A number of famous Business Schools in the UK and US such as MIT Sloan, NYU Stern and Imperial College have launched new programmes in business analytics. These courses have been nicknamed ‘Big Data finishing school’. Why might qualifications in this area be highly valued by firms?
Employees who have the skills to collect and process Big Data might help firms to successfully implement a pricing strategy that approaches first-degree price discrimination.
First-degree price discrimination is where the seller of a product is able to charge each consumer the maximum price he or she is prepared to pay for each unit of the product. Successfully implementing this type of pricing strategy could enable a firm to make more revenue. It might also lead to an increase in economic efficiency. However, the strategy might be opposed on equity grounds.
In reality, perfect price discrimination is more of a theoretical benchmark than a viable pricing strategy. Discovering the maximum amount each of its customers is willing to pay is an impossible task for a firm.
It may be possible for some sellers to implement a person-specific pricing strategy that approaches first-degree price discrimination. Firms may not be able to charge each customer the maximum amount they are willing to pay but they may be able to charge different prices that reflect customers’ different valuations of the product.
How could a firm go about predicting how much each of its customers is willing to pay? Traditionally smaller sellers might try to ‘size up’ a customer through individual observation and negotiation. The clothes people wear, the cars they drive and their ethnicity/nationality might indicate something about their income. Second-hand car dealers and stall-holders often haggle with customers in an attempt to personalise pricing. The starting point of these negotiations will often be influenced by the visual observations made by the seller.
The problem with this approach is that observation and negotiation is a time-consuming process. The extra costs involved might be greater than the extra revenue generated. This might be especially true for firms that sell a large volume of products. Just imagine how long it would take to shop at a supermarket if each customer had to haggle with a member of staff over each item in their supermarket trolley!! There is also the problem of designing compensation contracts for sales staff that provide appropriate incentives.
However the rise of e-commerce may lead to a very different trading environment. Whenever people use their smart phones, laptops and tablets to purchase goods, they are providing huge amounts of information (perhaps unconsciously) to the seller. This is known as Big Data. If this information can be effectively collected and processed then it could be used by the seller to predict different customers’ willingness to pay.
Some of this Big Data provides information similar to that observed by sellers in traditional off-line transactions. However, instead of visual clues observed by a salesperson, the firm is able to collect and process far greater quantities of information from the devices that people use.
For example, the Internet Protocol (IP) address could be used to identify the geographical location of the customer: i.e. do they live in a relatively affluent or socially deprived area? The operating system and browser might also indicate something about a buyer’s income and willingness to pay. The travel website, Orbitz, found that Apple users were 40 per cent more likely to book four or five star hotel rooms than customers who used Windows.
Perhaps the most controversial element to Big Data is the large amount of individual-level information that exists about the behaviour of customers. In particular, browsing histories can be used to find out (a) what types of goods people have viewed (b) how long they typically spend on-line and (c) their previous purchase history. This behavioural information might accurately predict price sensitivity and was never available in off-line transactions.
Interestingly, there has been very little evidence to date that firms are implementing personalised pricing on the internet. One possible explanation is that effective techniques to process the mass of available information have not been fully developed. This would help to explain the growth in business analytics courses offered by universities. PricewaterhouseCoopers recently announced its aim to recruit one thousand more data scientists over the next two years.
Another possible explanation is that firms fear a backlash from customers who are deeply opposed to this type of pricing. In a widely cited survey of consumers, 91% of the respondents believed that first-degree price discrimination was unfair.
Articles
Big data is coming for your purchase history – to charge you more money The Guardian, Anna Bernasek and DT Mongan (29/5/15)
Big data is an economic justice issue, not just a Privacy Problem The Huffington Post, Nathan Newman (16/5/15)
MIT’s $75,000 Big Data finishing school (and its many rivals) Financial Times, Adam Jones (20/3/16)
The Government’s consumer data watchdog New York Times, Natasha Singer (23/5/2015)
The economics of big data and differential pricing The Whitehouse blog, Jason Furman, Tim Simcoe (6/2/2015)
Questions
- Explain the difference between first- and third-degree price discrimination.
- Using an appropriate diagram, explain why perfect price discrimination might result in an economically more efficient outcome than uniform pricing.
- Draw a diagram to illustrate how a policy of first-degree price discrimination could lead to greater revenue but lower profits for a firm.
- Why would it be so difficult for a firm to discover the maximum amount each of its customers was willing to pay?
