Some serious questions for anyone considering Cloud investment

On Feb 26th posted a piece in which I warned readers of the dangers of buying into CLOUD solutions without due care and without attention to all the little details they would pick through if they bought a small solution from me or even from an SME or “front of mind “,  big noisy solution provider. On March 1st 2017, Amazon went down to the shock and horror of the media at large. I promise you I had nothing to do with it, but I did get a flood of emails, some of them quite amusing.

Cloud services
Is the cloud right for me

The HIC problem

No I am not referring to the HICKs of Hicksville but rather to the much more common problem of “Hiding in Crowds”.  Closely related to the brand new evil you hear quoted everywhere, “ Populism”.
A populist is someone who, seeing his sweetheart taking a dip on the next plain, pretends to hear a lion and quickly convinces the herd to rush over there.

The HIC theory is sound enough for a plain dweller, if you are part of a large crowd the probability of being the one chosen for lunch by a marauder is very low, especially if you are careful not to stand out, I.E. don’t say or do anything different from the crowd.
If you are responsible for making key decisions on a modern organisation you can also retain some credibility after a disaster by saying , “Well everyone believed this at the time”,  or ” look at all the others who fell for it”.
If you are a responsible individual or if this is your own money at risk then you simply can’t afford to be a HIC.   What that means is making your own decisions on the basis of information, accepting the risks you can’t control and standing by your decisions, while always being open to new information and constantly monitoring your sources. E.G. You need to know who his sweetheart is.
Here are some thoughts to help anyone struggling with these decisions.

Business case for cloud investment
Building a business case for cloud investment

 

Some very strong arguments for investing in a cloud solution

  1. The IT department don’t want to give me a “NDB system” because it can’t be justified financially and won’t fit into the Enterprise Architecture just now. Who do they think they are, I’ll rent a cloud solution and I won’t even need to tell them let alone ask. That’s not as dumb as some might think. There are plenty of situations where this will be a good answer, just be sure that it is a temporary and not a long-term part of the business strategy and be absolutely clear that a: data is handled strictly within the law and b: You can get your data out safely when you need to and get it into another system. Remember you are responsible, not the cloud provider.
  2. I have no or an inadequate IT department and don’t want one because I won’t be able to control it. Instead I’ll get this cloud provider to give me the whole thing in one go and the problem is solved. You have to love it don’t you! If you truly do find the right solution available via this kind of deal that’s a big part of the problem solved, though by no means all of it. You are going to need a hell of lot of skilled man hours by some smart IT guys to arrive at that conclusion though and it will still be a best guess, just a very much better one.
  3. I don’t have and can’t or won’t raise the capital needed for this huge system I want, so I am going to rent it from a cloud provider and keep my capital working at the coal face. Not bad thinking on the face of it. Do consider the following: Are you really in business with insufficient access to capital to fund core process? I doubt it. Do you seriously make decisions about employment of capital in this way? Do you have a business case? If it says this is a good option, then given all the other ducks are in the right places, what are you waiting for?
  4. My business is made up of the original business plus a growing number of acquisitions around the globe, I am fed up of struggling with 7 different CRM systems and all the others, I want all of it in one system so nobody tells me again that the revenue from selling “tap”s was missed because 30% of sales were classified as “Faucets” and all the myriad of other such errors that turn my reports and dashboards into danger zones rather than information.
  5. I need my people around all of the group businesses working together to innovate and share ideas, but it is hard to achieve when they are working with so many different systems and using different vocabularies to discuss essentially the same thing. I want to migrate all of these businesses to cloud systems and administer them from Group Head Office, then we will be one business instead of 75
  6. I have fairly good systems and I am reasonably satisfied with what I have, but I need the ability to handle large demand spikes better and I need to prepare for an increase in the regularity and size of these spikes. Buying hardware to deal with this could be very costly and offer a low return on investment, given it would be redundant most of the time. I plan to extend my systems to encompass a cloud element so I can rapidly respond t short-term sever spikes in demand.

Some “gotchas” you really need to keep in mind

1 I need my CRM/ERP/other to be available via browser from anywhere in the world.
That is not cloud, that is Worldwide Web. It’s been around since the early 90s. You don’t need a cloud discussion, you need a web hosting provider and someone to find you a good free open source tool. If you don’t believe me, I have done tis more than once.

  1. My industry is highly regulated, e.g Pharma, Finance etc I need to bear this in mind.
    My personal experience of this is based on Pharma, but I believe the principles are the same.
    Right now there is a fledgling process for validating public clouds as suitable for specific types of data and sometimes or specific situations and geographies. Being a very new industry and a not well understood problem domain, the regulation is immature and almost certainly inadequate. If I were making a decision for the medium term, I’d be very slow to risk the future on what we know today and I certainly wouldn’t expose myself to any assumption that today’s regulation would be sufficient for tomorrow. Handle with extreme caution or stay way entirely is my personal view and that is based on knowing what we don’t know rather than any certainty.
  2. My business needs to be operating every day with no exceptions. Outbreak of war, epidemic you name it, this are more likely to be opportunities , or maybe the scenario is that I have a legal obligation to be operating. If this is you, don’t so it.
    a. Using the cloud depends on the internet and increasingly on mobile phone signals. This is still an area for very mixed quality of availability and signal across most of the globe, but do bear in mind that Governments everywhere hold an off switch for the mobile phone network and internet, any kind of political crisis can at any time lead to a black out in one or many regions. Can you handle that?
    a.i. The internet is not nearly as robust as people would have you believe. There are many points of failure and they are sought out and taken down from time to time. Logically, with all the publicity from the US election, this kind of thing will become more and more popular. Recently DYN the people who help with dynamic DNS issues were taken down bring the whole East Coast of Americas TV entertainment to a virtual halt and costing people like Amazon, Netflix and others fortunes in lost revenue. Expect more of this leading to more of above.

A.ii. Large providers such as Netflix for example are heavily exceeding their peering agreements or downstream traffic with the result that they are being throttled. This makes viewing almost impossible for many customers.  Such throttling is perfectly legal and it is likely to be used as part of trade wars between rivals. Your business could easily become the innocent casualty in one of these battles.

