Thursday, February 16, 2017

What do consumers value in smartphones?

As part of the Little Book of Value (#LBOV), I am writing a number of case studies, including:

- Value of smartphones - see draft case here
- Value of NBN; national infrastructure
- Value of new products (denting the universe); Apple and iPhone

The #LBOV is a collaborative writing project at Github, but the pics need to be on a URL, so I will post the pics here for linking from Github. Please add you Value stories as a link to this post, or other #LBOV posts on this blog.

Here are the images of what consumers valued in their smartphones. All images CC-BY.
Please also refer to my Phd at Ferrers (2013), full reference at: http://dx.doi.org/10.6084/m9.figshare.680002.



Fig 1. What do consumers value in smartphones? A small sample.


Fig 2. Count of value elements by consumer - the PhD sample.


Fig 3. Comparing value dimensions across consumers - the PhD sample


Fig 4. Theoretical saturation - Value Concepts - the PhD sample


Wednesday, February 1, 2017

NBN coming to Vic 3166 - I made a map. Here's how.

See the map (v.1) I made (with 40 datapoints) at:
https://twitter.com/ValueMgmt/status/827009730870521856 
I made a (v.2) map (with 60 datapoints) at:
https://t.co/zd8F86Z9am

Method

If you want to repeat this for your area, here's how I did it.

Getting Started

  • Lat/Long: I use a Mac, and its Map program provides an easy way to turn an address into a Lat Long. You can also use maps.google.com.
  • Spreadsheet. I used a Google Sheet. You can also load data into excel (csv) and drop into Google Maps.
  • Google Maps. You need a Google login for this.

Making the Map

  1. Create Google Sheet (or spreadsheet) with four columns
  2. A. Address B.Lat C.Long D. NBN Status – in rollout (yes/no)
  3. Get the Lat Long. In Apple Maps, pick an address, Drop a pin = Right Click. Click (i). Copy address into Column A. Copy Lat/ Long in Col B,C. Alternatively, in Google Maps, right click What's here to get the Lat/Long of any point. You can also find a Lat/Long with Google Maps API; by inserting and address into: http://maps.googleapis.com/maps/api/geocode/json?address=ADDR where ADDR = 12carlislecrescent,hughesdale,vic eg Link

  4. Paste address into NBN map checker:
  5. http://www.nbnco.com.au/connect-home-or-business/check-your-address.html
    This gives rollout status. In Hughesdale it was either (1) (Available: Apr – Jun) = yes or (2) (Still finalising) = no.

  6. Paste Address status (yes/no) into Col. D.
  7. Gather a list of addresses you want to map... I did about 25 before I made a map. Then the map helped pick where to check next.
  8. Go to Google Maps: https://www.google.com.au/maps/
  9. -> Menu -> Your places -> Maps -> Create Map -> Add Layer -> select Google Sheet -> indicate Lat/Long fields -> indicate NBN Status: Yes/No field
    This places all your address points on a map.
    Add a title and description to explain what area you are mapping.

  10. Colour code the points into different colours for NBN Status: Yes/No.
  11. Select Layer -> Uniform Style -> Uniform Style -> Style by Data Column -> Col D. (NBN Status).

  12. When you add new data to your spreadsheet, you need to (but maybe there is an easier way) readd the layer: Add layer -> select Google Sheet i.e. repeat Step 6,7. Delete the old layer: Choose layer -> layer options (three vertical dots) -> delete this layer.
  13. Add polygon to show the boundary of rollout for the region.
  14. Post to Whirlpool / Twitter for comments: Maps -> Share -> Change: anyone with the link can View – copy/paste URL

  15. Enjoy!

Friday, January 27, 2017

The Little Book of Value

I am writing a 75 page book on Value to publish by the end of this year (2017).


  • Will be $10 for the plain black and white text copy (eBook at Amazon).
  • Will be $20 for the colourful eBook, with videos, photos, exercises and more.
  • Will be free for the Community Version, where you earn a copy by contributing your value stories.


