Through independent research, evaluation and strategic consulting support, SBD Automotive helps vehicle manufacturers and their partners create autonomous, more secure and better connected cars. Adam O’Shaughnessy is a Senior Specialist – Connected Car. Lorna: Can you tell me a little bit about your background and how you’ve come to be working with data and statistics …
Expert insight – Adam O’Shaughnessy, SBD Automotive Read More »
Rob Woods has worked in the analytics industry for over 20 years. He’s currently an Analytics Solutions Architect working on IBM’s Watson FSS suite of products. All views here are his own and not IBM’s. Describe your own background and how you came to be working with statistics / data / analytics I started as …
Expert insight: Rob Woods, Analytics Solution Architect/Data Scientist, Watson FSS Read More »
Like a lot of consultants working in the analytics industry, I’ve built up an extensive portfolio of materials to illustrate different kinds of applications and approaches. Some of these consist of files and slide decks used to explain quite esoteric procedures such as TURF analysis or Partial Least Squares. However, there are certain materials that …
In April of this year, IBM released the latest version of SPSS Statistics. Version 26 introduces a number of additional analysis procedures as well as new command enhancements. If you’re an existing SPSS user and you’d like to upgrade to v26 there’s more information about how to do that here. If you’re interested in trying SPSS …
Lorna: Please could you start just by talking a little bit about your own background and how you’ve come to be working in data? Cliff: I went to university to do a mapping science degree, during which time I had a year out in industry. I worked as a surveyor for a company that was …
Expert insight: Clifford Budge, Head of Ecommerce Data Science, major toy manufacturer Read More »
Here is an interesting confession. I work for an analytics company but I would really rather not think about or talk about analytics. Let me explain. I once worked with an operations director. He had a great team of analysts. He valued their work and was interested in the information they gave him but the …
I work for an analytics company, but I don’t want to talk about analytics Read More »
The Regular Expressions for IBM SPSS Modeler node pack provides 4 nodes that integrate the power and flexibility of regular expression pattern matching into SPSS Modeler. However, some of these capabilities can be supported using the extension nodes built into SPSS Modeler and that begs the question – why buy the Regular Expression nodes? One …
Regular Expressions for IBM SPSS Modeler: performance comparison Read More »
I was talking to a potential client recently who was frustrated by the lack of ‘real analysis’ happening in his organisation. He had a team of analysts working for him, most of whom were using Excel when he really wanted them to be using Python. Although we don’t generally recommend Excel for advanced analytics – …
Don’t overlook the value of quick wins in your analytics project Read More »
In this video Jarlath Quinn takes a first look at SPSS Modeler v18.2 and demonstrates some of the new functionality that’s included within this release.
This year SPSS is 50 years old. Development started in 1965 by a team of political scientists, frustrated at how much time they had to spent on manual data cleaning before they could start their analysis. The first release was in 1968 and by the end of the 1960s SPSS was in use in over …
Expert insights: Major Lester, founder of SPSS UK talks about fifty years of SPSS Read More »
You may have noticed by now that there seem to be a couple of recurring themes in the plethora of articles and news programmes about artificial intelligence (AI). These themes can be summed up as a) “The dangers of AI” and b) “The limitations of AI”. Articles addressing the dangers of AI tend to focus …
Three questions to ask when reading articles about artificial intelligence Read More »
When we’re talking to potential clients about advanced analytics we often ask them what tools they’re currently using. More often than not they say they’re using spreadsheets. Spreadsheets are one of the most widely used tools for statistical analysis and of course, most businesses couldn’t run without them. However, when it comes to advanced analytics …
Thinking of using spreadsheets for advanced analytics? Think again. Read More »
Can you tell us a bit about yourself, your background and how you came to be where you are career-wise? I started my career in 2001 at Research International’s Marketing Science Centre, following a degree in Sociology and Social Policy. Back then I was working mainly on analysis of market research surveys. Over time I …
Expert insight – Paul Jackson, Head of Advanced Analytics, Bonamy Finch Read More »
Can you start off by telling us a bit about your background, and how you came to be working in the analytics field? I came to analytics via a somewhat circuitous route. My first degree was in psychology, then I did a postgraduate qualification in newspaper journalism. Obviously psychology is all about the science of …
Expert insight – John Gill, Head of Insight and Analytics, Betfred Read More »
Can you start off just by talking a little bit about your background and how you came to be working in analytics in the first place? Yes, I did research methods at university and was experienced at using spreadsheets and things like that, and that’s where I picked up SPSS, and then I got into …
Expert insight – Nick Di Paulo, Lead Customer Researcher, Hyde Housing Group Read More »
I have been in the business of delivering software applications and solutions that have advanced and predictive analytics at their core, in one form or another, for last 25 years. In a recent conversation with colleagues we were discussing how the wider market has changed and, more specifically, how this has affected the way that …
5 key trends affecting technical training provision in predictive analytics Read More »
Could you start off just by telling us a bit about your background and how you came to be working in the area that you’re working in with analytics? I studied statistics with economics undergraduate level, then I went on to do a Masters in statistics at the LSE part-time whilst I was working at …
Expert insight – Karsten Shaw, Director of Analytics, Populus Read More »