- Explain how the large amount of information on the individual behaviour of customers (so-called Big Data) could be used to predict differences in their willingness to pay.
- What factors might prevent a firm from successfully implementing a policy of personalised pricing?
As most developed countries continue to experience relatively low rates of economic growth by historical standards, governments and central banks struggle to find means of stimulating aggregate demand.
One explanation of sluggish growth in demand is that people on higher incomes have enough of most things. They have reached ‘peak stuff’. As the Will Hutton article linked below states:
Around the developed world consumers seem to be losing their appetite for more. Even goods for which there once seemed insatiable demand seem to be losing their lustre. Last week, mighty Apple reported that in the last three months of 2015 global sales of the iPhone stagnated, while sales of iPads tumbled from 21m units in 2014 to 16m in the same three months of 2015. In the more prosaic parts of the economy – from cars to home furnishings – there are other warnings that demand is saturated.
People on lower incomes may still want more, but with income inequality growing in most countries, they don’t have the means of buying more. Indeed, a redistribution from rich to poor may be an effective means of increasing aggregate demand and stimulating economic growth.
It’s important to clarify what is meant by peak demand for such products. It is not being said that people will stop buying them – that future demand will be zero. People will continue to buy such products. In the case of durables, people will buy replacements when products such as furniture, fridges and cars wear out; or upgraded versions as new models of televisions, smartphones or, again, cars come out; or new music tracks or films as they become available for download, or clothing as new fashions appear in shops. In the case of foodstuffs, concerts, football matches and other consumables, they too will continue to be purchased. The point is, in the case of peak demand, the demand per period of time is not going to grow. And the more products there are that reach peak demand, the harder it will be for companies and economies to grow.
If peak demand has generally been reached, it is likely that the demand for material resources will also have peaked. Indeed, we could expect the demand for material resources to be declining as (a) there has also been an increase in the efficiency of production, so that a lower volume of material inputs is required to produce any given level of output and (b) there has been a general switch towards services and away from physical goods. The graph shows domestic material consumption in the UK in millions of metric tonnes. Domestic material consumption is defined as domestic extraction of resources minus exports of resources plus imports of resources. As you can see, domestic material consumption peaked in 2004.
But, although peak demand may have been reached in some markets, there are others where there is still the potential for growth. To understand this and identify where such markets may be, it is important to step back from simple notions of consumption to satisfy materialistic demand and focus on the choices people might make to increase their happiness or wellbeing or sense of self worth in society. Thus while we might have reached peak red meat, peak sugar, peak cars, peak furniture and even peak electronic gadgets, we have not reached peak demand for more satisfying experiences. The demand for education, health, social activities, environmental conservation and a range of fulfilling experiences may have considerable potential for growth.
There are business opportunities here, whether in the leisure industry, in building networks of like-minded people or in producing niche goods that satisfy the demands of people with specific interests. But without greater equality there may be many fewer business opportunities in the mass production industries producing standardised goods.
This is not a world in which goods and services are produced at scale as conventionally measured, but a honeycomb economy of niches and information networks whose new dynamics we barely understand, even if we have a better grasp of its values.
Articles
- If having more no longer satisfies us, perhaps we’ve reached ‘peak stuff’
The Guardian, Will Hutton (31/1/16)
- Steve Howard, Ikea Exec, Says The World Has Hit ‘Peak Stuff’
Huffington Post, Zi-Ann Lum (20/1/16)
- We’ve hit peak home furnishings, says Ikea boss
The Guardian, Sean Farrell (18/1/16)
- Peak stuff: the ‘growth’ party is over. So what next?
The Ecologist, Bennet Francis and Rupert Read (22/1/16)
- Have we reached peak ‘stuff’?
The Mancunion, Tristan Parsons (22/2/16)
- Ikea senses room to grow amid ‘peak stuff’
Financial Times, Aliya Ram and Richard Milne (18/1/16)
- Peak Stuff
ifs insights, Janet Hontoir (21/2/16)
- UK retail sales soar as Brits splash their cash on ‘fun stuff’
The Telegraph, Szu Ping Chan (19/2/16)
- How less stuff could make us happier – and fix stagnation
The Guardian, Katie Allen (26/4/16)
Questions
- What are the implications of countries reaching ‘peak stuff’ for (a) the marginal utility of mass produced goods; (b) the marginal propensity to consume and the multiplier?
- Give some examples of goods or services where peak stuff has not been reached.
- If peak stuff has only been reached for certain products, does this mean that there may still be considerable potential for stimulating aggregate demand without a redistribution of income?
