In God’s Name

Sometimes I feel sure that one day God will lose patience, forget that he promised to not get angry and destroy everything and come down to see his creations and tell us

HOW DARE YOU do these VILE things and have the TEMERITY to say it is in my name? IN MY NAME?

The shocking events this past weekend need no further deliberation. It takes an especially disturbed mind to indiscriminately shoot at children. Children. Who probably did not even understand what was going on.

Now, much has been said about the terrorists and the usual “Islamic militants” label bandied around.

There have been tweets and Facebook posts saying absurd things like “Not all Muslims are terrorists, but all terrorists are Muslims”.

This is patently and demonstrably false.

No religion holds the monopoly of misguided fundamentalism.

Religions have been doing unspeakable things to each other from the beginning of time, and happily invoking God’s name in the process.

Examples abound.

Crusades

Look at the Crusades. Christians and Muslims did SHOCKING things to each other. And to innocents. Including raping and torturing women and children, burning alive and other vile acts.

As a matter of fact, there are Christians who fought each other.

In the name of God.

Look at the Inquisitions.

Catholics tortured, maimed and killed Jews and Muslims.

In God’s Name.

Look at the English reformation.

Protestants tortured, burned alive and killed Catholics. Who promptly returned the favour when they got into power.

In God’s name.

Read about the painful process of the formation of the state of Pakistan. Atrocities from both Hindus and Muslims.

In God’s name.

Have we forgotten Timothy McVeigh? Okahoma bomber? Before he was executed he requested a Catholic sacrament.

Remember Anders Behring Breivik, who killed 69 (mostly teenagers) in Norway? Calls himself  “100% Christian”

I would urge people to get to know each other’s religions and beliefs. Get to know. Not convert. At least understand where they are coming from.

It is truly the height of arrogance to commit the most atrocious of acts and then excuse yourself claiming you are doing it in God’s name.

If you’re a Christian, read a Koran. If you’re a Muslim read a Bible. Read the

Bhagavad Gita. Read the Tripitaka.

It costs you nothing. And you will be the better off for it.

Terrorists win not when they shoot innocent people – but when those who ought to know better give in to ignorance and bigotry.

50 Shades of William’s Grey

William Ruto, I feel sure, is a nice man, with robustly functional tear ducts.

However the news that 50 MPs are going to accompany our gallant leader as he attends to personal but pressingly urgent business at the Hague is not news I have received well.

50 out of 220 MPs, by the way is 22.7, % of our national assembly.

Take it away, Jackie Chan

This offends my sensibilities, and should offend yours too.

First of all, your MP is earning that big fat salary because you put him there to serve you and your constituents. He should be earning that top dollar doing his core business – representing his constituents and legislating.

Uhuru Kenyatta is on record as saying this ICC business is a personal matter. How then can 50 MPs justify taking 21 days of their employer’s time to attend to someone else’s personal matter?

Ludicrous.

The work ethic of our MPs is lackadaisical at best unless it comes to business to do with their on well being. There their enthusiasm is impressive.

This is an insult to their constituents that they are not going to go through the motions of pretending to earn their princely salaries.

Ludicrous.

Given they will be away for three weeks, I feel sure that they will not only be paid their salaries, they will also claim handsome per diems, all at the expense of you poor fools, the tax payers.

Ludicrous.

Let us crunch some numbers.

First let us round up the minimum wage to 15,000 for ease of calculations. When I say monthly wages, form here on in, I will mean this.

Let us assume, in a fit of insanity, prudence was the watch word and they tried to get the cheapest flight.

From Kayak.com, this would be Emirates, at about 126,000. This works out to the monthly pay of about 9.

Given that there are 50 MPs, this works out to a clean 6,300,000. Yes, that’s 6.3 million bob. This works out to the monthly pay of 420 people.

Now we all know the one thing our MPs cannot be accused of is modesty. These fine ladies and gentlemen will not want to rub shoulders with the unwashed masses.

A business class ticket is 294,000. This is the monthly pay of about 20.

As there are 50 MPs this works out to a clean 14,700,000. That’s 14.7 million shillings. This is the monthly pay of about 980.

So, air travel budget minimum – 14.7 million.

Let’s move on.

