Contacts

• Colin Shearer

  Non-Executive Director colin.shearer@houston-analytics.com +44 7900 683250

  
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  Colin Shearer

  The era of big data and analytics is upon us. All organizations have the potential to benefit from this technology, but most don’t have the right processes in place to fully leverage data and analytics and enable knowledge-based decision making. Colin Shearer, the father of data mining and Non-Executive Director of Houston Analytics, is the right person to help businesses in this vital transformation.

  Colin Shearer studied Computer Science and Artificial Intelligence at the University of Aberdeen, and since 1984 has been involved in applying advanced software solutions to business problems.

  Colin co-founded Integral Solutions Ltd. (ISL) in 1989. A pioneer of data mining in the early 1990s, he was the creator and architect of ISL’s award-winning Clementine system (now IBM SPSS Modeler) and led a team which tackled numerous successful predictive analytics projects across a wide range of industries and application areas. In 1996 he jointly initiated and led an international cross-industry project to create CRISP-DM, which quickly became established as the de facto standard methodology for predictive analytics.

  In 1998 SPSS acquired ISL. Colin led the worldwide development of SPSS’s data mining business, as well as leading a worldwide team of data mining consultants and SPSS’s Advanced Data Mining Group. He subsequently held various positions at SPSS including global head of Product Marketing and Senior Vice President for Market Strategy. He was responsible for the introduction of the first enterprise-level analytics technology platform, adding rich automation and deployment capabilities to SPSS’s predictive modeling suite.

  SPSS was acquired by IBM in October 2009. At IBM, Colin led the development of industry-specific offerings utilizing predictive analytics, created and launched IBM’s first cloud-hosted analytics services, and helped design and develop advanced analytic solutions for Next Best Action and Predictive Maintenance & Quality.

  Throughout his career, Colin has been in demand as a speaker at events around the world, and has met with numerous clients to share his experience and knowledge of the use of advanced analytics and advise them on how best to leverage this technology in their business. He joined Houston Analytics in December 2016, where he will continue his mission to bring the value of advanced analytics to organisations of all types.

   

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• Antti Syväniemi

  CEO antti.syvaniemi@houston-analytics.com +358 50 387 5971

  
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  Antti Syväniemi

  My core competencies: analytics-based management models and strategies.

  My experience in the field: retail, industry, media, finances, insurance, FMCG

  My ideas about knowledge-based management

  In this era of dynamic strategy, information and managing with knowledge are the key to everything. Intensive use of knowledge is vital to sustained competitiveness. It is what links the market and competition situation with strategy, and strategy with implementation.

  Exponential increases in the amount of data can make the shift to knowledge-based management seem overwhelming, but it is no longer so. Easy-to-adopt cloud services and advanced analytics make it quick and easy to begin using information including big data.  This allows traditional financial data to be combined with up-to-date customer and market data, which enables a forward-looking view through predictive modelling

  From the very beginning, the ease of use of the information produced is important as well as the flexibility of the process.  At its best, implementing the customer-centred view throughout the organisation promotes continuous and flexible progress towards common goals.

   When a shift is made from the traditional managing with financial knowledge to the comprehensive managing with knowledge, the greatest challenge is the cultural change that is required to complete the shift. A unified view of the business operations and their targets must be formed in order to achieve results from the traditional patchwork of unit- or function-oriented knowledge. The processes must be supported by up-to-date information. The users’ outlook may change, but information belongs to everyone. This means that everyone in the organisation can understand the significance of their work in implementing the strategy, and everyone can commit to the set targets. Therefore, the change is more about an information project than a technology project.

  Regardless of whether we want it or not, we have shifted to an information society. Now the generation and continuous development of new business models is essential to business survival. This requires not only experience and knowledge to understand the present and the ability to view and analyse options open-mindedly, but also – and above all – the courage to move on from old thinking and operating models.   This is why the opportunities provided by the processing and analysing of information increasingly shape the agenda of corporate strategy work.

