How to be happier

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Our brain is constantly rewriting memories- therefore trying new things, going out of our comfort zones and developing ourselves as best we can, will help us to expand on memories. Bad memories are suddenly seen from a new perspective and become more positive; our already happy memories grow in their importance and significance to how we view ourselves as today. All experiences and memories make us who we are today, so it is important to look back on the past positively to help us develop as a person.

It’s also important not to rely on our brain to rewrite these memories. Addressing painful memories in which you have felt hurt or lied to can be painful. However, by facing them directly, and even the people who caused them can help you deal with the memories and the pain associated with them. By doing this the memories become less painful, and less significant to you, allowing you to give greater significance to positive parts in your life.

It is of great significance to create new memories. It is important to live for today, ensuring that all the new things you bring into your life help you develop into a more positive person. Trying to live without expectation for tomorrow can help benefit when that day comes as there is no opportunity for disappointment. It is important to remember that life is a journey, not a race. Making time to laugh, have fun and sleep in your day ensures that your needs are fulfilled. A lack of sleep makes you more vulnerable to negative emotions as it is harder to rationalise all the different ideas following through you day. Therefore enough time should always be put aside to rest and rejuvenate.

Remember that everyone has their own problems, and whenever you struggle you are not alone, or weaker than those around you. It is not a weakness to feel pain, or to be apprehensive to trust others because of the people who have lied to you in the past. But, we should use these memories to grow. By taking a negative memory and focusing on the positive can help us to have a whole new positive outlook on life. For example, do not let ignorant, rude people in life bring down your mood, but appreciate the positive things they have provided, for friends you would never have met without them.

When you focus on your problems you have more problems. When you focus on your possibilities you have more opportunities.

Read more Schezzer’s Blog articles at
https://www.linkedin.com/pulse/how-happier-schezzer-scheherazade/


Is Big Brother alive and well and living in your fridge?

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Back in 2009 we wrote a blog post called “Is Big Brother Alive and Well and Living in Your Fridge?”  That was long before people were talking about “the internet of things” but now that the topic is back in fashion we’d thought we’d re-publish it!

Enjoy!

What is the only appliance in your house you are unlikely to ever switch off? Your heating? Your TV? Your computer? Your broadband?

If you think about it, the most likely “always on” device in everyone’s home is their fridge.

So, if your fridge has a mobile wireless internet connection (probably paid for by the fridge manufacturer rather than you) it could become a key hub within your home for all sorts of applications from automated home controls to CCTV. This is quite apart from all the commonly discussed aspects about it being able to send shopping lists to your grocer (and then telling your robotic assistant when they’re ready to collect).

Have you bought a new fridge lately? Ever checked what electronics it has built-in that you might not know are there? In future that could become a decision-criteria on what fridge you buy.

Now the scary part. What if it had a built-in web cam?


Behavioural Economics – An incomplete solution?

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When psychologists and economists discovered market research behavioural economics was born.

Many market researchers will see some of the examples of behavioural economics and think “Surely we knew that anyway?”

“How so?” you may ask.

Well that is because market researchers have to understand those types of outcomes in order to design research studies that provide useful results instead of results that stem from the circumstances under which the experiment took place. The key difference is that in the past there was no real scientific description of how decisions were systematically affected by these circumstances.

In the April edition of Marketing magazine Professor Nick Chater, Head of the Behavioural Science Group at Warwick Business School, described one such experiment. Female experimenters situated at the ends of two bridges, one high and precarious – the other low and sturdy. People crossing the bridges were asked to perform a small task and given a number to call the experimenters to follow-up later. The net result was that men who had crossed the high and precarious bridge were the ones most likely to call. Women crossing the low sturdy bridge the least likely. But that was not the most interesting part.

The most interesting part was that the men crossing the high bridge were more likely to call because the adrenaline rush that went with crossing the bridge transferred to the meeting such that they believed they had met someone who they really liked and wanted to see again. In many respects this is the same phenomena that drive people to repeat ever more risky experiences.

But is this really that surprising? Or is just a perfectly understandable and well-known outcome being presented in a new way? My belief is that often it is the latter and not the former.