  1. Since my days in the broadcast industry I remember the affect Netflix had on the Amazon cloud when they were busy processing film. It was a well-known phenomenon and it lead my client of that time away from that solution. There has been a catalogue of large outages on a fairly regular basis since the beginning of the cloud movement and I fail to understand why somehow, senior CIOs clearly began to conclude that AWS and others were “Too Big To Fail”. Well that is reserved for bankers. The cloud can and will fail. It is technology and politicians don’t have much of value hidden there, so don’t be foolish about this.
  2. If the “Too Big To Fail” cloud provider fails, or decides this is no longer profitable, I must be able to replicate all of these services and carry on in business.
    Here is a simple piece of advice that I am grateful for having received a number of years ago.
    “Nobody sits around dreaming up risks that could not happen and writing complex legal clauses to extricate them form the risk situation when it occurs.” Let me translate that into simpler English; Read the legal contract, if the terms of the contract render the cloud provider blameless in such a situation, then they believe there is a really good chance it might happen and they know more about it than you do.

Unless you can build and rehearse a viable strategy for recovery given the reality of what might happen, you probably should stay away.

  1. Even if it were feasible, I wouldn’t put my entire business into a single cloud ERP and expect to live happily ever after, I need to be able integrate my systems in order that my people have efficient processes and data is not re-keyed repeatedly and I have an “almost trustworthy” view of the business to support decisions.

This is an area I have struggled with many times over a number of years and I can add to that the experience with non-cloud but WWW systems before that.   I have had a close and personal look at a number of leading cloud solutions and the variation in the quality of APIs provided is quite remarkable. One or two provided very consistent a comprehensive APIs, but the majority simply paid lip service the idea.
Even when integrating one of the better ones with systems “back at the ranch” we constantly ran into dead-ends where something we wanted, simply could not be done.
No is not a word I have ever accepted at face value and in the world of technology my first reaction always is, yes it can be done, even if we have to invent it. When your data is locked in a cloud data store that sometimes even the operator can’t understand with certainty and more to the point, you are not allowed any access to it, then it is beyond your reach unless the API provides access. Hence, “No API, no Data” Any architect will tell you to avoid going direct to the data store and I agree totally, but once in a while when the goals is big enough and there is no other way, it saves the day. Not with cloud services, unless of course you are referring to your own service built on PAAS or IAAS, see below. That is a different scenario and outside today’s scope.

               

 

Some definitions and buzzwords you need to keep an eye on

There are so many experts out there and so many levels of depth different people want that I hesitated to add this, but hopefully this will help some users. If you need deeper explanations google will find you more than you bargained for.

Cloud.  It began with the little cloud icons used to denote internet, and now it seems to have settled as any system you access via the internet rather than on you own infrastructure.  There is always an exception and this case it is the cloud you build on your infrastructure, see the next item and don’t get too hung up on this.

Private cloud.  This is about using the idea and the tools of the cloud to build a central resource on your own infrastructure.  The benefits are for example ability to virtualise servers of any size for a specific task  thus offering tremendous flexibility and potential savings, though licensing systems in cloud is a hugely complex area and a real minefield for assumptions about future costs.

Hybrid cloud This is simply a combination of the two above joined virtually to provide a single network so that the public part of your cloud appears and functions in almost every way like it were your local private cloud.  This gives tremendous flexibility with an ability to rapidly scale for sudden changes and reduces complexity at least at a superficial level.

 

PAAS.  This is really just the cloud providers renting you out the systems on which they build their applications. It is very similar in ways to renting virtual servers from a hosting organisation and building your application on that. The same principles apply. It saves a lot of time and capital investment and is especially useful when you want the ability to fail cheaply with something.

 

 IAAS.  This is as PAAS except that they are only renting you the infrastructure .
Within this are some very useful services that provide an end to end Continuous integration pipeline ready to log in and start developing software.  This is hugely valuable to software business not just impacting cost but also quality and consistency.

 

How much data is “Big Data”

For many, this question is almost an irrelevance. The question that should always start the conversation is “ What do you want to achieve?”, yet in my personal experience it never has and when I have introduced it I have been made to feel uncomfortable. Many feel that they must have a big data project in their portfolio and the why? and how? is of less importance. A high proportion want answers to fairly simple questions they can’t currently get answered and are lead to believe that answering those questions is indeed big data.
Let me make this very simple. With few exceptions, there is only one reason why you might want a Big Data solution: Because you have so much data that anything less could not analyse it and provide solutions in the timescales you need.  There are two key elements here; Timescales and volume of data to be analysed.

Timescales is the simplest one so let’s deal with that first. There tends to be two timescales: 1. Instant response and 2. Non-urgent responses. The latter is by far the more common and is typified by the “Data warehouse” approach. The former is typified by the “search engine” scenario.
Although the search engine appears to be providing instant response, in reality it is merely searching well-ordered indexes that have been populated at a leisurely pace, so in fact it does not differ as much from the data warehouse scenario as one might at first think.
The data warehouse is a model of efficiency where the questions are carefully defined in advanced, most of the processing done and the answers stored away until needed.  Often further processing is then carried out at the point of consumption.
Again you may be thinking that there are more parallels than differences between the two approaches apart from all the hype. You’d be right.

What does Big data do that is different?

Well the term as we understand it, owes its existence to Google’s own solutions to the search engine problem. Perhaps another penny has dropped for you now.  Hadoop, Map-reduce and all those sexy terms refer to a simple and very powerful approach to getting a huge job done efficiently.

The infrastructure relies on the idea of dividing each job into smaller jobs and continuing to do so until each is quite manageable and then delegating them to different machines. If you’re a software engineer, think Jackson.  A simplified view might be that you have five people doing operational work and a manager coordinating that work and responding with a single answer to his sponsor. If you ever attended management courses you will surely remember this type of organisation. Well that’s the big idea.
Why is this better? Well it allows a vast, unlimited number of servers to work on bits of the problem at the same time,  thus speeding up the time to complete. This allows one to demand immediate answers to questions that are more efficiently dealt with over a longer time-frame and there lies the risk.
Is Big data Machine Learning?
No, it definitely is not, but of course it can be useful for doing this. However, it is very important to understand that there is a plethora of tools, many free and some you already have in the toolkit such as excel,  that can very effectively carry out machine learning tasks if you take a little time to learn them. Not only  is it  infinitely easier to learn and carry out such analysis on tools like SQL server, Excel, etc. than it is to spin up a big data factory on AWS and become a data scientist just to find out if it will rain tomorrow.