  Motto: “A mind is like a parachute. It doesn’t work if it is not open.” ― Frank

  Zappa

   

   

   

   

   

   

   

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  Motto: “A mind is like a parachute. It doesn't work if it is not open.” ― Frank Zappa

• Tommi Havukainen

  Country Manager Finland tommi.havukainen@houston-analytics.com +358 50 340 6340

  
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  Tommi Havukainen

  Tasks: bringing the benefits of analytics to support daily decision-making at various levels of customer organisations

  My core competencies: applying knowledge-based management to business development

  • Consultancy services: CRM ECR, big data, product and project management
  • Technology: SQL, Toad , SPSS, Oracle, Teradata, SAP, business objects
  • Analytics: customer insight, trends, and forecast models

  My experience in the field: retail, industry, media, telecommunications, FMCG, hotel and restaurant sector, finance sector

  My ideas about analytics

   In using analytics, what matters is not the model but the problem to be solved. For the best possible results, the end user of the information must be involved in the process from the beginning. So the questions to be answered must be specified by a joint Problem team. Only then can the Solution team of experts begin their work.

  Working in a wide range of operating fields has led me to take a pragmatic approach to analytic thinking.  It is vital that analytics are not made science: the results must be easy to put into practice.  This does not mean that research and difficult analytic models would be useless, it means that the output of the models must be easy to understand and easy to apply to real-world business conditions.

  Too often, a model that yields good results elsewhere is automatically turned to in another setting without first considering what the requirements of this new setting actually are. This turns things backwards – the analytics model must serve the business situation, not the other way round. Furthermore, for a solution to be successful it must be based on existing data. And the parties must jointly specify the reasons for the modelling, as well as where and how it is to be applied.

  In most cases, the analyst is not the end user of the results in business operations. Successful solutions are those that are developed in close cooperation with the customer. For this reason, the user-friendliness of the results is vital to the solution. The solution must be easy to understand and unambiguous to the user, and must bring added value. Applying analytics to business is nothing to be afraid of!

  Motto: The clearer the target, the better the chances of success.

   

   

   

   

   

   

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• Ville Laitinen

  CTO ville.laitinen@houston-analytics.com +358 50 376 1349

  
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  Ville Laitinen

  My core competencies: background systems, in particular databases and big data

  • Technologies
    • IBM SPSS Modeler (certified professional), SAS, R, Python, ODBC/JDBC
    • Databases: Teradata, MS SQL Server, Oracle, MySQL, Postgres
    • Web crawling: Scrappy, gui based
    • NoSQL: Mongo, Casandra
    • Hadoop: Hortonworks, IBM, Apache Hadoop
    • Spark
    • ETL: Pentaho, Informatica, SAP business objects data services
  • Hardware
    • Work stations: analytics work stations
    • Servers: virtual, cloud, and analytics servers
    • Networks: VPN, cloud, and analytic networks

   My experience in the field: retail, FMCG, mechanical engineering industry, media, finances

  My ideas about technology

  Big data changes business models and creates various opportunities to better serve customers. Today, fragmented and very large file structures (up to several petabytes in size) can be organised and analysed to meet the needs of business operations.

  The rapid development of technology and analytics makes it easy to apply big data even in situations where it was not previously used, either due to technical limitations or prohibitively high costs.

  Information provided by data mining is becoming a necessity on the increasingly competitive markets. Companies that are managed with knowledge and use up-to-date information to create added value for customers are at the forefront of digital business operations.

   Motto: “An intellectual says a simple thing in a hard way. An artist says a hard thing in a simple way.” Charles Bukowski

   

   

   

   

   

   

   

   

   

   

   

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  Motto: “An intellectual says a simple thing in a hard way. An artist says a hard thing in a simple way.” Charles Bukowski

• Juha Raunama

  Director, Customer solutions juha.raunama@houston-analytics.com +358 40 084 5908

  
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  Juha Raunama

  Tasks: understanding and solving the customer’s business challenges in close cooperation with them, using analytics and knowledge-based management.

  My core competencies: vision and strategy work, business models, business intelligence, location intelligence

  My expertise in the field: public administration, FMCG, industry, financial sector, retail

  My ideas about business development projects

   When a company faces the need to change and up its game, the first step is to understand the present situation and the accompanying challenges. A compelling vision for the company can be developed by first asking where the company wants to go, and why. One way to approach the matter is to assess the situation thoroughly using the available data. The aim here is simple and straightforward: identifying information that supports decision-making and questions that are critical to the business operations from that data. These facts provide a solid grounding for cooperatively forming an inspiring vision of the company’s future.

  Once the present situation has been analysed, the next step is to develop the data and business models. This requires close cooperation between the business and analytics teams.  The shared goal is to acquire concrete and visible results as quickly as possible, before the actual automation process begins.