Having worked for many years doing data analyses for the purposes of predicting individual customer behaviour, we have found that most behaviour can be described and anticipated if one assembles data on individual circumstances and attitudes. We call it the ABC of customer prediction. These “ABC” are:

- Attitudes
– Behaviours
– Circumstances

Understand the attitudes of the individual – what they value, what they aspire to, what they tolerate – and the circumstances in which they are making the decision – in as much detail as we can gather – and you can predict what they will decide to do with more than 50% certainty more than 50% of the time. And that is being conservative. Typically the 80/20 rule applies and you can predict the outcomes such that marketing profitability can be increased by 50%.

We have achieved this for numerous clients and our case studies provide the details. To find out more log-in to our site and visit our case study section.


The Passive v Interactive Debate

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Business consultant Luke Johnson stated in the April edition of Management Today that the old-fashioned ‘linear’ and ‘one directional’, PowerPoint-based, presentation is now dead. People now expect discussion and interaction. What’s more he then expanded that to say that it is the way of the future for all communication – whether film, TV, advertising, documentary, debate and so on.

Anyone who has watched Match of the Day or Question Time on the BBC will be aware of the fact that random Tweets are shown on-screen from equally random people. The question this interactive proliferation raises, however, is “Who wants this?”

It is true that when watching a film or reading a book one can be moved to the extent of wanting to share ones thoughts with others or with the authors. But that does not mean everyone on the planet – and certainly not on an unsolicited or unassociated basis.

Surely there is a right ‘not to be forced to interact’ as well as a right to offer interaction.

Certainly I would not wish to see inane Tweets on MOTD even when viewing on the HD channel. Viewing on that channel does not mean I have also given permission to receive unsolicited Tweets by dint of the fact that I have paid a TV Licence fee.

If Luke Johnson is correct and interactivity is something that is going to grow in pervasiveness then it suggests that there will be a growing debate about “Passive v Interactive” opt-ins, as there was when direct marketing vis telephone, fax, and email came onto the scene.

It would be good to know what others think about this topic.


Changes to Society and Effective Net Preference

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The Office for National Statistics recently released new data on the structure of Britain’s 26.4 million households. It showed that 29% of households now consist of only one person. Most of those in the 16-64 age group are male. For those over 65, the gender balance is reversed.

The most common family type in 2012 is a married or civil partnered couple without dependent children, accounting for 7.6 million out of a total of 18.2 million families in the UK.

The number of unmarried couples living together has doubled over the last 20 years.

This all has implications on the way businesses structure their customer databases and the implementation of their CRM strategies. This dramatic shift in social structure has coincided with an equally dramatic shift in household purchasing behaviour, attitudes and preferences. Except it isn’t coincidental.

Now, more than ever, a business needs to understand and react to the changing attitudes and preferences of their customers caused, in part, by their changing lifestyles and social structures. It’s essential to develop an effective CRM programme to maintain engagement and preference with the business’ customer base.

The best way of doing this is to measure and track Effective Net Preference (ENP) using a customer panel.

And how do you do this? Why not ask us?


Buyer Beware!

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So many projects that promise the earth end up costing too much, take too long to deliver or never quite do what they say – and analysis projects are just as prone to this as big infrastructure projects. However there are ways to mitigate the risk – you just need to look out for the warning signs, and if they start flashing get out quickly!

Warning sign 1 – “We’ll do it all for you”
This is a classic opening gambit in a sales pitch. Companies bringing in consultancies to do analysis projects typically do so because they have a resource and/or capability gap. A proposal that promises hands-off management is very attractive in these circumstances.

Risks
No business is the same – in terms of the data used, how the business operates, the decision making process etc. It is not credible that an external consultancy can absorb this understanding without committing sufficient time or resource to do this. It is those quotes that understate this work that should signal a red warning light. Ironically a proposal for work, which has significant time and effort allocated to knowledge gathering and understanding, should be seen as a positive not a negative!

Warning sign 2 – “Trust me I’m a big blue chip consultancy”
The logic is that risk is reduced by going for reputation and a track record of delivery with a big ticket consultancy. The argument is that while it may cost more, you know it will work so you save money in the long run. And look how glossy the promotional material is – and boy, do the employees sound credible!