These fine species of leadership will require room and board.

As befitting the status they fondly imagine as deserving, it is unlikely they will accept the hospitality of Nienke’s Bed, Breakfast, Bar & Grill. They will stay somewhere more appropriate.

Let’s look for a hotel at the Hague. How about Crowne Plaza? There is a king bed, 2 bedroom non smoking suite. Perfect for a 3 week stay. That’s 350 Euro. Which is about 40,000 a night. This is the monthly pay for just under 3 people.

Given there are 50 MPs, 40,000 a night works out to 2,000,000. 2 million shillings. Given they will be staying there for 3 weeks, this works out to 42,000,000. That’s 42 million shillings. This is the monthly pay for 2,800 people.

So, accommodation – 42 million shillings.

Adding air travel of 14.7 million, we are up to 56.7 million.

Our gallant friends will no doubt claim travel per diems for entertainment and miscellaneous items.

From this article going back to 2011, the rate was revised to 1000$ a day. I cannot seem to find a more up to date rate. So let’s use that one.

1000$ @ 87 /- to the dollar over 21 days for 50 MPs tips the scale at an impressive 91,350,000. That’s 91 million bob.

Take it away, Jackie Chan

This number is so outrageous I will assume that MPs will get 100$ a day in allowances to cater for taxies and miscellaneous expenses.

So, our grand total for air travel, accommodation and allowances is 65 million bob.

That is the monthly pay for 4,300 Kenyans.

Unwisely used pissed away in a mere 3 weeks.

Ludicrous.

65 million bob can pay the minimum wage for an entire year for 360 Kenyans.

Assume 30% of all of Kenyan’s salaries is lost to income tax, VAT, excise etc.

Let me put this in perspective.

A Kenyan working minimum wage will pay 4,500 in taxes.

It therefore takes about 14,500 such Kenyans working for a month to foot this bill.

Or alternatively, it takes about 1,200 Kenyans working minimum wage working for a YEAR to foot this bill.

It takes 360 Kenyans earning 50,000 working for a YEAR to foot this bill.

It takes 180 Kenyans earning 100,000 a YEAR to foot this bill.

If you earn a million shillings a month – congratulations. It will take a year for 18 of you to foot this bill.

The CEO and CFO of Kenya airways who between them pocket 6.3 million a month – will take them just under 3 years to foot this bill.

My mind has refused to comprehend the absurdity of this situation. MPs who are meant to serve us not only absconding their duty, but wasting our money and vomiting on our shoes to boot!

Amazing!

Being Online Does Not Make Media Digital

Consider a newspaper.

Publishing a newspaper has certain constraints

  1. Size. Most newspapers are A4. This places some limits on content
  2. Pages. Newspapers have a finite number of pages per issue, usually constrained by costs of production. This places a limit on content.
  3. Frequency. Newspapers are committed to a timetable, usually once a day
  4. Static. Once it is printed, you can’t do anything until the following day
  5. To adapt to the above constraints, there needs to be prioritization when it comes to content. Typically advertisers, “hot news” and content conformant to the editorial policy (official and unofficial) wins.

Enter the advent of technology and the internet.

One would think that now, 2013, newspapers would have evolved to fully capitalize on changes on technology.

But no. Inexplicably, they snatch defeat from the jaws of victory.

  • Online versions of newspapers have page numbers. PAGE NUMBERS. Why? This is for no benefit to readers. It is to artificially skew page hits.
  • Online versions of newspapers have the exact same content as the print version. Right down to the typos and grammar errors.
  • Online versions of newspapers as well seem to have a daily cycle.
  • All this despite the fact that there are no constraints of size and space on the web

To me, this is a HUGE missed opportunity.

Most media houses understand digital by having the newspaper online and slapping on blogs and YouTube.

WRONG!

Perhaps the issue is fundamental. Should it at all, in fact, be thought of as an “online newspaper”?

The world has evolved. Industry has evolved. Consumers have evolved.

The distinction between “online” and “print” is largely becoming an arbitrary one.

Perhaps the answer is media houses should think of themselves as content generation and delivery engines. How it consumed (print, web, audio, video, images) is a decision best left to the consumer.