If you want to be part of the writing process, either:

- comment below with your email, and tell me "what do you value?", or
- make a three minute video and post the link below to the question "what does value mean to you"
- the writing process will be a public community exercise at Github.

By posting, you agree your content can be included (royalty free) in the above books. All included entries will earn the author, 10 copies of the book, so be sure to leave your email.

Add your comments to the wiki or fork the repository. Add your questions about value either in comments below or at Github.

You can see the outline at Github.

Happy New Rooster Year!!

Thursday, January 19, 2017

A new beginning: creating and destroying value

On the eve of the 45th Presidency, it seems appropriate to reflect on the potential for innovation to create and/or destroy value. [1]

I have long argued here that innovation is doing new things that create value. But many new things destroy value. For instance, a tweet saying a President-Elect will cancel a $5B contract sends a company share price down as investors price that information into a stock.

It is harder to create value with new things. At ANDS, we work with Universities to promote the new idea of #openscience and data sharing as a value creator. The idea takes time, effort and investment to implement, which are costs. These costs have uncertain returns, so may create or destroy value. As Gilder suggests, the entrepreneur takes a leap into the future ("Faith of the Futurist", Wall Street Journal, 1999), reaching out to grab some uncertain future potential value.

Of course, Schumpeter talks of "creative destruction" (1942, Capitalism, Socialism and Democracy). So a new industry or product negatively affects what came before. Cars puts horses out of work, as did farm machinery. Agricultural labour fell from 70% of the population to low single digits (say 4-5%) as machinery and mechanisation raised the amount of work a farmer can do. The losses of jobs are destruction of value. The raised productivity of the remaining agricultural workers add value. Similarly, Rogers in Diffusion of Innovation (1962, 2004), quotes Machiavelli, saying (I paraphrase), a new idea has the lukewarm interest of those who may benefit and the criticism (resistance) of those who benefit under the old regime. Thus new things benefit and harm people. New things, new ideas, new products both create and destroy value. The value of those benefiting under the old regime is destroyed (transferred) to those benefitting under the new regime.

The trick for innovation is when there is more than a zero-sum game. When the benefits outweight the costs. Generally we can see this through GDP as those benefits and costs are turned into dollar equivalents. However, value is not measurable in dollars alone. Social, emotional and other types of value exist alongside economic value (see Value Dimensions). So people are concerned, worried, anxious about the new Presidency and his potential actions. Such emotions are temporary negative value, that may be converted into economic value, with consumer outlook an intermediate measure.

What comes to pass, we will have to wait and see. For me, I have set my expectations so low, that I may be pleasantly surprised when a new President does something half sensible. New perspectives bring opportunity for new ideas, new interpretations, new approaches. It remains to be seen whether these will create or destroy value. There is always another election in four years (let us hope).

There is always risk and uncertainty in new things. So let us not judge a person by their words, (which fade away like flowers, the wind, or a wave lapping on the beach). Let us judge a person by their deeds, that will last. Let us let our emotions assess ones words, and tell us whether to like, trust or resist their actions. I have noticed that new leaders arrive full of new ideas, but a real test is what can be put into action, as those ideas have to pass through the value filters of those affected both positively (the promoters) and negatively (the resistors) to those ideas.  This is the social process of creating and diffusing an innovation. A process whereby the value in the idea is assessed by all those affected by it.

[1] I believe we have no word for something new, destroying value (maybe 'denovation', Valman 2009).






Monday, August 8, 2016

Where is the economy growing / shrinking? #AU

The Australian Tax Office (ATO) has recently provided me with a dataset to examine innovation in Australia. I am interested in economic activity over time and by location. Previously the ATO has provided corporate data, but companies are seen only as Australian, and not having a point or multi-point location. Employees however have an address which provides a point location.

Thus the ATO has kindly provided all the salaries and wages data (for 12 years), and sole trader data, by fine detailed industry and location. Sole Trader's have 500 industries and employees have 1500 occupations. Australian locations, while requested at postcode level, were provided at a statistical area level (SA4) which splits Australia into 100 regions of similar population. Cities have many zones, while the country has large zones.

See my request for the data here.