- Would it be in the interests of companies such as Asda to make a unilateral decision to pay their workers more? Explain why or why not.
- Why may we be a long way from reaching peak demand for housing, even without a redistribution of income?
- Make out a case for and against tax cuts as a way of stimulating (a) economic growth and (b) a growth in wellbeing? Do your arguments depend on which taxes are cut? Explain.
- The Ecologist article states that “Attaining one-planet living will probably involve in due course achieving degrowth in countries such as ours: building down our economy to a safe level.” Could such an objective be achieved through a mixed market economy? If so, how? If not, why not?
- Does the Telegraph article suggest that peak stuff has not yet been reached as far as most UK consumers are concerned?
Economics, but not as we know it. As the introduction to this programme on BBC radio 4 suggests, there has been criticism and concern about the way in which we think about economics. About, how it’s taught; the lessons we learn and whether we need to have a re-think. Tomas Sedlacek is a Czech economist and has a different way of thinking about this subject.
Humanomics is certainly a new way of thinking about economics and considering how it links and can be applied to a wide range of areas: the Bible; movies such as Fight Club and the Matrix. This 30 minute discussion between Evan Davies and Tomas Sedlacek provides some interesting insights and thoughts on some of the current challenges facing this subject and some novel insights into how we could change our thinking.
Tomas Sedlacek: The Economics of Good and Evil BBC Radio 4 (25/01/16)
Questions
- How do we define and measure value? Is this always possible? Can you think of some things where we cannot assign prices or numbers to values?
- How could economics be relevant Adam and Eve?
- Think about the marriage market. How would you apply the model of demand and supply to this most unusual of markets?
- What insights does Tomas Sedlacek provide about the ancient business cycle and this might affect our thinking about debt and assets?
- Do you think that refugees are of benefit to a country? If you don’t think they are of benefit, does this mean that countries should not accept them?
- If we did find out that corruption or crime and terrorism were of benefit to the GDP of a country, would you encourage it? Or would you place the morality issue above the actual figure of contribution?
Recent reports in the media have included headlines such as “Sexist surcharge” and “Pink premium?” Various claims have been made that women pay significantly higher prices for similar products than men.
The Times newspaper recently published the results from an investigation it carried out on the prices of hundreds of similar products that were marketed at both men and women. The study found that those products marketed at women cost 37% more on average than similar versions that were marketed at men. Examples included:
- Disposable razors: Tesco priced a packet of five of its own-brand disposable razors for women at £1. The key characteristic that targeted the razors at female customers was the colour – they were pink. For the same price, a packet targeted at male customers (i.e. they were blue) contained 10 disposable razors.
- Ballpoint pens: Staples priced a packet of five pastel-coloured Bic pens marketed ‘for her’ at £2.99. A packet of five Bic pens that were not in the ‘for her’ range (i.e. they had transparent barrels) were priced at £1.98.
- Scooters: Argos increased the price of a child’s scooter by £5 if it was pink instead of blue.
Maria Miller, the chair of the Women and Equalities Select Committee, stated that:
“It is unacceptable that women face higher costs for the same product just because they are targeted at women. Retailers have got to explain why they do this.”
A more detailed study carried out by New York City’s Department of Consumer Affairs was published in December 2015. Average prices were collected for 794 individual items across 5 different industries. The key findings were that products marketed at women were:
- 7 per cent more for toys and accessories
- 4 per cent more for children’s clothing
- 8 per cent more for adult clothing
- 13 per cent more for personal care products
- 8 per cent more for health products
Interestingly whereas the investigation in the UK only found examples of women paying higher prices than men, the New York study found some goods where the price was higher for men.
Reports in the media have claimed that this is clear evidence of price discrimination. Although this is likely to be true, it is impossible to say for certain without more detailed information on costs.
For example, when referring to the higher price for the razors marketed at women in the UK study, Richard Hyman, an analyst at RAH Advisory, stated that:
“the packaging will be different and they will sell fewer so it could be to do with the volume”
If economies of scale and the different costs of packaging can fully account for the difference in prices between the razors then it is not an example of price discrimination.
Articles
Questions
- Define price discrimination.
- Outline and explain the three different categories of price discrimination.
- Could a situation where a firms charges all of its customers the same price for a good or service ever be classed as an example of price discrimination?
- A firm with market power may still not be able to successfully implement a policy of price discrimination. Explain why.
- Under what circumstances could price discrimination improve allocative efficiency?