Take for example a hypothetical case of EABL launching a new Whisky, Green Label.

In 2000, a media house would send a reporter and a cameraman to the launch. The reporter will listen to the speech from the MD. There would be the obligatory photo of the MD holding the new bottle. The reporter will ask a few follow up questions and do some research.

The reporter and cameraman will then return to the newsroom. Reporter will write a 2,500 piece on the launch and file his story.

The following day a 1,000 word piece would appear, after editing, in the business pages.

In 2013 what should happen is that the journalist should have a decent camera. And a voice recorder. He should start by touring the plant. Interviewing employees. Some on video. Some by audio. He should take photos. He should record the speeches. He should interview as many people as he can find, no matter how remote their connection to the launch. He should obtain an org-chart electronically. He should dig deeper. Why Green Label? What other names had they shortlisted? Who was involved in the product? Are there any more planned?

When he returns to the newsroom, he should have video, audio, photos and text. He will still then proceed to write his 2,500 world story.

However, the print paper still only has space for a 1,000 word piece. So it is edited.

Which is fine. But what should happen is that in the online portal, the 2,500 piece should be filed. Together with selected photos and video.

If the media house has a TV arm, they will have video and audio and photos to borrow from to run the story during news.

If the media house has a radio arm, they will have audio to borrow from to run the story.

And the final benefit is that the media house has a fantastic resource repository about EABL from this one story that will continue to be used for the immediate future.

If anyone is doing a story on EABL they are spoilt for choice when it comes to content.

That is what should happen. What happens now I bet is exactly what happens in 2000.

Notice that there is no distinction between digital and analog journalist. There is just a journalist. The content is just repurposed for delivery mechanism.

A media house that has digital and print divisions is likely on the wrong path. There shouldn’t be such a distinction, if the media house is to remain relevant.

The other issue is revenue.

I personally used to buy the Nation and the Standard daily. Until one day I realized that I was spending 100/- daily on newspapers. Auditing what I was paying FOR left me in no doubt I was not wisely using my money.

The newspaper essentially contains what happened. Seldom does the newspaper cover why it happened, or what it means going forward. This may or may not be due to the constraints I have talked of above. It could also be due to the quality of journalists. Or the interests of advertisers. Or quality of editors. Or any combination thereof. Point is, I decided 100/- a day on 40 odd pages, largely full of ads and short blurbs of news made no sense.

Especially given that the content was freely available online.

The Nation I remember tried to charge for online access to the newspapers and readership dropped like a stone.

This should have communicated that the problem is not the medium. It is the content.

With an online medium available, media houses should work hard on adding value to content, and not more content. I mean Analysis. Video. Audio. Maps. Electronic documents.

Media houses should realize that they are no longer the first port of call when things happen. People discover things faster on twitter and Facebook and all these social networks. Those not on social networks find out from WhatsApp and text.

Media cannot fight this. Therefore it should leverage it.

You may find out about events on twitter, but if you want to know why it happened and what it means, come to us.

Take something like Konza as an example. It is amazing that no media house has built a complete repository on this. Where is Konza? Here is a map. How will it look like? Here is a 3D model. Who started it? Here are their profiles and photos. What have people said about it? Here are some blogs. Which firms are working on it? Here are their company profiles and key staff.

Imagine all this in a single location. Text, video, audio, maps, blogs, documents. Together. Immersive.

I refuse to pay 50/- for political headlines, Pulse (no offence), ads and 500 word blurbs.

But for curated, immersive, complementary content? You bet your ass I’ll pay. And happily.

A smart media house should figure out there are people like me who have zero interest in socialites, scandals and shenanigans like pulse and prefer business and analyses.

Correspondingly there are those who have zero interest in business and analysis and want nothing more than scandals and socialite intrigues.

Why not have a concept of content channels?

  • News
  • Politics
  • Business
  • Entertainment
  • Sports

The problem today is that I am forced to pay for all 5 and only read one, and even that one I find wanting. So I stop buying the paper.

Suppose you were charged 10/- per channel? Now we’re talking. You only consume what you want. Everyone is happy. In fact, why should they all be 10/-? Charge entertainment 5/- and get volumes.