The resulting dataset has two tables:
  • Sole Traders (100,000 rows) 2014 $96B, 2002 $61B.
  • Salary and Wages (200,000 rows) 2014 $584B, 2002 $285B.
The raw data is available here at data.gov.  I have loaded the data into an online database at Nectar, which provides free cloud services for Australian Researchers. Preliminary analysis is taking place at a website set up for that purpose here. For SELECT access to the database please contact me.

Data Visualisation of the Industries of Sole Traders.


See details including rollover to get names of each bubble here.

A Data Visualisation of growth by SA4 region

Figure 1: Growth by SA4 region (2006, 2010, 2014). Data
Data Citation: Ferrers, R., Australian Tax Office; AURIN (2016): Where are Australian jobs growing or shrinking (2002 - 2014; over 100 regions; SA4)?. figshare. Online at: https://dx.doi.org/10.6084/m9.figshare.4056282.v3 Retrieved: 06 05, Oct 27, 2016 (GMT)

Top ten occupations (2010-2014) - growing / shrinking

Top Ten Growing Occupations**20102014Diff
Sales Assistant (General) 235,449 273,104 37,655
Corporate General Manager 162,899 198,595 35,696
Office Manager 145,522 172,883 27,361
Primary School Teacher 121,599 147,589 25,990
Child Care Worker 73,496 92,813 19,317
Aged or Disabled Carer 103,196 121,359 18,163
Labourers nec 72,007 89,238 17,231
Program or Project Administrator 81,640 94,905 13,265
Registered Nurse (Aged Care) 29,605 42,581 12,976
Machine Operators nec 18,764 31,263 12,499


Top Ten Shrinking Occupations**20102014Diff
Practice Managers nec 131,480 73,434 68,722
General Clerk 361,094 326,118 34,976
Earthmoving Labourer 33,313 13,585 19,728
Sales Representatives nec 90,840 74,679 16,161
Nurse Practitioner 35,031 21,767 13,264
Secretary (General) 46,570 33,800 12,770
Farm 33,781 21,038 12,743
Hospitality Workers nec 40,256 28,725 11,531
Clerical and Administrative Workers nec 44,280 32,874 11,406
Checkout Operator 65,242 54,294 10,948
NB**: excludes unnamed occupations. Full List. Data (1162 lines, csv).

Other sample reports

Several sample reports are now available, including;
  • List of Occupations from largest to smallest
  • List of Occupations from highest average wage to smallest
  • List of Sole Trader industries from highest sales to smallest
  • Change in one Industry over time - Hairdressing.
For more information: contact richard.ferrers@monash.edu.

Thursday, February 4, 2016

FTTN vs FTTP (6): the graphical version

After attending a Data Visualisation workshop at University of Melbourne this week (Resbaz 2016; D3 Visualisation workshop, plot.ly workshop; Thanks Isabel and Errol), I have tried to plot graphically the FTTN vs FTTP perspectives. See my outputs here from this week's workshops.

Through playing with the model (available on figshare (v5)), the most important variables seemed to be:

- impact on GDP per household after 20 years
- discounted by an interest rate (0,3,5,10%)
- impacted by a delay in FTTP rollout (0,2,4,6,8 years)
- impacted by Household GDP growth (0,1,2%) externality

as discussed in earlier posts.

Plot.ly: FTTN (blue) vs FTTP (orange). Some assumptions support FTTN (blue). Other assumptions support FTTP (orange).

Datapoints: GDP per household at Yr 20, discounted to current $$; difference FTTN -  FTTP
eg 1. At Year 20, FTTP Delay = 8 yrs, 0% discount rate, FTTP and FTTN GDP impact is $20k per household. Difference is close to $0. A datapoint of $0 is plotted;a brown dot. Where FTTN GDP > FTTP GDP then plot is blue (positive nos). When FTTN GDP < FTTP GDP impact, then plot is orange (negative nos).
eg 2. At year 20, Delay = 6 years, interest rate 5%, household GDP impact 1% pa; FTTP GDP impact is: $13k; FTTN GDP impact is $20k. So the difference ie $7k is plotted; a light blue dot.