What’s your background? How did you come to be working in analytics? I came from an accounting background and then moved into retail where I worked across a variety of teams in finance, marketing analytics and strategy for various different retailers. I then left that to join a consultancy working with loyalty card data. I …
What’s your background? How did you come to be working in analytics? I suppose accidentally really. I studied politics at university, then I happened upon a short-term contract for a market research company doing data entry and progressed from there. I found the work interesting and enjoyed the projects I worked on. I moved to …
Expert insight – Emma Brooker, Customer Insight Manager, L&Q Read More »
In most businesses it’s not enough to simply be measuring outcomes like customer satisfaction, sales, customer churn rates, subscription renewals, customer loyalty, cancellation rates and so on. To gain competitive advantage you also need to know what’s driving those outcomes. Which aspects of the service you provide most influence how likely someone is to renew …
7 things you need to know about key driver analysis (KDA) Read More »
Surveys remain one of the most popular forms of market research, and consequently we regularly work with customers on large survey-based market research projects. Most commonly this is customer satisfaction surveys, and these can be one of the most valuable forms of data that a company has. We also have clients who conduct broader market …
As it is the end of the year I’ve decided to devote this blog post to some thoughts on where we see the analytics market going in 2018. Unlocking the analytics potential of unstructured data Enterprises are collecting ever greater quantities of unstructured data. A recent survey by Forbes showed that the number of organisations …
Most companies these days are aware of the potential value that advanced analytics could offer them. Lots of people are talking the talk of advanced analytics, hiring data scientists and investing in sophisticated analytics technologies. But these things on their own aren’t going to give you the competitive advantage that you’re hoping for. It’s not …
How to ensure advanced analytics gives you a concrete competitive advantage Read More »
With less than a year to go until it comes into effect, organisations are really starting to get to grips with what GDPR will mean in practice. We’ve talked to lots of customers who are concerned about the implications that GDPR might have for the way in which they collect and analyse customer data. Much …
Many of our clients regularly hire new analysts and we’re often involved in discussions about what the core skills are that they should be looking for. Similarly, I often talk to people looking to build a career in analytics who want to know what skills they need to develop. The most skilled analysts are in …
Thinking of hiring a data analyst? What skills should they have? Read More »
We often talk to people who are unsure whether they need SPSS Statistics or whether SPSS Modeler might be more suited to their needs. In fact, it’s not always a clear cut choice as to which tool is more appropriate as it depends on the context in which the technology might be used. With that …
Do I need SPSS Statistics or Modeler? How to choose the right product for your needs Read More »
Over the past two years I’ve noticed a steady stream of articles in the mainstream press and business journals centred on the themes of a) the dangers of machine learning 1 2 or b) the limitations of machine learning 3 4. Many of these articles refer to incidents where machine learning initiatives have echoed and …
Contemporary analytical platforms like SPSS and SAS represent the some of the earliest and yet longest-lived examples of proprietary software in the industry. When we think of the tectonic shifts the technology landscape has witnessed in last four decades, through the mainframe era, the rise of the PC, browser wars, the dotcom bubble, the smartphone …
How alternative interfaces can help you get more out of R Read More »
Many of the analysts we speak to are being pushed over to R, primarily because it’s open source and therefore a free alternative to commercial data analytics packages for which the costs can sometimes run into tens of thousands of pounds (or more). However, even experienced analysts often find that getting to grips with R …
It’s not uncommon for people to say to us that they don’t understand why they should pay for industry standard analytics products like SPSS or SAS when there are strong open source alternatives freely available such as R. Indeed the development of R has really transformed the analytics marketplace in many ways. It’s tempting to …
Six questions to ask before you opt for open source software Read More »
It’s not uncommon to talk to potential clients who consider themselves to already be very much data-driven in the way that they operate. However it’s very rare to find a potential client that truly is exploiting the full potential of the data that they hold. That’s because companies often confuse business intelligence with predictive analytics, …
What’s the difference between business intelligence and predictive analytics? Read More »
As we help our clients get up and running with the predictive analytics tools and skills they need, we see some trends emerging in terms of the kind of applications for which clients tend to use predictive analytics most commonly. These are what we call ‘repeatable application templates’. In my previous post I outlined the 4 …
Data science is everywhere at the moment. Nearly as everywhere as big data, but not quite. Books out there are making the concepts behind statistics and predictive analytics more and more accessible not only to those in business making decisions everyday but also to the average man or woman on the street. Try Super Crunchers …
Data science is everywhere, so why no data scientists to be seen? Read More »
A is for Automation Why bother trying out loads of modelling techniques to see which one works best when Modeler can do that for you? Modeler can test many permutations of the same algorithm and multiple instances of different methods before selecting the best performers according to a pre-specified criteria. Oh and it will also …
An in depth guide to using the chi-squared test to determine statistical significance.