The problems media faces today boil down to three

  1. How do we effectively collect content (not necessarily ourselves)
  2. How to we add value to it?
  3. How do we retrain and repurpose our personnel to do 1 and 2?

I have much expectations of the new Nation website. Have they learnt anything or is the old emperor in the new skin?

It is too early to tell. I guess we’ll see

Paying Unemployed, Healthy Graduates

Let’s crunch some numbers.

So there is this story in the Standard, captioned thus:

“Jobless graduates to earn 15,000”.

My reaction to yet another half baked policy from our Jubilated administration is, unsurprisingly,

This idea actually verges on the absurd.

Let us begin from fundamentals.

If i understand this correctly, if you are an unemployed graduate, you will receive 15,000 iron men either in your bank account or MPesa to cushion you from the effects of your joblessness.

Absurd.

First of all the minimum wage, as of May 1 2013, is 13,674. Unemployed graduates will be paid 15,000. This means, the payoff is greater than the minimum wage. Which means:

  1. Without doing anything, graduates will already make more money than folks on minimum wage
  2. There is little incentive to get a job immediately
  3. Only a foolish graduate will remain employed if they earn minimum wage.

Then, let us look at the numbers.

Data from a recent World Bank report shows that more than 800,000 people get into the job market each year. The huge jobless market competes against 50,000 employment positions in formal employment.

This means that of the 800,000 people, 50,000 will get formal employment, leaving 750,000 split between unemployment and informal employment.

If i was unable to find a job i have the following options

  1. Get into self employment
  2. Get into semi-formal & casual employment
  3. No nothing & claim from government

Option 3 is now viable given that I will be paid 15,000 for doing nothing.

However, given the nature of humans I can guesstimate 90-95% of the 750,000 will take either option 2, option 3, or both.

Now, let us consider the worst case scenario.

Let us say 95% of these 750,000 claim the 15,000 (include those who only claim as well as those who claim and work on the side).

This is

750,000 * 0.95 = 712, 500

If each of these claim the 15,000 that works out to

712,500 * 15,000 = 10,687,500,000.00

That is 10 billion shillings. A month.

Spread over a year that will be

10,687,500,000.00 * 12 = 128,250,000,000.00

That is 128 billion shillings a year.

Chew on that.

Let us go on to consider the fact that nowhere has it been specified that these payments will begin with graduates of class of 2014. It is perfectly reasonable to assume that there are graduates going back all the way to say 2004 that have been unable to find jobs as of 2014.

Let us guesstimate a bit. Let us assume the number of graduates grows by 10% every year.

So let us project backwards to 2004

2014 800,000
2013 727,273
2012 661,157
2011 601,052
2010 546,411
2009 496,737
2008 451,579
2007 410,526
2006 373,206
2005 339,278
2004 308,435

 

Let us then assume that the rate of unemployed graduates remains the same, which is about 0.63

So, the numbers going back to 2013 are as follows:

Year Total Graduates Total
Employed
Total
Unemployed
2014 800,000 50,000 750,000
2013 727,273 45,818 681,455
2012 661,157 41,653 619,504
2011 601,052 37,866 563,186
2010 546,411 34,424 511,987
2009 496,737 31,294 465,443
2008 451,579 28,449 423,130
2007 410,526 25,863 384,663
2006 373,206 23,512 349,694
2005 339,278 21,375 317,904
2004 308,435 19,431 289,003

 

So, if we further guesstimate that 90% of them never found work, the numbers would look as follows

Year Beneficiaries
2014 675,000
2013 613,309
2012 557,554
2011 506,867
2010 460,788
2009 418,898
2008 380,817
2007 346,197
2006 314,725
2005 286,113
2004 260,103
TOTAL 4,820,371

 

Remember we are gesstimating a worst case scenario.

So, potentially there are 4.8 million unemployed graduates going back all the way to 2004.

To pay them for the fiscal year of 2014 that would set us back

4,820,371 * 15,000 * 12 =

867,666,735,394.67

That’s 867 billion shillings, which is roughly 10 billion dollars in spending for 2013 on this program.

The entire budget for 2013-2014, by the by, is 1.45 trillion shillings. More than half will be used on this program, from our guesstimation.

So, it doesn’t take a rocket scientist to see that this policy is in no way shape or form, sustainable.