The dots are smoothed into colour sections. Blue sections where the assumptions favour FTTN (preferred by the Liberals Party, in conjunction with HFC, some FTTP and other wireless tech for Regions and Remote) and orange sections where the assumptions favour FTTP (preferred by Labor Party). Live version of image, with mouseover datapoints at: Figshare (v5) to download, and Github to view.

Click pic to enlarge


Figure 1,2,3: Stronger colours indicate more value. FTTN vs FTTP GDP per household impact at Year 20, discounted by interest rate; Y axis shows interest rate (discount rate). X axis shows years delay until FTTP installed. Orange zones indicate FTTP preferred. Blue zones indicate FTTN preferred, per model (linked above). Heatmap coded added to Figshare model (v5). Html version shows GDP values at each point. Blogger unfortunately doesn't run javascript. See live heatmap version here.

Data:
var data = [{
  z: [[-12, -9,-6,-3,0],
      [-10,-7,-4,-1,2],
       [-9,-6, -3,0, 2],
       [-7,-3.5,-1,1.5,3]]; // GDP diff FTTN - FTTP $k per HH, 0% HH GDP imapct

       
  x: [0,2,4,6,8], // Delay years
  y: [0,3,5,10]}; // Discount rate
 
z: [[-12, -6.5,2,5,11],
      [-10,-4,1,6.6,11.5],
       [-9,-3, 2,7, 11],
       [-7,-1,4,7.5,11]], // GDP diff FTTN - FTTP $k per HH, 1% HH GDP impact
       
 
z: [[-12,-4, 5,14,22.5],
      [-10,-1.5,6.5,14,21],
       [-9, 0,7,14, 20.5],
       [-7,1,8,14,18]], // GDP diff FTTN - FTTP $k per HH, 2% HH GDP impact
       
Source: Figshare model (manually entered from model into heatmap html);
view source on Github page.
  
What the above figure shows is:
  • at 2% impact on household (HH) GDP ($70k household) then FTTN is highly favourable, even if only short two year delay. The HH GDP annual impact $1,400pa is much larger than around $2,000 difference between FTTN and FTTP capex and dwarfs OPEX and revenue differences.
  • at 1% impact on HH GDP, a four year delay in FTTP installation is sufficient to favour FTTN over FTTP.
  • at 0% impact on HH GDP, then FTTP is favourable even with long delays to FTTP. At higher interest rates, then a shorter delay for FTTP is equivalent to FTTN.
In previous cost benefit analyses of NBN, a 0.5 - 1.0% impact on GDP was sufficient to make the NBN NPV positive - ie benefits exceed costs, accounting for time impact of cashflows. At these lower household impacts, FTTP is preferred, but where there are immediate significant household GDP impacts ( ie more than 1%) then FTTN is preferred. Long delays in FTTP encourage more use of FTTN, as do higher interest rates.

NB: outstanding and unaccounted for issues were described in the last post, eg cost of replacing FTTN at the end of its perhaps 10 year life; the excess benefit of FTTP over FTTN, and so on.

Conclusion:
FTTN and FTTP are only as good as the assumptions that assert their case.  There are many cases, listed above where FTTN is better than FTTP for GDP over 20 years. Where the NBN impact on household GDP is significant, this prompts an earlier install of FTTN.

Sunday, January 24, 2016

FTTN vs FTTP (5): cheaper now or faster later; a value clash of assumptions

[NB: Best viewed for iPhone in Reader view.]
This is likely the last post in this series, and adds another element to the value assessment.
So far, I compared FTTN and FTTP based on CAPEX, OPEX and Revenue. I aggregated those costs to get a GDP impact. I applied an interest rate to compare cashflows over time. In this post, I add an external GDP impact (an externality) to a household with NBN. The Prime Minister argues for FTTN now, rather than the delay of FTTP. He sees a benefit now, rather than waiting. The analysis so far shows over the longer term, except in an extreme delay (eg 8 years), FTTP is preferred.
Source: wikimedia

However, if an extra boost to GDP comes from getting FTTN early, how much does that change the picture? I modelled a 1% and 2% increase in household GDP for the years between FTTN and FTTP.
That is, if a $70k household generates $700 extra benefit (1%) from using FTTN does that justify FTTN over FTTP? I updated the model to add a household (HH) GDP impact, then tried to find what HH GDP impact makes the GDP impact of FTTN the same as for FTTP. I used both 0% and 10% discount rates. An update to the model  (v4) is now provided which included a GDP boost (variable) for FTTN in the years pending FTTP delay.