Very few questions you are likely to want answers to require anything more than traditional statistical approaches or even simpler BI reporting that can be carried out very effectively on stunning data volumes and extremely complex problem domains with tools like EXCEL (try SOLVER or explore the many regression functions), POWERBI, KNIME, RAPIDMINER, MATLAB, OCTAVE, Google FUSION TABLES, TABLEAU. Many are free and very good tutorials can be found online. The best thing about these tools is that you can test your hypothesis and decide whether a major project is worthwhile.

How big is big?

Well there are truly big problems and yours may well be one of them, but the vast majority of questions can be answered with a well specified windows server or your personal preference.
rememeber alos that remarkably small samples are known to provide extraordinaty insihts that improve very little when expanded.
For a better technical analysis than I could offer have a look at this very good blog. It gets to the point much faster than I do

As usual, comments only via email. No new subscribers being accepted at this time.

Image result for bot wikipedia

I wont be long-winded about this, I’ll discuss it via email with anyone who is interested, but I’ll break with my usual mode and come straight to the point.
A great many people who know little at all of machine learning  and even less about people and many more who are simply  oblivious to the potential consequences of their words are talking about the miraculous things we can expect from Machine learning.

What is ML in a nutshell?
Academics break ML into two modes:  Supervised and Unsupervised.
In the case of the former we give the machine a large corpora of content and ask it to decide what will happen next, or to find other similar instances. A translation service for example  begins this way and learns after a while to translate without help.
In the latter case, we give it a body of content and ask what it thinks of that.. Google search is an example of this approach and it simply makes sense of what it finds.

Often we give it a few hints like “Classify this for me and establish links” as in Google search. This would be a “Classification problem”. We might on the other hand ask it to read the racing papers and decide who will win the four o’clock today. This would be a “Regression problem” because we are asking it to look at the past and predict the future. Yes all of this is highly condensed as promised, if you are an expert you don’t need my explanations.
Understanding what the customer will want next year, predicting the weather, finding Oil under the sea, predicting tumours, the challenges are endless and the rewards enormous.

What is the loop of self-destruction?
The loop happens when, thanks to social media, a good, but no a sole example, the machine begins to make judgements that influence the data and then discover exactly what it predicted.

As with humans this will give it the machine equivalent of a big head and possibly some citations and will lead to even greater confidence and fewer checks and before anybody spots it, it I all too late.
If any Movie producers out there are stuck for an idea, I am available to help with the plot. Here is a simple example we are all aware of:
Joe Gel, and Josephine Lotion our dear friends, represents an enormous body of intelligent and informed people who spend most of their waking hours  checking back with their phones for reassurance. Joe searches Google for Tom Raspberry, his favourite politician and receives a huge list of pages. The ML in google notes his interests and begins sending him dozens of articles about Tom Raspberry, what he says and does and what people say about him. Unwittingly Our pal Joe has become astonished by the fact the whole world seems obsessed with Tom R and realises subconsciously how important to is be aware of Tom R. He begins to tweet and have the odd Facebook conversation about something he read. Immediately the ML in Facebook and the one in Twitter hone in his apparent obsession with Tom R and all begin to bombard him with content and introduce him to thousands of people with the same problem. Poor Joe.

Now our Machine does a Recce to see what are people talking about and it discovers that millions are talking and reading about Tom raspberry and concludes that tis is the way to keep the customer happy so it ups its game and heightens the emphasis. It also confidently announces that Tom R will undoubtedly be unstoppable in the forthcoming election.

Joe and Josephine realise the importance of not standing in the way of a social crowd and are not about t be shunned and subconsciously they begin to take more interest in the positive stories about Tom which now triggers the Machine to filter their feeds and search results and friend recommendations etc more toward the positive . You don’t need me to finish the plot. There is only one way this is going. Imagine if the secret services relied on this kind of information to brief their bosses. But they do, don’t they.

You may well think, as I do , that despite the  shear “wrongness” of rigging democracy, whether by design or accident, it matters little who is elected anyhow. In that case imagine the same scenario when the machine turns its hand to guiding change in a government department or a large business , or guiding product development or even finding the cure for cancer. If you would like to see many better examples with a strong scientific analysis, check out Weapons of Math destruction.

One wonderfully simple yet highly destructive outcome of ML that I have seen up close is the  call centre  automated system that recognises your telephone number, calculates your value as a customer and decides if you will be answered, how long you will have to wait and whether you get to speak to somebody skillful.  Just to update my card details for a £20 a month hosting service, I had 11 hours of my time wasted, had my service disrupted and was threatened by a bot with £150 fine to put the service back on.
I hate to disappoint you, but if you have ever had an IM conversation with a patient lady on the support portal “That was no lady” nor was it my wife, that was a distant cousin of Cortana.
If she did not know the answer, or more likely the question, you were never going to be served.
If you are wondering what might happen to your pension, your job and your home if these guys get involved in stock trading, well take a look here  According to a 2014 report, sixty to seventy per cent of price changes are driven not by new information from the real world but by “self-generated activities”.

It’s not all negative by any means. I actually do use ML to predict the winners of tomorrows racing with a consistent level of profit. When I get it wrong, usually after a late night of programming with insufficient testing, my winnings disappear very quickly into someone else’s pocket and I sit up and take notice.
I sincerely hope that someone starts sitting up and taking notice soon  of the impact of poorly programmed Bots that are already beginning to increase risk for the most powerful nations on earth.

Amateur Excel wizards-the simplicity, scale and incredible consequences of their errors

Nobody imagines they can copy a bit of code off the internet and write the next messenger app, or heart monitor, but frequently people, whose position and professional standing suggests they ought to know more, make a hasty edit to an excel sheet in between meetings with extraordinary consequences.