Risks
Everything that we have said in regard to warning sign 1 applies even more to this situation. The day rate associated with the blue chips can make even the biggest company gulp and the natural inclination is to cut back on costs wherever possible – and the initial ‘knowledge and understanding’ work tends to be the area where the axe falls. Even if this part of the project survives, typically it is the handover or on-going support that is curtailed – often to recover an earlier cost over-run or simply because management priorities have changed as the project progresses.

The second risk area relates to how the blue chips operate. The calibre of the individuals is typically strong – quite simply you get what you pay for and they also have the reputations that attract the best. However with any company of significant size (and an audit heritage) the natural culture is one of conformity. Hence there are documentation and process standards – as a result the client often ends up drowning under a forest of paper, which needs costly time and resource to review and ensure that it reflects their requirements.

Finally businesses continuously evolve and change. For one-off analysis projects it isn’t such an issue but a significant number of projects hand over models or learnings that need to be updated to ensure they remain relevant. Certainly from a consultancy perspective these are far better solutions to sell into a company as there is the opportunity of future income. With a blue chip the ongoing cost becomes prohibitive for all but the largest organisations.

In summary, for many companies the glossy brochures are not necessarily the best solution. Technology is such that tools and techniques are no longer the preserve of the blue chips consultancies. Smaller suppliers can provide a more flexible and tailored approach that is relevant and can add more value to the client. They are also more likely to establish an ongoing relationship as they are not hamstrung by fixed processes and excessive overheads that result in inflated costs.

Warning sign 3 – “There will be no need for manual intervention”
This is the classic black box solution. The expectation is that there are standard approaches and all that is needed is to gather the right information from the client and then the commissioned model can be completed and handed over. The onus is then on the client to update it with the latest information and the model will continue to churn results as and when required.

Risks
The first risk is around the one size fits all mentality. I have yet to see a business where this works. Every company has its own quirks and foibles and ways of working. Typically you see IT projects where every effort is made to get the business to conform to the new system. Often this is the right thing to do and over time can work. In fact the risk is greater going the other way – adapting everything to the client results in the delivery of a bespoke solution that is difficult to maintain. In the field of analysis this argument is significantly weaker. Analysis is intended to add value to the business through insight – it is an agent of change and not a change in itself. Hence any deliverables or outputs need to be fit for purpose and usable by the client. In this situation the black box approach is unlikely to be the best solution.

The second area of concern is the assumption that the modelled outputs remain appropriate. Businesses constantly adjust, driven by changes in the markets that they compete in. The assumption that you can simply pass over a black box and say goodbye is flawed. There needs to be constant evaluation and verification to ensure that the model remains fit for purpose. There is no issue with passing this responsibility over to the client – similarly it may only need a review process on a quarterly or annual basis or when certain tolerances are breached. However I have seen many companies where key internal processes are based on a model or analysis that was completed many years ago and where there is nobody left who understands it. What they do know however is that the process notes say run the macro on a Tuesday and to type the prices that are generated into another system on Wednesday. If they do this they get a pay cheque at the end of the month.

The final risk in this area is the data itself. In my experience the maintenance and quality of data has deteriorated in companies. There are a number of reasons for this, but this is not the time or place to explore them. The consequence is that much greater care is needed to ensure the data, and assumptions that underpin the data, are valid. This applies to internal projects but even more so to external projects. This care is required not only as an initial input but also on an ongoing basis. It is very easy for data to subtly change (eg bringing in categories not previously reported) or data sources to change. This may be known – in which case the black box model will need to be updated – or not known – and so either the model will fall over, or start generating spurious results. The impact of this is cumulative over time and so the issue is not noticed initially. No matter the situation there is a need for transparency as to how a model or process works and an on-going process of review and evaluation to ensure it remains fit for purpose.

Implications
The clue is in the title – “buyer beware”. There is no approach that is always right but there are key principles that need to be considered when commissioning work.

  • Solutions that work in isolation of the client usually end in tears. It is important to work with companies that have a good cultural fit or an approach that spends time understanding how your company works and ensuring that the project deliverables add the most value to you.
  • Size isn’t everything – there a large number of smaller and niche operators who are able to match the big boys in terms of the quality of the output at a much lower cost and probably more importantly they are companies you can afford to establish an on-going relationship with.
  • Transparency and ownership are increasingly important – if you do not have an explicit understanding or knowledge of the final model or basis of the analysis then you are at risk moving forward.

