping clients achieve quick wins and high ROI with predictive analytics.  IBM soon noticed the active start-up company.

– “The IBM Business Partner Award 2014 showed that our expertise was highly rated internationally”, says CEO Antti Syväniemi. “It was great to receive such significant recognition at this early stage of operations”.

On premise and cloud-hosted services

Soon the company’s clientele expanded to cover the financial and media sectors, and  the rapidly expanding IoT market. Based on the background of the core team and Houston’s experience with their clients, the company was soon able to offer a portfolio of use cases covering customer analytics, planning and supply chain, internal auditing, and predictive maintenance, quality and optimization.  These form the basis of Modeler solutions available to Houston clients, provided on premise or as cloud-hosted services.

 

Why SPSS?

 – “The benefits to our customers are the best proof of the efficiency of SPSS Modeler. Valmet is a good example. Predictive analytics have enabled the company to extend the maintenance interval of its paper machines by 20%”, says the Chief Analytics Officer of Houston Analytics, Joonas Isoketo.

According to Isoketo, the superiority of SPSS Modeler lies in its ease of use for presenting complex analysis through graphics.  SPSS makes the creation of analytical models and testing of different approaches extremely rapid; users can quickly develop best fit solutions that maximize predictive performance. In addition, automation enables easy migration from model development to production.

– “It is also important to us that all customers can easily follow the process, regardless of their level of understanding of analytics. We use a Problem-Solution team model, in which solutions are developed in cooperation with the business stakeholders. We take an agile approach to creating analytical models”, says Isoketo. “Information that is critical for the business process can be brought into play quickly.”

Houston Analytics aims at developing sector-specific vertical solutions. These processes offer an analytical and data-based solution for a certain operating sector or its sub-section such as product group management, which includes optimization models for the product range, pricing, use of space, and procurement.  In most of the vertical solutions offered by Houston Analytics, SPSS Modeler is included in the analytics engine in one way or another.

 

Unsurpassed expertise

 The CEO of Houston Analytics, Antti Syväniemi, has worked with Colin Shearer for years. Colin is a pioneer of data mining and predictive analytics; his CV includes groundbreaking analytics projects and the design and development of Clementine, now IBM SPSS Modeler. Colin joined Houston Analytics as Chief Strategy Officer at the beginning of 2017; his unique background in the advanced analytics industry complements the extensive experience of the Houston team.

– “The CRISP-DM process model, developed by Colin and his team working with a Special Interest Group of industry practitioners, unites business understanding, data considerations and analytical approaches to offer the most direct route to achieving business targets. Applying CRISP-DM has helped us and our customers in many projects to work more efficiently and deliver fast results”, explains Antti.

In 2017, Houston Analytics was the only company in Northern Europe to receive the IBM Business Choice Award and to be listed by Forrester as one of the leading customer analytics companies. From its beginnings just a few years ago, the company’s rapid development into a significant international operator is quite an achievement. It shows that IBM SPSS Modeler was the right choice as the working foundation for Houston Analytics.

 

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