* An accountant omitted a single minus sign resulting in their dividend estimate spreadsheet being out by a $2.6 billion.

* A simple cut and paste error resulted in TransAlta over paying $24 million for US power transmission hedge funds. “Cut and paste” can you believe it?

* In a written statement, Jayne Shontell, Fannie Mae’s vice president for investor relations put a $1.3 billion reporting error down to an “honest mistake in a spreadsheet”, but did not go into detail about the error.

* “ JP Morgan, was running huge bets (tens of billions of dollars, what we might think of a golly gee gosh that’s a lot of money) in London. The way they were checking what they were doing was playing around in Excel and not even in the “Masters of the Universe” style that we might hope, all integrated, automated and self-checking, but by cutting and pasting from one spreadsheet to another. And yes, they got one of the equations wrong as a result of which the bank lost several billion dollars”. Again, “Cut and paste” the mind boggles! http://www.forbes.com/sites/timworstall/2013/02/13/microsofts-excel-might-be-the-most-dangerous-software-on-the-planet/#5f70ad0772ae

* Reinhart, Rogoff… in 2010 published an influential report, “Growth in a Time of Debt”, used by economists globally, but specially in US and Europe to argue against fiscal stimulus. Now anyone with a grasp of economics had to be wondering about this straight away, however, it was not until a student, Herndon spotted not just flaws but what looked like careless weighting of data ranges and blew the whistle that the scale and arrogance of the mistakes came to light. Who knows what impact these errors had on millions of human lives. http://www.peri.umass.edu/fileadmin/pdf/working_papers/working_papers_301-350/WP322.pdf

* A report published in January stated that poor spreadsheet protocols were primarily to blame for JP Morgan’s estimated $5.8bn (£3.8bn) of trading losses racked up last year from credit default swaps, including by a trader nicknamed “The London Whale”.

Spurned by a continuing list of catastrophes, regulators around the world, including the Basel banking committee and Britain’s Financial Services Authority, have focused their attention on spreadsheets as a key component of best-practice corporate governance.

You may not be running J P Morgan, but the figures you are dealing with have equally big consequences for you, your staff, your customers, your shareholders. The stark reminder here is that code is not for children, cut and paste is something we don’t even discuss in polite company, methodical approaches with sufficient testing and oversight is the bare minimum and I’m not even discussing regulation or compliance. Serious decisions should be made using reliable information that has been quality checked and is understood for what it is.
The average executive playing with a few formulas and macros in Excel could soon be risking a Jail sentence and certainly eventual ruin is inevitable.
Software engineering is now a mature profession and when allowed, let alone encouraged to do it right, the profession will follow proven procedures and well-trodden paths to ensure a very low risk of highly expensive errors. It is easy to understand the temptation for a subject matter expert to ignore the need for a software expert and just paste in some data, but increasingly this kind of foolishness is being identified and outlawed and it can only be a matter of time until “Honest mistakes” come under more serious scrutiny.
A few simple steps now and an achievable plan could pay big dividends in a short time frame and besides,  a seasoned pro can achieve more safely in a few days or even hours sometimes and not only cut out the risk and delays, but save you money into the bargain.

If you are concerned about any of your  processes, please do get in touch for a confidential chat.

 

Two elections that few expected and a majority didn’t want- the information perspective.

Two groups of people mastered the truth about data, its interpretation and it’s presentation and two groups didn’t. The former of course are Republicans in US and Brexit’s in UK.

The theories are not new, nor are they difficult to understand but executing on them might only seem an option to somebody with no other options (Trump, Farage). Most people would never dream of applying for a multi-million pound loan and filling the entire application with fiction. It’ not because they believe it couldn’t be done, we’ve all seen it done, but because they were not brought up like that. They still believe they have other options and they won’t make that move to the dark side.  People who did it and often did it successfully were generally people who had no other option and didn’t see the downside. In banking there have always been checks and balances, but in media there has always been a weakness and right now there is a total void where the media used to sit. Enter two people who had no right to talk to us and simply couldn’t win. Donald Trump and Nigel Farage and look what happened.

Why did they win?

Nobody buys newspapers much less reads them any more and old fashioned journalists have hanged themselves by their braces long ago. There’s no revenue stream any more to sustain them, for what little use they might have been once and now we have instead, social media, polls (much the same thing) and personal content filters all very much for sale to the highest bidder and very controllable.

As IT professionals, we have always had to operate in a tricky area between less than perfect hard data collected from disparate systems or countries and the jazzy punchy little reports and dashboards that our paymasters dine on to excess.
Let’s be realistic, hard data is of little use to anyone, it’s only when the great unappreciated droves have cleaned it , sense checked it and translated it to comparable terms and then turned it into consumable visual bites that decision makers can grab it and do something useful with it, like selling a lie often as not.
When I see an email proposing a radical new strategy on the grounds of the figures in my reports I can sometimes pull somebody aside and caution them on the potential for error in the data or point to a conflicting KPI and suggest further checks. This type of scenario is part and parcel of business life in the world of IT.

Lets’ now take  a look at the world of rigged polls, injected social media, wholesale unapologetic lying and presentation that appeals to the baser emotions of fear and mob action.

  1. Destabilise the enemy by kidding them that they are doing better than they really are and encourage them to focus their attempts in the wrong places. Easy and very effective.
    I’m not sure that Farage had the budget or reach for this one, but it was certainly a central part of the Trump strategy and clearly explains why the bookies did so well. Read about Colonol John Boyd’s OODA loop to learn the basis for this strategy. Ask any social media consultant how to do it.
  2. Fill the media with mountains of lies about the enemy, begin by raking up a few real stories to set the scene, wait a few days for people to stop questioning that and then pile it on thick.
    For some good examples of this in action check out Niemanlab.org
    In the UK voters were incensed about legislation preventing the sale of bent bananas, (it never happened)
    They were told it would mean hundreds of millions per week spent on the health service, all immediately denied after election day. The list goes on and on.
    Why is it easy to find and cultivate these knuckleheads? Because Facebook, snapchat and others have detailed profiles of their entire lives and everything they discuss, read, think, say do, even the therapists they visit. Finding a numpty on Facebook and sending him to kill the president should be a doddle ( I didn’t give you the idea by the way)
  3. At the last minute create a powerful picture to capture the emotions of the more  ignorant layers of the electorate and plant a semi-subliminal message that appeals to the baser emotions i.e. massage the “lizard brain”.
    Nigel Farage’s posters were so blatantly aimed to incite civil unrest that there were well supported calls for him to be charged with this offence. On the day after the election, people of foreign birth were accosted on the streets around Britain and told to “go home”.
    In Florida, Trump’s “swing state”, Trump supports were seen on election night chanting “Lock her up”. The Canadian embassy crashed under the load of applications to immigrate and the flood of Mexicans going home in disgust continues.