Saturday night was a happy one. I had got back from the Kingpower Stadium after watching my beloved Leicester City win and climb back to the top of the English Premier League. It does not get much better than this. My levels of satisfaction are off the scale, at least for now. There is an economics angle here: what affects the level of satisfaction people derive from watching live sport, such as football matches? Satisfaction affects peoples’ preparedness to pay. Understanding this is invaluable to all organisations, including football clubs. Is the Leicester effect good for football?
Economists refer to the satisfaction from consuming something as utility. Understanding how supporters like myself derive utility is vital to the success of football clubs and the industry as a whole. It may, for example, help clubs better understand how to price match tickets or club merchandise and better inform important decisions about the structure of leagues and cup competitions.
According to the BBC Price of Football Survey 2015 there appears to be a high preparedness to pay to watch live football. The report shows that the cheapest season ticket at Arsenal for 2015/16 is £1,014, at Tottenham £765 and at Chelsea £750. You could have bought a Leicester season ticket for just £365. Meanwhile the cheapest match day ticket at Arsenal is £27, at Tottenham £32 and at Chelsea £52. The cheapest match day price at Leicester is £22.
So why can football clubs charge what appear to be such high prices? An important part of the story is considering what influences how much fans are willing to pay. Supporting a club for those like me involves an enormous emotional attachment. I derive a lot of my satisfaction from supporting my home-town team. Supporting another club is not alternative. No substitutes will do: it has to be Leicester. The greater the number of people like me, the higher we can expect, other things being equal, prices to be.
Of course, not everyone is like me. Leicester shirts are seen fairly infrequently outside of Leicester and even as I walk through my home city I am likely to see folks adorned, for example, with Arsenal, Chelsea, Liverpool or Man United shirts. Furthermore, most teams have a section of fans whose interest may wane if the team starts losing and dropping down the league. The responsiveness of match-day attendance to the winning percentage of a team is referred to by economists as the win elasticity of demand. The figure is expected to be positive because if a team’s win percentage improves its match-day attendance should increase.
For some supporters who are considering purchasing match-day tickets the issue may simply be who the two teams playing are. This helps to explain why prices for local derbies tend to be higher. It might also be the case that some matches allow supporters to see particular ‘superstars’. More generally, a rise in the quality of player on show will increase the preparedness to pay.
Another factor that can affect preparedness to pay is the perceived closeness of the contest. Many fans gain particular pleasure from watching their club win a game where they believe the two teams are evenly matched: i.e. where the outcome is very unpredictable. This idea is referred to by economists as the uncertainty of outcome.
As well as the uncertainty of the match outcome, interest and preparedness to pay may be affected by intra-seasonal uncertainty. This is highly pertinent in the English Premier League given ‘the Leicester effect’. Longer term, inter-seasonal uncertainty may also be important. If leagues such as the EPL become less predictable then this may further increase interest among fans.
Of course, the benefits from increased uncertainty may not be evenly felt. While this is probably good for the total preparedness to pay across a league like the EPL – and for the rights to broadcast the league – some clubs might have to adapt should interest in them begin to wane.
Article
Price of football: full results 2015 BBC News (24/10/2015)
Questions
- Draw up a list of the characteristics of watching live sport from which people derive utility (satisfaction).
- How might we measure the predictability of leagues like the English Premier League (EPL)?
- How might an increase in the unpredictability of EPL results affect the preparedness to pay to watch EPL matches?
- Is it in the long-term interest of all clubs for total points collected in the EPL to be less concentrated?
- What is a superstar effect? How would this affect preparedness to pay to watch live sport?
- Analyse what you consider to be the relative importance of the superstar effect and the uncertainty of results in affecting preparedness to pay to watch live football or other sporting events.
- Can we describe football clubs as ‘brands’? How does the nature of a brand affect our preparedness to pay for its products and services?
A number of famous Business Schools in the UK and US such as MIT Sloan, NYU Stern and Imperial College have launched new programmes in business analytics. These courses have been nicknamed ‘Big Data finishing school’. Why might qualifications in this area be highly valued by firms? 
How could a firm go about predicting how much each of its customers is willing to pay? Traditionally smaller sellers might try to ‘size up’ a customer through individual observation and negotiation. The clothes people wear, the cars they drive and their ethnicity/nationality might indicate something about their income. Second-hand car dealers and stall-holders often haggle with customers in an attempt to personalise pricing. The starting point of these negotiations will often be influenced by the visual observations made by the seller.