Where you end up with is a clash of assumptions. One set of assumptions favour FTTN. Another set of assumptions favour FTTP. I tried to find the line, where the assumptions balance out. Therefore, increasing or decreasing an assumption will point to either FTTN or FTTP. Then the argument becomes which assumptions (or set of assumptions) do I believe/trust/support.

In short, FTTN vs FTTP is a marshmallow test. The marshmallow test is a classic child test. Do you want one marshmallow now, or wait to get two marshmallows? Do you want FTTN now, or wait to get FTTP?

Figure 1: Children wrestle with the Marshmallow test. Some (FTTN) now or more (FTTP) later.

Let's see how the numbers change, when you add some household boost to GDP, on top of revenue paid to NBN Co for FTTN.

I use two interest rates for the assessment of extra HH GDP; 0% and 10%. Later I will add in 3% and 5% in a summary. The first two Tables show interest at 0%. FTTP  figures do not change, since the HH GDP is increased only for the time until FTTP is available. I assume no extra benefit for FTTP, since I have no basis for those figures. The GDP impact benefits come from earlier NBN Cost benefit analysis I have done. They showed a 0.5-1% increase in GDP was needed to make NBN cost benefit analysis positive (DCF basis). See links to Whirlpool NBN Costs Benefit summary.

GDPDelay = 0yrs2 468
Yr 10FTTNFTTPFTTNFTTPFTTNFTTPFTTNFTTPFTTNFTTP
$'000$'000$'000$'000$'000$'000$'000$'000$'000$'000
0%101810151012109106
1%1018131515.512189216
2%101815.5152112279326
Table 1: Year 10: GDP: with GDP boost to FTTN: 0% Un-discounted cash generated by one FTTN or FTTP household at Yr 10, given delay of installing FTTP. Shaded column indicates better outcome.


GDPDelay = 0yrs2 468
Yr 20FTTNFTTPFTTNFTTPFTTNFTTPFTTNFTTPFTTNFTTP
$'000$'000$'000$'000$'000$'000$'000$'000$'000$'000
0%20322029202620232020
1%20322329252628233120
2%20322529312637234220
Table 2: Year 20: GDP: with GDP boost to FTTN: 0% Un-discounted cash generated by one FTTN or FTTP household at Yr 20, given delay of installing FTTP. Shaded column indicates better outcome.

What these tables show is that extra GDP significantly improves the FTTN proposition.
The 0% is the base case, and the 1% and 2% show major financial gains, the greater the longer the delay in FTTP. Where previously at Yr 20, FTTP was always better except where the delay was 8 years then FTTP and FTTN were the same. With extra GDP, even a four year delay can be enough at high extra GDP for FTTN to be more attractive.

Let's look at how the numbers change if we charge a high interest rate of 10% on each years cashflows. Now all the GDP figures are lower, since later cashflows are worth a lot less. High extra GDP will make a large difference, since the cashflows are early. The longer the FTTP delay, the less GDP (discounted at 10%) generated by FTTP.

GDPDelay = 0yrs2 468
Yr 10FTTNFTTPFTTNFTTPFTTNFTTPFTTNFTTPFTTNFTTP
$'000$'000$'000$'000$'000$'000$'000$'000$'000$'000
0%71379.5777472.5
1%71399.5117134142.5
2%713129.5167194222.5
Table 3: Year 10: GDP: with GDP boost to FTTN: 10% Discounted cash generated by one FTTN or FTTP household at Yr 10, given delay of installing FTTP. Shaded column indicates better outcome.