In both cases, before the vote had been fully counted, the claims were being refuted and the lies were being reneged on.   No “Lock her up”, but tributes to her commitment. No “Go home”, or even close the borders in UK.  How far the reversals and denials will go on both fronts is yet an unknown, but nothing would surprise me mainly because the stretch room is usually very small once they find themselves in the reality of office.

So what is the lesson?

  1. Don’t rely on traditional media to be guardians of truth, what’s left of these are either state owned or in the pockets of the multinationals that own the politicians.
  2. Do I need to say it? Don’t expect politicians to tell the truth and don’t assume they have the same values or standards you do.
  3. Opposition parties ( that means both sides) have to guarantee the truth by monitoring and refuting media and actively and aggressively bringing liars to justice before and after the event. We all want the truth to be spoken, especially on important subjects and that is one of the things we will all agree to pay for and support politicians to achieve for us, so join the winning side for once and promote truth and honesty in media by attacking lies and dishonesty and supporting those who stand for truth and honesty.
  4. For god’s sake, or whatever you believe in don’t believe everything you read in social media, especially if it’s controversial and even more-so if it agrees with your predispositions.
  5. Make sure you defeat the personal filters to get alternative views of the world, use proxies or VPNs to hide your location and see a different view of the same thing. Ask a teenager if you don’t know how.
  6. Take responsibility for your own mind and for your decisions and actions.
  7. Don’t stay silent and let the liars prevail, it’s now a community affair, so speak out and have an impact on the balance of opinion. This way we can all help to keep society safe

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

What to watch out for when researching and testing journeys

Previously:

Why you need to pay attention to customer experience

What to watch out for when researching and testing journeys

 

1. Last Click  can be a costly mistake

The customer journey does not begin with the last click before they visited your ecommerce site. No assumption could be more damaging than this one.

Here’s an example of what happens before “LastClick” (Uses App to order)

 UJ1

You need to take off that blindfold and clean your glasses if you’ve been ignoring this part of the journey.
Once you have got ahead, next you will need to criss cross this journey with the interactions with your competitors if you want to stay ahead for any length of time.  And don’t forget all those potential customers who have been influenced by this on-line saga.

For an interesting interactive tool that can be filtered by industry classification to get a glimpse of how last click relates to the other channels and influencers, check out the ink below

http://www.thinkwithgoogle.com/tools/customer-journey-to-online-purchase.html

 

2. Its not what they say, or what they do, or even what they say compared to what they do, but it’s what they tell their friends that is interesting.

If you have spent any time working with professional market research you probably noticed that people tell you what think you want to hear, what they think makes them sound clever, or mostly what they believe the group will be impressed with.

It takes a great deal of skill to capture useful insight from market research and to make large investments on the basis of just a market research report, however good, is a fatally risky thing to do.
People invariably do entirely different things to what they expected they would do in a particular situation and even from what they planned to do.  It can be very difficult to explain why you did this, you can read the underlying Social Psychology theories and decide whether to believe them, or not, but it wont change the facts at all.
People are more driven by their acceptance in, or leadership of groups than any other thing and hence, once they announce to the group what they are going to do,  it is more likely that they will do it than not.  Hence the most valuable insight into what someone will do is what they are wittering about in social media.
Be warned of course, just like other forms of research, this is one more voice to add to the conversation, not the single source of truth.
Just in case you are thinking it, most people ask this , there is a big difference between what people say in idle chatter to their friends and what they tell you in focus groups. The latter is not populated with their peers and it ends when they leave.

 

3.    The journey does not end at purchase, or anywhere close to it.

If you have been following the series so far, you will remember that in paragraph 5 of the last section I presented some hypothesis about the power of referral from your customers.  This is a very valid argument indeed for being switched on to the journey after purchase. In many sectors of course ,there is an ongoing relationship with the brand.

First of all the product may be one that is repeatedly used over time, each repeated use will therefore be another interaction with the brand and the quality of that interaction does count. Additionally there will be the difficult period when customers are learning to use your product and later there may be issues that require active support.

If you take the view that once they have purchased and you have their cash, there is little motivation to spend more money on them, then you are greatly mistaken, because even if they never plan to make another purchase of your product, they will talk to everyone they know and their influence will cost you dearly. Put together enough of these negative voices and it will put you out of business.

A far more constructive way of thinking is to ask yourself what up-sells, or cross-sells you might be able to introduce as a result of providing high quality personal support. If you don’t have other products, this may be the catalyst you needed to re-think your brand and product strategy

4.  Pay special attention to understanding Critical touch points (Moments of truth)

A user journey can be and usually is very complex, even when we only represent the main points. Even this however, is a potentially misleading picture. Thee are always Moments Of Truth when you win or lose on the tiniest of margins and these are the ones you must identify and focus your closest attention on.

For example: When the customer finally returns to your store feeling really happy with her decision, clicks buy and you don’t have her size in stock. That’s not a good situation.

When she clicks buy and gets a spinning thingy that goes on and on. Not good.

When she buys and although being a regular customer she is asked to enter a lot of information yet again despite being on a sunny bench with her HTC One and her longest nail extensions. You are really pushing your luck here.

It’s not all about clicking buy, it could be when she decides to see what people are saying about you and the first thing she finds is a blog by an irate customer of yours that you didn’t even bother to respond to let alone apologise for. The writing is on the wall.