   Once the knowledge-based management model and process have been created, the automation process can be implemented in phases. The basic principle of “get the high profits immediately, smaller ones can wait” is also an excellent guideline for implementing automation projects. A proven method is to progress one function at a time, all the time listening to the user’s needs. A typical feature of successful development projects is that users feel that the information and new operating models make every task easier and more effective.

  Motto: “It is a lot easier to get where you want to go once you know where you are now, and where you are heading.”

   

   

   

   

   

   

   

   

   

   

   

   

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• Joonas Isoketo

  Chief Analytics Officer joonas.isoketo@houston-analytics.com +358 40 570 2166

  
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  Joonas Isoketo

  My core competencies: specification, implementation, and end use of analytics solution.

  • Analytics
    • Modelling; data mining; web, customer, business, and predictive analytics and interpreting the results
  • Technologies
    • Analytics tools and programming: IBM SPSS Modeler (certified professional), R, SAS, Java, Python, C#
    • Database management: SQL, relation databases, algorithms, Hadoop, big data, data models, EDW, CDW, testing of data resources
    • Marketing automation: Adobe Campaign (Neolane)
  • Statistical modelling
    • Regression, time series, life cycle, and association analyses; segmentation, grouping, classification, Bayesian analysis, hypothesis testing, simulation, optimisation, and multiple variable methods

   My experience in the field: FMCG, retail, industry, media, financial sector

  My ideas about analytics

   This is definitively the era of analytics. Unfortunately, people still confuse analytics with static reporting. Companies collect data and make analyses, but without a concrete purpose or practical implementation of the results they easily remain one-off reports. Often they are far too mathematical to be of any practical use. However, a growing number of successful analytics projects create real added value for business. These prove that data analytics can greatly benefit business processes.

  So what is it that separates analytics that create added value from the ineffective kind? If analytics are used to answer the question “what happened?”, the result is a traditional report, which of course also provides important information.  But answering the question “why did this happen?” creates more added value and is closer to real analytics. The question “what will happen?” leads to more profound, future-oriented analytics that help grasp the real opportunities provided by analytics. However, it is easy to get carried away, as the opportunities offered by analytics are endless. The next question might well be “what do I want to happen next?”. This question can also be answered using analytics.

  Analytics is about adapting algorithms and statistical models to business problems based on available data. The aim is to make these problems concrete in order to make the decisions needed to solve them. My job at Houston Analytics is to produce analytics solutions that are understandable from the business point of view, and that are easy to integrate with practical decision-making processes. A direct link with practical applications is one of the main cornerstones of current analytics.

  Motto: “If you can’t explain it simply, you don’t understand it well enough.”

  Albert Einstein

   

   

   

   

   

   

   

   

   

   

   

   

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• Tuulikki Markkula

  CMO tuulikki.markkula@houston-analytics.com +358 40 516 5641

  
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  Tuulikki Markkula

  My core competencies: Vision and strategy work, crm, multichannel customer dialogue, marketing automation and communications

  My ideas about customer-oriented business operations

  A successful strategy starts from understanding the market changes, trends, competitor and network analyses, non-verbal signals, and the courage to see outside one’s own surroundings and to identify points of discontinuity.

  In this era of data overload, everything is based on knowledge and managing with knowledge. Information links the market and competition situation with the strategy, and the strategy with monitoring. Because the strategy is the sum of the business choices that are made, a successful strategy is best created by combining analysed information with a strong business view.

  The shift from product-centred to service-centred business that is boosted by the digital revolution will significantly increase the value of customer information in business management. However, often very little thought is given to customer relations and customer targets. This shortcoming is dangerous in an era where nodes of information that are linked to customers form the gateway to success.

  There is no such thing as an “average” customer. What is an optimal product-price-time-channel for one customer is inadequate for another customer’s needs. This applies to both consumer and B2B business. In the world of fragmented consumption and intense specialisation, it becomes increasingly important to understand the customer. A general knowledge of mass consumer behaviour models is no longer sufficient for a strong competitive edge. Instead, a 360 view of the customer is needed, integrating internal and external knowledge with business.

  Motto: A wise question is half the answer.