GDPDelay = 0yrs2 468
Yr 20FTTNFTTPFTTNFTTPFTTNFTTPFTTNFTTPFTTNFTTP
$'000$'000$'000$'000$'000$'000$'000$'000$'000$'000
0%9169139109896
1%91612131410158176
2%91614131810218246
Table 4: Year 20: GDP: with GDP boost to FTTN: 10% Discounted cash generated by one FTTN or FTTP household at Yr 20, given delay of installing FTTP. Shaded column indicates better outcome.

What Tables 3 and 4 show is a much improved FTTN proposition at 10% interest rate. FTTN is now preferred at Delay of 4, 6, and 8 years, and even a two year delay if the GDP boost of FTTN is high.

This raises the question - where to draw the line between FTTN and FTTP? On reflection and through playing with the model I can show the assumptions where the GDP (discounted) for FTTN becomes the same for FTTP.


GDPDelay = 0yrs2 468
              





Yr 10i=10%i=5%i=3%i=0%
Yr 20i=10%i=5%i=3%i=0%
Table 5: When does GDP (FTTN = FTTP)? What interest rate (discount) equates to years delay to FTTP?

What I tried to show in this table is what interest rate charged on cashflows make the GDP impact  of FTTN = FTTP.  Thus at Yr 20, with no interest FTTN and FTTP have the same GDP impact, when FTTP is delayed eight years. When a high interest rate is used on the cashflows (10%), then FTTN is the same GDP effect as FTTP, when the delay is only four years.

In the next table, I compare how much extra GDP boost would FTTN require for the GDP impact to be the same as FTTP.

GDPDelay = 0yrs2 468
FTTN=FTTP



















Yr 10i=10%FTTP > FTTN1-2% (High)0%(Low)
FTTN > FTTP
FTTN > FTTP
i=0%FTTP >2-3%(High)0-1%(Med)
FTTN >
FTTN >
Yr 20i=10%FTTP >1-2%(High)0-1%(Med)
FTTN >
FTTN >
i=0%FTTP >3-4% (High)1-2%(High)0-1%(Med)0%(Low)
Table 6: When does GDP (FTTN = FTTP)? What GDP boost to FTTN equates to years delay to FTTP?

What Table 6 shows is that FTTP and FTTN are favourable based on different assumptions.
FTTP is favoured when there is no delay and when interest rates are low. When only a two year delay to FTTP, then FTTN needs high GDP boost to be equivalent. When delay is four years, GDP is roughly equivalent at high interest rate, but requires medium GDP boost at low interest after ten years. After 20 years, FTTN needs medium or high boosts to be equivalent to FTTP.

FTTN is favoured when delay is six or eight years, when interest rates are high (10%), or when boosts to GDP are high.  Previous cost benefit analysis showed a 0.5-1% boost in GDP was needed for NBN to be successful (ie DCF positive).

Conclusion:
FTTN as an alternative to FTTP is significantly boosted by including a 1 or 2% GDP boost from FTTN now up until a delayed FTTP rollout. A high interest rate (10%) also makes FTTN more attractive if delays to FTTP reach four years.

So, cheaper now(FTTN) or faster later (FTTP), is complex. The model now accounts for:
  1. OPEX, CAPEX and Revenue
  2. Delay in FTTP install
  3. Life of assets (but not replacement of FTTN)
  4. Interest rate (ie DCF discounted cashflows_)
  5. Impact on GDP based on OPEX, CAPEX and Revenue
  6. a GDP boost from NBN
Like the marshmallow test, less now (FTTN) and more later (FTTP) is a value tradeoff, which is personal, subjective and complex. Accounting for a short term GDP boost from FTTN makes a significant difference.

What is not yet counted? More factors can be taken into account. Some hard. Some very hard to assess or estimate.

Hard: what cost to replace FTTN with FTTP and when? eg $4k FTTP CAPEX inflated at 1,3,5%pa, discounted at 0,1,3,5,10%, at Yr 10, 15, 20.
Too Hard: how much more GDP impact will FTTP have over FTTN?
Too Hard: how much customer satisfaction will FTTP and FTTN create?
Too Hard: how to compare customer satisfaction with $$?