These moments of truth may differ for different customer segments and personas, so you really need to know this and it may even differ at different times of day or seasons or with different devices.
For cheap flights customers I would say that, certainly for me it is “Paying the bill”,” Leaving on time”, “Arriving on time”.  The other stuff in this case is far less important and if it can only be done at the cost of these three, I hope they just ignore it.

“Learn what the Moments of truth are for your customers and focus a lot of your attention on getting them right, it will make a huge impact on your top and bottom lines.”

ZMOT-GRAPHIC1

According to Google, there’s a Zero Moment of  Truth.

“that moment when you grab your laptop, mobile phone or some other wired device and start learning about a product or service you’re thinking about trying, or buying.”

When I talked previously about taking a hit to let customers realise how badly they want your product, this was ZMOT.
When Henry Ford gave them a smelly noisy Iron horse and changed their lives, that too was ZMOT.  For you and I, winning at ZMOT means deeply understanding our customers habits and preferences so that we can be there at the moment when the inspirtaion hits them and showing the the right messages to take them to the next level in the journey.

1MOT

In bricks and mortar terminology, this is nothing more or less than “First Impressions”.  Until Google gives you the time machine, you can’t go back and redo first impressions.
We spoke in the last instalment about how People see what they expect to see and feel what they expect to feel,  well this is ground zero. Here is where you set that expectation and it had better be good.

2MOT

This is when they open that box and your shiny product falls on their toe and puts them in hospital, or they struggle with one point white print instructions on grey papaer in broken Korean. You may well have thier money in the bank right now, but dont fool yourself about the importance of getting this right.

3MOT

Is the remebered sensations of using your product and how they compare to the expectation.  Wow that requires some thought.
Its not enough to have a great product, but it should be at least up to the expectation. Not only do they need to like the product, but they need to trust you to give them an even better one when your competitor moves the goal posts with a new offering, otherwise you’ll be saying an early farewell. Don’t forget that it is not just your product, but everything your business does in the public eye as well as how you answer your phones, or not and help them when they have a problem.

4MOT

This is when they talk about you to their friends and social media contacts. This is one you absolutely must win

Confirmation bias at the speed of light

The extraordinary world of the trader really opened my eyes

Image result for halo effect

Most readers will already be aware of confirmation bias and will no doubt believe they have it under control. Good for you. If however you are trader, or gambler the likelihood is that you have got it down to a fine art and it has become a heuristic behaviour.  What I mean by this simple, is that you’ve been doing for so long and become so attached to the theory that you are smarter than the rest, that now your brain does it in auto-mode without your intervention or even awareness.

Recently I spent some time developing trading tools for people earn a  living trading movements on a betting exchange.  The betting exchange, for those who are not familiar is a simplified clone of a stock exchange and is very similar to currency trading .

Some of these people act as bookmakers accepting bets form the public, while others simply trade the movements in the market or “SCALP” the market.
I was amazed to hear bookmakers of some standing use the phrase, “ Let’s get this one beaten”.
Quietly testing the intent of this over a period of time I realised that they actually associated their attempts to attract money and lay the runner with the runner losing.  Naturally they would never admit to it openly and they all know that such a thing is impossible, yet they daily select a weak runner and go about betting against it with the hope that it will be beaten and regularly it loses and bit by bit the brain has begun to associate tis intent and action with the outcome. Given they will be laying an 8: shot that really as a 1 in 12 chance of winning, the see it lose 11 times out of 12.
What is happening here is the brains own “Inspect and adapt learning process”, taking what it sees at face value and jumping to dangerous conclusions.
For years renowned physicians dispensed useless or even dangerous treatments to unsuspecting patients while convincing themselves and the patients that it was having a positive effect. After all, some of these people recovered. I wonder how much of this still goes on?
Economist and ex trader Max Keiser recently did a TV show on economics where he talked about stock traders believing they were changing the economy by their actions when in fact they are simply gambling with liquidity against other traders.
The UK government has been conspicuous in their inactivity in terms of fixing the economy, or even banking since the crash. They have sat back and conserved the status quo for all intents and purposes, yet George Osborne makes speeches in which he associates his office with a “reported “ improvement in the economy. Has it improved? If so, has it improved beyond a possible “ gently rising tide”?  Does he actually believe it?  What do you think?

Given the power of such self-delusion, would it be a shock if we found traders fixing things like exchange rates, or would it be far-fetched to imagine it might then stretch to bribing politicians and officials.
If those same people had gone into the munitions business instead of banking, do you think they might find a way to start wars? Do PMs and  generals ever admit that they achieved nothing ( best case scenario) or created a catastrophe?

Systems thinking

Negative bias the damage it can cause

Requirements engineering strategy can make or break your project .

Part one – What would you like sir
Part two – Requirements,tests, training, help files
Part three – Why no project exists in isolation-what should be done
Part four – Business rules, Process rules, Process, Data, different viewpoints
Part five – Testing requirements is not optional
Part six  -Requirements strategy can make or break your project

If you’ve been reading my blogs on the subject of requirements, you will no doubt appreciate the level of importance I place on getting requirements right and then testing them before committing yourself to a contract or a technical specification.
Just in case you are thinking that this is in some way anti agile, then nothing could be further from the truth. Please read my blog on agile requirements engineering for a discussion on this topic.

Let’s take this opportunity to recap on why we do requirements. The simple fact is that once a development team start work on creating a technical specification, the till begins to ring up with costs and every time you make a change after this point more costs are added. The closer you are to rollout when you make the change, the greater the extra cost will be and that time phased increase is exponential, therefore the first purpose of requirements engineering is to contain costs and eliminate or reduce slippages.

The second purpose is to make sure that the end product delivers value by meeting the needs of the business precisely in order to meet or exceed the benefits targets set in the business case.

Getting requirements right therefore, is absolutely critical if you are to contain costs and deliver value

Developing a requirements engineering strategy

Each organisation and each project are different and requires a tailor made strategy for getting the requirements right by recognising, exploiting and working with the capabilities of the organisation.