What is correlation? Correlation is a term that we employ in everyday speech to denote things that appear to have a mutual relationship. In the world of analytics correlations are specific values that are calculated in order quantify the relationships between variables. This kind of analysis is powerful because it allows us measure the association between …
This post describes how to use Python scripts to create and modify Modeler supernodes, and control the execution of the nodes within the supernode. If you’re after a basic overview of Python scripting in Modeler then this post may be of interest, and I’ve also written about how to write standalone Python scripts in Modeler here. As …
We spend a great deal of our time at Smart Vision helping our clients to establish the use of predictive analytics in their business. For many organisations, getting started with predictive analytics can feel like a real departure from more traditional and familiar areas of activity. That said, organisations in almost every industry sector are becoming …
Four reasons why getting started with predictive analytics is simpler than you think Read More »
The concept of the net promoter score was introduced to the world in Frederick Reichheld’s seminal Harvard Business Review article The One Number You Need to Grow in 2003. Reichheld’s research led him to believe that there was a deep and intrinsic link between profitable growth and customer loyalty. Two years of research revealed that, for most industries, …
Understanding what drives your net promoter score – how data science can help Read More »
Data science is on the rise. A couple of years back Harvard Business Review suggested that ‘data scientist’ is the sexiest job title of the twenty first century and the hype around data science shows no sign of abating. The term ‘data scientist’ itself was only coined in 2008 but since then the number of data …
Data science projects – what skills do you need and where can you get them from? Read More »
Prescriptive analytics is a relatively recent development beyond the broader disciplines of predictive analytics and data science. In this blog post I want to explain a bit about what it is and discuss why I think many organisations are already on the road to using it, without even knowing it. Prescriptive analytics is the third …
10 reasons why your organisation is ready for prescriptive analytics Read More »
In my career I’ve seen many examples of successful and unsuccessful data mining projects. I’m often asked how clients can maximise the chances of their project being successful and, based on the many projects I’ve been involved with over the years, I think there are 9 things that really help. When these factors are in …
An analytical tool for the business user. It isn’t a new idea, more a nut that many of us have been trying to crack for years. Today, of course, this problem is more pressing than ever. There are more questions that can be answered with analytics, more data to analyse and fewer trained analysts to …
In this blog post I’m going to suggest some ways in which predictive analytics can help retailers weather the economic storm they’re currently facing. The UK’s battered retail sector has been enduring an ongoing perfect storm following the financial crisis of 2007 / 2008. The government would like us to believe that things are much better …
How can predictive analytics help retailers weather the economic storm? Read More »
It’s well known that there’s a growing skills gap in the area of analytics. As organisations are waking up to value contained within their data, so demand for statisticians, data scientists and analyst grows. It’s great that so many organisations are realising the power of analytics and the competitive edge that it can give them. But …
The widening analytics skills gap – how much of a problem is it? Read More »
When talking to companies who have yet to invest in predictive analytics I am often asked if I am sure that they will benefit. Will it be worth the time and effort involved in setting up a predictive analytics project? What kinds of benefits can they realistically expect? Are they large enough to reap the …
Predictive analytics – five ways your business can benefit Read More »
After basic significance tests, T-tests, Z-tests and so on, key drivers analysis (KDA) is probably the second most popular statistically-based technique in market research. Given an outcome of interest a KDA gives us a measure of the relative importance of a set of attributes (potential drivers).Typical outcomes of interest in research are: Satisfaction – customer, employee etc. Purchase intent – how …
What do your customers care about most? Using key driver analysis to find out. Read More »
Data visualisation is a hot topic at the moment. And with good reason: a picture paints a thousand words … and the better ones can convey clearer meaning than a similar volume of numbers. There is also an ever-growing list of charts and infographics, both in the public domain and in research deliverables. They are not totally new …
In my last post I gave a brief overview of the new Python-based scripting available in Modeler 16. In this post, I will cover Modeler 16 scripting in a little more detail. This assumes some familiarity with Python such as the Python module mechanism and exception handling. There are three types of script in Modeler: …
Modeler scripts are used to automate the creation of streams, construction and configuration of nodes, stream execution and managing the execution results such as saving models to file or a content repository. A major new feature in Modeler 16 is the introduction of Python as the default scripting language. Python replaces the original bespoke language Modeler …