Finally, there are a number of other issues this program raises

  1. We are paying able bodied, potentially productive society members to stay at home?
  2. We are poisoning the pool of labour that earns below 15,000 a month
  3. This program will be roundly abused
  4. That 15,000 will likely be consumed on subsistence. In other words will probably not make any returns

Remote Internship

My company, which develops software in the finance and investments sector is piloting a remote internship program.

This basically means you, a student, will work with us remotely without having to physically come to our office. This means you don’t even have to be on holiday.

The software we build makes use of the usual (programming, database etc) and over and above that we are using artificial intelligence, machine learning, econometric models, mathematical models, network analysis, human behaviour and lots of other interesting disciplines.

Wanted: a student studying any of the following

  • Mathematics (actuarial science, statistics, etc)
  • Technology (computer science, etc)
  • Economics
  • Psychology / Philosophy
  • Law
  • Finance (Commerce, etc)
  • Any discipline you can convince us is relevant to the above

The work for the non-technology types will typically involve a lot of research, analysis, proving / disproving of hypotheses, co-relations.

For the technology types the work will involve all the above plus algorithm analysis, design and programming.

What You Will Get

  • Practical experience in not only your area of study, but related disciplines
  • Hard skills (analytic thinking, research
  • Soft skills (public speaking, report writing)
  • Work on live projects
  • Industry exposure
  • Mentorship
  • A small stipend

Send a well written essay of why you should be considered, and what value you will bring to rad@innova.co.ke

WTF, NSSF?

Reading the papers these days is an exercise for those who are not faint of heart.

Half of the time you react as follows:

For instance, there is this story of NSSF.

You will react as above if you crunch the numbers from snippets in the story.

Managing Trustee Tom Odongo says the form will cut its payroll further after shedding 315 jobs since April through a voluntary retirement plan.

Further in the story

The fund will save 1.5 billion annually in wages from the first phase of job cuts.

Assuming these savings are from the aforementioned employees, this means that on average the folks being cut pocketed an average of

1,500,000,000 / 315 / 12  = 396,825.40

Every month.

This is not bad money.

Let’s read on

The fund had 1,700 employees in December and its administrative costs in the year to June 2011 stood at 5.2 billion compared to 6.8 billion remitted by workers in the same period.

Let us graph this

image

Now, if 5.2 is being spent on administrative costs out of the 6.8 billion, this means only 1.6 billion is available for investment

Let us graph this so you can see what that means

image

In other words, out of every 1,000 shillings Kenyans contribute, 765 go to administrative expenses and only 235 shillings are actually invested.

This invested money by the way is what is meant to pay out your pension.

Just think about that.

So, 76% of our contributions vanish the instant they hit the account.

Amazing.

Let us read on

Employee expenses were more than 2.6 billion

If we couple that with the fact that there are 1,700 employees this means that the average salary at NSSF from cooks can cleaners all the way to the CEO is

2,600,000,000 / 1,700 / 12 = 127,450.98

The average salary at NSSF is 127,450/-

Yezzir.

Remember also that NSSF wants to jack up the contributions to about 12% of your salary.

The band of lucky folks who earn 150,000 and above will pay about 18,000.

Currently you pay 400.

If we graph this

image

This represents a whopping 4,400% increase

Now, if you fondly believe this will not affect you let me disabuse you of that notion.

The way NSSF works is that you contribute and your employer matches your contribution.

Which means if you have to contribute more, your employer must contribute more.

No additional money has magically appeared in your employer’s coffers.

2 things will necessarily happen.

  1. Your net pay is going to go down
  2. Since your employer will have to look for more money to pay you, you can consider maintaining your gross salary as your raise for this year.

Mining MPesa Data For Fun & For Profit

If you haven’t already, read KRA, Safaricom & You. Go on. I’ll Wait.

That post has raised quite a bit of interest, and so, a follow up.

First of all, there is nothing wrong with data mining. If you are a serious company you hire a guy like me to crunch your data and give you new, non-obvious insights. You will get insights like

  • How to target your products
  • Which to discontinue
  • Which to invest in
  • Whether an advertising campaign is working
  • Usage patterns
  • Purchase patterns
  • Customer patterns
  • etc

What I OBJECT STRONGLY to is government mining our transactional information because we might be evading taxes. And so should you!