Awareness of these warning signs doesn’t mean you are guaranteed a positive outcome – but at least increase the chances of successful outcome!


Analytics and the Finance Team

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A typical Monday morning in many companies involves a panic stricken Finance team rushing around at some ungodly hour desperately trying to provide explanations as to why sales are down 1% on the budget and showing 3% growth on the previous year.  Spreadsheets of increasing complexity are being pummelled into submission, powerpoints are being generated and words are being crafted in ways that do not offend delicate egos nor upset the political apple cart.  A final check to ensure all of the action points from last week have been closed down – and then it is done!  Only the world has moved on – the critical questions from last week have been superseded by other questions.  Somebody had spotted a rounding error. Nobody could remember how much buffer was built into the forecast.  What impact will the unseasonally bad weather forecast have on sales next week?  And so the chaos starts again with only a few days to turn it round in time.  And in some companies this maelstrom of chaos happens daily.

When sales and profits are growing there is little need for complex analysis – the urgency to understand the drivers of performance is more muted where the return on investment is 7% compared to the target 10%.  One of the consequences of this is that the analytical role became the preserve of finance.

Growth and profit have until recently been driven by an unrelenting focus on operational efficiency.  For this the classic Finance approach is perfect – systematic variance analysis that deconstructs performance variances and delivers clear accountability.

Most of the companies I have worked for have at various points had teams of specialist analysts, typically having maths, science and economist backgrounds.  But the number of people employed in these roles has significantly reduced in recent years.  After all, the numbers are easier to access.  IT are claiming one version of the truth and Finance can do anything nowadays in their Access databases. So why have two teams doing what is seen as the same thing, ie the numbers?  An easy call to drive operational efficiency and reduce unnecessary overheads is to reduce the analyst pool.

We have lived through an era where progress has been made through driving operational efficiency, compliance and standardisation and customer demand has been relatively strong. Is this sufficient for companies to thrive in the future?

Finance rarely look at the world from a customer perspective – it tends to be transaction based and ignores customer circumstances and attitudes.  However it is now relatively easy to identify at an individual level motivations and preferences and hence empower communication and engagement at an individual level.

The one size fits all approach to marketing is no longer relevant.  We are not simply looking at another level of sophistication with CRM – we are now at a point where a product can be tailored specifically for an individual, where a promotion is tailored based on individual preference.

 

So What are the Consequences?

  • There are a number of companies who have used analyst capability alongside classic Finance with continued success.  These companies will continue to exploit this competitive advantage.
  • For companies that have reduced their analytical talent or simply have never had this capability – with the tools that are available today it is relatively easy to play catch up.  The risk is in getting the right data from your system (which may require significant IT investment) and can find the right resource.
  • For many smaller companies this type of customer centric analysis was simply not affordable – it is now.  A good example is with regard to market research – in the past this required dedicated resource (bought in or in house) to ask customers questions.  The ability to generate online surveys at nominal cost, combined with the ability to handle large volumes of data without expensive tools such as SAS means the playing field has at least partially levelled  with the blue chip beasts.
  • The world of retail is already seeing niche operators springing up specialising in customer and/or product niches.  This is clearly happening in the analysis world as well – and this again comes back to the tool capability and cost – you no longer need excessive server and application running costs to produce the analysis and insight that you did 10 years ago.
  • Hence companies no longer need to get support from the big blue chip consultancies in these areas and can have confidence in the ability of smaller specialist operators.  It is these operators that are also working with some of the best analysts who are attracted by the flexibility of the working relationship and avoiding the red tape and bureaucracy that goes with working for a “normal” company.
  • Of these new analytical companies the ones that thrive will be the ones that can communicate clearly and effectively to ensure clients are making decisions on the best information available.  Those that fall into the old analytical trap of poor communication and analysis paralysis will simply not survive.

 


Fabio Capello: the best football manager England ever had?