To do this successfully, you will need a few things:

  1. A detailed analysis of the stakeholders involved in the as-is process in order to make interviewing efficient and thorough.
  2. A strong feel for the past experiences of the organisation in terms of successes or failures with software projects in terms of meeting business need and staying within budget and time constraints. This along with some tactful exploration of causes will give a strong steer about the current capabilities of the organisation to engage with a formal requirements process and to take seriously concepts like change control.
  3. A feel for the organisations ability to take on and successfully adapt change will help you decide whether and how far you might decide to upgrade their skills and attitudes to requirement engineering
  4. A good indicative plan that indicates the products to be created, their acceptance criteria, time scales for delivery and the amount of effort that will be needed from stakeholders.
  5. The understanding, agreement and total buy-in of key stakeholders to the proposed approach with full support in terms of making people and facilities available for the process

 

Stakeholder analysis for requirement engineering

Step one

Using RACI to identify stakeholders for the Requirements function.

In my blogs on business case techniques and models I discussed the importance involving the right stakeholders to gain buy-in and get a real picture of what success will look like.
In order to design the system, you will need a different type of stakeholder list, one that describes roles, responsibilities skills and communication. This list will give a clear view of where the knowledge skills and the responsibilities lie within the organisation and therefore point you at the right people to describe requirements and take responsibility for their quality. My favourite tool for achieving this is a well known HR instrument known as the RACI chart. Responsibilities Accountabilities, Consults, Informs and it provides a two dimensional view of a team that helps you quickly analyse the team for adequate skills, supervision, communication and quality control. It can be adjusted in form or emphasis to suit your precise needs, but the fundamental principal serves well in any circumstance straight out of the box.
Here’s an example;

RAACI example

The table above lists nominal roles across the top and Activities down the left, each cell is then marked with one or more of RACI to show who has what role in that activity.
The example is for a software development team, but if you were building a hospital it would list things like planner, builder, architect and activities like approve plans, complete design, etc.

A software project for a builders might involve, Construction director, surveyor, cost controller, quality controller etc and Liaise with clients, agree costs, sign off completion, etc.
Apart from being a huge benefit in helping to highlight the important stakeholders for your requirements process, the RACI chart also provides a quick but effective sanity check to make sure that your team is adequate and that there no duplications, conflicts or gaps.

Horizontal analysis of each task will quickly tell you whether there are sufficient doers and accountability exists and is in the right place.
Vertical analysis of roles will quickly highlight overworked, underworked, misplaced authority or responsibility and lack of or too much consultation and information.
Too much consultation stifles decision making and too little leads to dangerous decisions. Corporate culture can lead to busy bodies who don’t always follow through, or teflon in-trays. All of these issues need to be understood and ideally addressed ahead of system design, because the system will only perform as well as the people who use it.

Once you have created this chart, the next thing is to create a list of names with contact information to place in each of the role areas. If the project is large and/or complex, there may be more than one name in each box and there may be further sifting to do in order to resolve any doubts.
Don’t be surprised to find skeletons in the cupboard and lack of agreement over who does what. If you uncover these issues, now is the time to discuss them at a high level and attempt to get them resolved ahead of requirement gathering.

Step Two
The second step is identify the Actors, the people and systems that carry out tasks as part of this process and the sources of all the skills, knowledge and decisions required to complete the process successfully. This will generally begin with the R people in your RACI chart and will usually expand to people who do the work with or for the R person. E.G. the R may be in your chart as the Technical architects for design, but on investigation, you may find a DBA, a SysAdmin and many others who play key roles and these people also need to be interviewed.
The actual actors may be more usefully broken down to specific skill sets or disciplines as opposed to specific roles. E.G you may have Document writer, Interviewer, modeller all of which are actors within the BA function. This approach gives a slightly more abstract approach that lends itself to reorganising roles for efficiencies, or to adapt to a new system.Never be tempted to accept the assurance that a supervisor can tell you the whole story and you don’t need to talk to her/his charges. If anything this should be seen with an element of suspicion and tactful verification is a good idea.

To better understand and communicate how the various roles influence the outcome of a process, it is sometimes useful to create a fishbone chart adapted slightly for the purpose. Here is how i like to create it:

Stakeholder fishbone chart

The fishbone can be made as complex as you need it to be in order to show all the influences on your new project. The thing that becomes apparent very quickly is that whether they are aware of it or not, most of your stakeholders rely on others for skills, support, knowhow, data, administration and other inputs that can potentially prevent the processes progressing and hence you need to know about it and to resolve, or risk manage it.
Your fishbone chart will immediately tell you who to talk to and by way of a bonus, it will very quickly highlight the areas of influence, both positive and negative when it comes to rolling out.

Organisational culture and requirements process maturity.

Once your target interviewees are lined up, your next step is to hold a number of short interviews and/or an interactive workshop to discuss past projects, how they went and how the organisation reacted at the time and now. Asking them what they felt went well and what went wrong will go a long way towards gauging what will go down well, or will meet with resistance in terms of methodology.
The aim is not to deliver the perfect project, by your standards, but to deliver the best you can within the capabilities and expectation of the clients.

The last critical aspect of this phase is to get a good feel for their favoured mode of communication within this area. Do they have requirements documentation that they worked with in the past? Are they comfortable working with it? Does technical documentation create silos that exclude valuable stakeholders to the benefit of technical people .

This aspect is vital, because the quality of decisions they make and their perception of you as a trusted adviser will be directly proportionate to your skill in communicating the concepts clearly to them. Not only that, but your ability to get their attention at all let alone hold it long enough to achieve a useful level of consultation will depend on not confusing or alienating them with technical or complex instruments of communication or use of unfamiliar jargon.

A clearly communicated strategy and indicative plan

Once you have gathered your information it is time to make some preliminary decisions about how to take it forward. How to collect information, how to verify your information and how to communicate back to stakeholders ahead of defining the requirements.

Identifying these tasks, the stakeholder and support staff needed and the order and dependencies of the work, it is time to add this to a simple Gantt chart that defines high level activities, high level milestones and products to be delivered.

Understanding, agreement and total buy-in.

If you have done your homework and worked in a consultative manner you will be very confident before presenting the plan, that it will be understood and supported and will be accepted by your stakeholders.
You should present:

  1. An introductory explanation of the approach with reasoning
  2. A list of products you propose to produce backed by a simple concise explanation of how and why and samples.
  3. A Gantt describing the timeframes and milestones.
  4. A simple, high level risk assessment
  5. An indication of the time commitments required of key stakeholders.