Now, let us get back to MPesa. I would like to discuss data mining in a bit more detail.

Again, I’m using MPesa because the numbers from the other providers are of nuisance value.

An MPesa transaction has the following information

  • Date
  • Time
  • Sender phone number
  • Recipient phone number
  • Amount
  • MPesa Outlet

To register for MPesa, or indeed to get your line you provided a raft of information about yourself. The interesting bits are

  • ID Number
  • Name
  • Date of birth
  • Gender

Let us look at that MPesa outlet. An MPesa outlet, obviously, must register itself. Therefore the following information is available

  • Outlet name
  • PIN Number
  • Physical Location
  • Owner name, ID number
  • GPS Co-ordinates *
  • Opening time *
  • Closing time *

The starred items are what I am not sure Safaricom collects, but if i were them, I would.

Now, 6 months of this data is data mining gold. I’d frankly be astonished if Safaricom did not mine this database.

There are some quick, obvious things that you can derive to improve service delivery.

Which MPesa outlets open on time

Given an outlet that claims to open at 8, if the earliest MPesa transaction on a daily basis is between 9 and 9-30 over a continuous period, it is likely that outlet does not open on time

Which MPesa outlets close on time

Same as above. Only for closing time

Which MPesa outlets should be closed

Given you have the GPS co-ordinates, you can position the MPesa outlets on a map. If you find there are four next to each other, A,B,C and D, and A,B and C do on average 30 transactions a day but D just does 5, you can probably close D

Where do you need more MPesa outlets

Example as above. If you find A,B,C and D are processing transactions continuously from opening to closing time i.e. there are no hourly spikes, cross references with the average number of processed transactions across outlets, it is likely they are working flat out in which case you might need more outlets to absorb the load

Which MPesa outlets have a demographic profile

This is more interesting. Since you have the sender’s details you can derive things like what is the modal age of customers at a particular MPesa outlet. By modal age I mean get the age of the sender, and find out how frequently that age occurs.

In other words, you can find in a particular outlet, most visitors are between 25-30 and in another most visitors are 18-23 and in another 40-50.

This is useful information for any competent marketing person. Or a practical person e.g. in the place where most visitors are 40-50 Safaricom can advise the outlets to get chairs for customers to sit on as they wait.

Which are the peak times for transactions

Self explanatory. You might find for example on average an outlet does 10 transactions an hour but at lunch time it spikes to 200. Then it drops back to 10.

You find this outlet cannot handle the spike so customers have to queue.

Dilemma. If you open a second outlet, it will likely be idle. If you do nothing – customer dissatisfaction.

Solution: something like a portable MPesa outlet (a van or something) that can go there at lunch time, absorb the load and then leave)

What is the average time it takes to complete a transactions

Self explanatory. If you remember the initial forms to fill they collected a lot more detail than they do now. Someone must have analyzed these numbers and optimized the process.

And so on. There are tons of other things that you can look out for but those examples should suffice.

Let’s move on to the transaction themselves.

Remember this information is at your disposal

  • Sender name
  • Sender ID number
  • Sender gender
  • Sender age
  • Recipient name
  • Recipient ID number
  • Recipient gender
  • Recipient age
  • Amount
  • MPesa outlet name
  • MPesa outlet location

Armed with a bit of mathematics, economics, psychology mining this information will yield a GOLD MINE of information. Let me re-iterate – anyone with access to both this data and data mining expertise OWNS YOU.

If that alone is a gold mine, Safaricom is sitting on a gold mine next to oil and platinum deposits for the excellent reason that they also have access to your call records.

In other words, they can cross-reference your call and your MPesa records and mine that bad boy still further. Add to this the SMS database and this is paradise.

You can derive a treasure trove of information from this, over and above the examples I gave in my previous post

Over and above who are you sending the money to, there is a lot of context to be gleaned if we can guesstimate why you are sending the money.

Let us take an example of how end to end mining would work.

Let me again repeat– data mining is premised on PROBABILITY, not certainty. Some of the assumptions may be wrong. But usually, you can derive pretty good confidence levels

0721 000000 sends 5,000 to 0722 000000 at 2.00 AM, via his phone.