   

   

   

   

   

   

   

   

   

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• Jani Göös

  Analyst jani.goos@houston-analytics.com +358 44 559 3770

  
  

  Jani Göös

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• Kimmo Kettula, PhD

  Analyst kimmo.kettula@houston-analytics.com +358408236353

  
  

  Kimmo Kettula, PhD

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• Hanna Pesanto

  Senior Rocket Scientist hanna.pesanto@houston-analytics.com +358 50 527 2811

  
  

  Hanna Pesanto

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• Chloe Ashworth

  Junior Consultant chloe.ashworth@houston-analytics.com +358 40 525 5532

  
  

  Chloe Ashworth

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• Oskar Vuorela

  Technical Specialist oskar.vuorela@houston-analytics.com +358 40 687 3131

  
  

  Oskar Vuorela

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• Aleksi Vuorio

  Junior Analyst aleksi.vuorio@houston-analytics.com +358 40 702 8482

  
  

  Aleksi Vuorio

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• Hannes Siitonen

  Sales and Marketing Trainee hannes.siitonen@houston-analytics.com +358 40 683 8831

  
  

  Hannes Siitonen

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• Ben Nyman

  Country Manager Sweden ben.nyman@houston-analytics.com +46 70 359 44 70

  
  

  Ben Nyman

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• Robert Moberg

  Chief Analyst robert.moberg@houston-analytics.com +46 7030 839 10

  
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  Robert Moberg

  Bio: Since graduating from the University of Linköping in 1996 with a degree in Statistics, Moberg has been working in the industry of Data Mining, a.k.a. Big Data Analytics. With extensive experiences, as well from the software industry as from the real world a profound well of use cases has been gathered, addressing a vast range of challenges, issues and problems. All with the clear main goal to create business value with the support of the data, that almost always is “just laying” around unused.

  Moberg, was until January 2017 employed by IBM for almost 7 years in the office in Stockholm and the one in Brisbane, as a Subject Matter Expert in Predictive Analytics. Among previous employers you will find SAS Institute and the telco “3”, as well as other European analytical entities.

  Tasks: Evangelizing the great benefits of advanced analytics that is applicable to almost every type of organization.

  My core competencies: Applied data mining and statistical analysis.

  Tactical and strategical views on the benefits of advanced analytics.

  Analyzing use cases with the target on articulating the silver bullet question that the advanced analysis will answer to ensure optimal business benefit.

  CRISP DM – methodology for succeeding in applying data mining to a business issue.

  My experience in the field: Retail, Telco, Manufacturing industry, Financial sector, Government, and health care

  My ideas about analytics: The one question dilemma. Although it seems trivial to rush through the first step in the CRISP DM methodology, Business Understanding I will stress the importance of being thorough here. The objective is to articulate the main question that will give us the biggest bang for the buck and that also can be answered by the data available. I know that many organizations out there and many projects fail in this seemingly easy process step. Spend some time to get this right and there is a lot of time and yield to be gained further down the line in the project. Here is a brief list of what needs to be addressed in articulating this question:

  • The question and the consequent answer needs to be on the corporate strategic radar, preferably touching on the targets mentioned in the annual reports.
  • The question and the consequent answer needs to be tactically deployable, i.e. it must be possible to be as proactive as the use case requires in order to reach the expected effect.
  • The question must be answerable by the data available.

  Motto:

  People Use Statistics as a Drunk Uses a Lamppost — For Support Rather Than Illumination

  Andrew Lang

   

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• Arto Tikkanen

  Senior Advisor arto.tikkanen@houston-analytics.com +358 40 144 2222

  
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  Arto Tikkanen

  My core competencies: business management, comprehensive development of the order-delivery chain, international business operations

  My experience in the field: food industry, packing industry, installation and mechanical engineering

  My ideas about knowledge-based management

  To succeed in a competitive market, a company must have excellent products and brands that differ from those of the competitors, and must also have the best order-delivery chain. An efficient and reliable order-delivery chain ensures the availability of the most popular products at all times.

  Improving the efficiency of the order-delivery chain has traditionally been based on models that forecast product demand. The Internet of Things has ushered in a new era, one in which real-time information can be collected on loading, deliveries, and driver information. Driving routes and resources can be optimised for quality, reliability of deliveries, and efficiency. The optimisation of the order-delivery chain generates the greatest benefits when linked with the surrounding processes such as production, concept development, and markets.

  The cornerstone of any company’s success is increased knowledge and expertise within the organisation. Modern technology enables extensive acquisition and use of information, e.g. on consumer behaviour, pricing, marketing strategy impacts, and performance of the order-delivery chain. However, the main requirement for development is the activity and positive attitude to change of the staff.

  Motto: The easy work has already been done!

   

   

   

   

   

   

   

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