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Everyone believes that Alf Ramsey was the most successful manager the England football team has ever had, but it simply isn’t true.  Statistically, it is Fabio Capello who has been the most successful.  Under his coaching, the England national team won 66.7% of all the games they played; when Alf Ramsey was in charge, they only won 60.7% of all the games they played.  By contrast, Kevin Keegan only managed to win 38.9%.

Of course, it’s not how many games you win, but which ones.  Alf Ramsey won the World Cup; Fabio Capello didn’t.

These are just the statistics of what happened in the past.  The England football team at a 66% win rate is no better or worse than the majority of all the other top class football teams in the world.  (There are exceptions – Brazil often manages to win 80% of their games, but then Brazil is somewhat exceptional.)

The problem with statistics is that they are not analytics.  Knowing the average performance of the past is of little use in trying to predict the outcome of the next game.  In the same way that your chances of winning the lottery remain unchanged no matter how many times you lose (and it’s amazing just how many people believe that their chances of winning increase after each time they lose).  The chances of England winning their next game are 2-1, irrespective of whether they’ve lost their last three games.  And the odds that their opposition will win the match are also likely to be 2-1 as well.

Analytics are different.  It’s analytics rather than statistics that will help you forecast the future.  Analytics and its associated modelling techniques can be used to predict future outcomes with a high degree of accuracy.  Forecasting outcomes of decisions made about the team depends upon knowing which factors correlate with success and which are irrelevant and that’s the beauty of econometric modelling which, when done properly, distinguishes between causal factors and those factors which are merely coincidental.

Many businesses are increasing the use of such analytic based models to help improve efficiency and determine all the outcomes of various marketing mix scenarios.  As a result they know all the consequences of any decision that they take before they take the decision, something that gives these businesses a significant competitive advantage.

For example, if the business operates in a market where launching new products has statistically only a 1 in 10 chance of success, then it is doubtful whether you would ever want to launch a new product.  What analytical modelling does is identify the drivers of success for a new product, radically improving the chances of success.

Now football clubs could do the same, but of course, the football business doesn’t comply with conventional business rules.  There has been some limited modelling undertaken on which factors really influence team performance and success.  For example, the outlay on transfers – buying new players – explained only 16% of the teams’ variation in final league position.  However, spending on team salaries explained 92% of that variation.  High wages help a club much more than expensive transfers.

Unfortunately, despite the evidence, club managers want to spend ever increasing amounts of money on acquiring new players at the end of every season, a lot of whom fail to live up to expectations and never produce the outcomes that were anticipated from their purchase.

So what will be the chances of success for Roy Hodgson?  Well, statistically speaking…


Why the Pen is Mightier than the Pad

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The iPad and other tablets like the Galaxy have brought a new dimension to computing. They are the closest thing we have to conventional non-IT-based reading, writing and drawing technology. In other words, pen and paper.

The fundamental flaw they have, however, is that the technology is in the pad whereas, if you think about it, with conventional pen and paper the technology is in the pen, not the paper.

Ink flows from the pen onto the paper. Where the ink goes is controlled by the user, not by the paper. And any part of the paper which is touched by anything other than the tip of the pen remains unblemished. The pen is mightier than the paper.

Our view is that the next great leap in ‘computing for the masses’ will be when the "pointing device" takes the next step and becomes the true controller of the technology instead of the slave to the machine.

Adobe Ideas Is an app which already moves in that direction but it’s not quite there.

So keep an eye out for pointing devices that become smarter and pads than become dumber.

They will be the user interfaces of the middle of the 21st century.


Copenhagen is just ‘History Repeating Itself’

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For those of you depressed that the two weeks in Copenhagen have not come up with a solution to climate change, then take heart – it’s just history repeating itself.

At the start of the 20th century, 200,000 horses lived in New York City and produced 5 million pounds of horse manure each day. It was an environmental and health catastrophe that affected every major city in the world.

In 1898, New York hosted the first international urban planning conference. Horse manure dominated the agenda. After 3 days (instead of the intended 10), the delegates gave up. They could see no solution to the problem and consequently believed that the great cities of the world were doomed.

The solution that saved the 20th century is one that appears to threaten the 21st century – the internal combustion engine.

When the solution to a given problem is not obvious, it is easy to assume that no solution exists. But history has shown us time and time again that such assumptions are totally wrong.