Let’s get started.

First of all, let us build a profile of both sender and recipient.

0721 00000 maps to John Kamau, aged 37. He has been a customer since 2000.

0722 000000 maps to Jamie Omondi, who is not a male as first thought, but a female, aged 32, a customer since 2003.

Next, let us analyze the context.

A 2.00 AM transaction is unusual. This is unlikely to be paying for something. Let us hop over to the phone logs database. Aha. John and Jamie have in the past made calls to each other.

We can therefore infer that they know each other. Therefore that transfer was probably either some emergency or Jamie had a pressing bill that she needed to pay.

The next bit is to check if there are any subsequent transactions where Jamie is the sender.

Oho! Lipa Na MPesa till number 000000 received a payment of 4,500 from Jamie 5 minutes after she got the money from John.

Have there been any other payments from Jamie to that till number? Yes. On average, twice a moth, over a 6 month period.

From the till number we can determine the business it was registered to. Turns out it is Sky Lounge, a swanky bar.

Have there been any other payments to tills belonging to bars? Yes! 6 other bars / hotels over the same 6 month period.

We can then infer that Jamie probably drinks. Given the profiles of the outlets she drinks at, she probably doesn’t drink Senator, but more likely spirits and cocktails.

So, if Safaricom were decide to license targeted customer profile databases and KBL requests and pays for that, guess whose details would be on that database?

Or if Safaricom decides to do context sensitive advertising. Once Jamie logs in to her Gmail via her Bamba modem, Safaricom can tie her traffic to her number. And can therefore serve appropriate ads (Smirnoff, etc)

Relax, I said IF!

Going back to John.

What other transactions has John made?

John has made at least one transaction every month via Pay Bill to a hair salon. The average amount is 5,000 which means it is unlikely he is paying for himself. There is probably a lady in his life, who he accompanies to the salon.

It also urns out he has used Lipa Karo to 3 different schools. Ergo he either is a father with 3 children or he has 3 dependants he pays school fees for.

John also pays DSTV via MPesa. Premium package (7,000) without fail on the 3rd of each month.

John also pays Access Kenya (10,400) for his home internet connection, also on the 3rd of each month.

John also pays Kenya Power an average of 4,000 a month in power, which says something about where he lives – he likely does not live alone.

His bills say a lot about his financial abilities.

In fact, none of his bills is paid earlier than the 3rd.

Looking closer, on the morning of the 3rd of every month John makes a 30,000 deposit into his MPesa from his bank which he uses to pay his bills. This suggests that likely he has a regular income that clears on the 3rd.

John also makes many payments to Steers. As frequently as 3 times a week, averaging 700. The payments are always in the evening.

This suggests that John eats a lot of take-away. Thus it is unlikely he is living with children (no one feeds kids burgers 3 days a week). This is supported by the fact that his spending at the Steers (700 is pretty much a meal for one).

There is also a payment of 3,000 at the end of every month to a number that does not appear in any of his call logs.

This same number also received the same 3,000 from 4 other different numbers, with the same pattern. No calls.

Who do you send money to but never call? Either some nefarious criminal enterprise or much more likely, a some sort of housekeeper.

But let me not belabour the point. A lot of insight can be derived for data mining, and this is not necessarily a bad thing.

Safaricom probably uses this number crunching to derive things like

  • New products e.g. tariffs
  • Promotions e.g. free calls from minute x
  • Pricing & price adjustments
  • Optimization of infrastructure
  • Competition containment (what is the highest we can charge for inter-network connectivity while still making money, staying clear of the regulator and blacking the eye of other networks)
  • etc

What horrifies me would be government having direct access to that information. That cannot be a good thing!

Here are some tweets i’ve exchanged with the Director Of Corporate Affairs this morning

BTW any lawyers care to chip in on the previous post?

KRA, Safaricom & You

So, there I am, like a good boy, reading my morning paper. I come across this story in the Business Daily. And upon reading it come across this, that triggered the following reaction

The section in particular was this one

mining

Yes, friends. The Kenya Revenue Authority is / wants to data mine your transactional information.

Personally, this offended my sensibilities. And it should offend yours too.

Of course the question arises, what’s the big deal?

Well to understand, perhaps a shotgun data mining primer.

Data mining, to cut a long story short, is a fascinating discipline that I have spent a few years studying and designing solutions around. It is basically using transactional data to detect patterns and trends.

The technical details of how this is done are fascinating but I need not go into detail. But it is used by serious companies to derive insights from data. Have you ever wondered why your mobile phone tariff is what it is? Or why there are promotions with strange twists like free calls that on paper make no sense?

Data mining.

If you find, for example, a promotion where they tell you that free calls begin from minute 3, that is because call logs were mined and it was found that most telephone calls are shorter than 3 minutes. Ergo those that make 3 minute calls will pay for those what make longer than 3 minute calls.

Examples abound.

Let me be blunt – given enough of your data, I OWN YOU.

Back to the point.

KRA wants to mine our transactional records.

An mobile money transaction contains the following

  • Date
  • Time
  • Sender
  • Recepient
  • Amount
  • MPesa outlet

If you give me a large dataset with ONLY this information over say 4 months I can tell you the following with a pretty large confidence level. Which is not to say it is 100% gospel truth, but can be pretty accurate.

  • Where you live
  • Where you work
  • When you are paid
  • How old you are
  • Your gender
  • An idea of how well of you are financially
  • Whether you are married or not
  • Whether you have children or not
  • Etc

And no, this is not magic. It is a simple co-relation of data.

For instance, the MPesa outlets you go to are usually the ones nearby.

For instance we notice that John goes to the same 3 or so MPesa outlets between 8 AM and 5 PM, and then a 3 different ones between 5PM and 10 PM.

BTW am using MPesa because the numbers of Orange Money, Airtel Money, Yu Cash etc. are of nuisance value. But the principals still apply.

We know where these outlets are.

We can therefore infer that the outlets John visits during the day are those near where he works and those in the evening are those near his home. Given enough outlets we can triangulate with great probability where exactly he lives.

If we notice a sudden spike of transactions (payments) around 3rd we can infer he has received inflows of cash fairly recently. If the same patterns repeats every month we can infer that the income  is regular.

Analyzing the recipients can tell us a lot about John.

If his payments are mostly to bars, utility bills and ticketing to event websites we can postulate John is probably a young bachelor.

If his payments include school fees, salons, supermarkets – we can infer John probably is either married or has a significant other, and probably either has a child or is supporting one.

I can go on about how you can infer a lot from this data (believe me this is just scratching the surface) but you get the drift.

It offends me that KRA want do this all the time. Not because I have anything to hide, but I resent that government feels like it has the right to scrutinize me in this fashion as if I am already guilty of something.

So I of course asked our friends at @SafaricomLtd

And asked them again

Their original response was they didn’t have any information about it, and I forgot to take a screenshot as that tweet has since vanished.

Next was this

And then I asked

Last I’ve heard from them. And by the way that response is bana oil. Transaction infromation without send and recepient is ABSOLUTELY useless to the KRA

So there are two queries

  1. Is it legal for Safaricom to hand over our data for mining?
  2. Is it within their terms of service to allow this?

Let us begin with the second.

Since most of you I feel sure never read a word of the terms of agreement, here it is in its entirety [PDF]. In case it is accidentally lost in a site update, I have saved a local copy.

The relevant sections are two.

One is under Privacy, Section 4

image

The other is under Disclosure & Data Retention, Section 16

image

Now, I am no lawyer but handing our data to KRA to data mine does not strike me as being within “genuine inquiry or investigation”.

In fact, the only way genuine inquiry can be stretched to allow what KRA wants would be if KRA says “we suspect EVERYONE of tax evasion so hand over everyone’s data”.

Is Safaricom handing over our data in breach of their own agreement?

Lawyer types, please assist.

It should bother you that KRA wants to just mine your information, never mind that you’re not actually guilty of anything.

The other issue is the larger issue of what Government can do / does with our data. Our data protection bill has been stuck in parliament for stages but it simply cannot be that government can willy nilly mine citizen data for its own ends in a civilized society.

This simply cannot be.

Unique – just like everyone else. Manufactured and bottled in Kenya