At the end of this you should answer questions and ask for their full support backed by a sign-off of the plan.

Ed Taaffe is a senior Consultant in Business Improvement through technology and Hi-tech Product management.

Reblog this post [with Zemanta]

Two important rules of the learning organisation that you won’t study in an MBA yet they are ignored at great cost.

The learning cycles described by    Sekar Sethuraman CISSP,CISA,CISM,CGEIT,CIA,PMP is in my view an excellent starting point that would most likely be a significant achievement to formalise and encode into almost any organisation.

My personal experiences apart from academic interest are around :

  1. What we often call “lessons learned” i.e. the constant adjustment to circumstances and to the perceived results of our previous actions.
  2. The impact of swarm intelligence on our ability to learn and teach.

Lessons learned, maybe we should not be doing it at all?

In the area of Project Management, few organisations do anything at all about “Lessons learned”  though virtually all would express a regret about this. In truth , doing nothing formally is not doing nothing after all and hence informal learning continues. Is that better, or worse? Well it’s not a clear-cut answer.

In the past year I returned for a period to the area of managing risk in an uncertain and volatile environment with vague rules and little explicit information.  A classic example of this environment is day trading , or any kind of investment banking activity, bookmaking, military activity, espionage, football  and a long list of less glamorous situations.  Football is too tricky for this discussion  because  there is almost no conscious decision making involved.
The reason I choose to discuss these more obviously volatile environments is because they are more like real life only sped up enough to trigger human emotions and  for people to  learn from trends  and responses  that otherwise  might remain hidden. i.e. because you see the results of your actions soon enough to make an association you have a chance to reflect on the actions and the outcomes that in normal, snail’s pace life , would remain hidden from most people .negative false

Actions and results are two key elements of all learning. John  Boyds OODA loop is a wonderful example of this.  What Boyd recognised is the need for “ Sense making” and this is the key, because learning without doing this effectively is to learn things that are patently wrong. The equivalent Is to put arsenic in your coffee cup.
In a fast moving environment we see every day people who pushed  a button a and felt a shock up their leg. Like the pigeon learning to select the right beans, he stops pushing the button, because he assumes a relationship between the two. How quickly he makes this assumption and how rapidly he reacts is directly related to his self confidence and very quickly you can see the cookie crumble to a pile of dust.  Burned out traders are almost as common as arrogant and broke ex-traders.
The answer lies in the ability to ignore what you hoped or expected to see, question what you do see and only act on proven information while filing the rest away for another day. The ability to do this is much scarcer than you might think.

Lessons learned can be formally handled in a project management environment and these lessons ingrained in culture at which point the will become pervasive until they need to be superseded.

That leads us neatly to the other area:

Swarm Intelligence or Hive Mind has most of us  firmly in her grasp.

Swarm Intelligence , or Hive Mind as I prefer, or in simpler terms culture is a far more pervasive and more potentially damaging force than most observers realise , in particular when it comes to learning.  Ask Paddy Power Bookmaers.- Paddy Power Left ‘Red Faced’ After Early Payout on Greek Vote. They trusted the wisdom of crowds and learned an expensive lesson.

Surowiecki had a bestseller and started a wave of books that appeared to discover something new in old wisdom , only to be widely discredited later.

According to Jesse St Charles of University of Tennessee at Chattanoogai, there are specific rules that define a swarm or flock:
1. The rule of separation. Think of a flock of birds flying in close formation but never  make contact physically. There is an unwritten rule that keeps them a certain distance apart and that rule alone defines where they go. Watch the starlings over Rome about this time of year.

  1. Cohesion. The birds all use the same patterns of flight and movement and even squeak and defecate in unison.
  2. Alignment. They gauge their direction by where everyone is going and align themselves
    4. Type recognition. A flock of starlings will never allow a crow to join, nor will he try

Once these rules are in place, the bird has waived all control over his own brain and simply follows the pack.  In all group based creatures this can be seen and it mostly likely stems for the safety of being in a group and ideally close to the centre.

Parallel this to the Stanford Prison experiment when a group of well bred and highly intelligent students form the top 5% or so of Americans were given roles and group structure in two opposing groups; Prisoners and warders and left to enact this for the benefit of a study.  If you don’t know what happened, I urge you o read this: https://en.wikipedia.org/wiki/Stanford_prison_experiment.

I am not commenting about the scourge of starlings in European cities, or the capabilities of the human given the right opportunity, I am simply pointing out that once an individual has identified his or herself as belonging to a particular group a large part o his/her brain is surrendered to the perceived group intelligence and the power of the written or unwritten rules of that group prevent learning anything that is contradicts the group in any small way

Conclusion:

If you are engaged in deepening the learning of your organisation, or team bear in mind two extra rules:

  1. Unless you adjust the culture of your hive so that learning and changing is a source of social acceptance and security, all you efforts will come to nothing.
  2. Sense making, for adults in a business means something different than in teaching and learning. People’s emotions play a huge role in how they perceive the effects of their actions, what they learn from what they see and even what they see. If you want to create a learning organisation, you must teach and assist people to collect and observe the results of their actions in an objective way, make and execute good decisions at the right time and police their emotions against rash reactions, or unearned self-doubt.

 

Perhaps the short description of all this is leadership, the thing mankind craves for more than anything

 

The health warning attached to agile is nothing more, it’s not a reason to ignore agile thinking as a powerful tool.

As a manager who entered software engineering as the agile movement was gathering pace and returned to management in the systems world, I find it amusing when other disciplines jump on the bandwagon as it were. I also find it encouraging, but I would have serious concern if it were my business and here is why:

  1. Agile is not what journalists say it is

In much the same way that we probably misinterpret and ingratiate many movements,  Agile is credited with a lot of stuff that was never  though t of,  never intended and for the most part never happens.
A bunch of software engineers (several in several places) to decide how they could “take back control” of the software process in business.  They knew the power thy held in their hands, but could see more and more of it ebbing into middle and senior management determined to make them “blue collar”.  At the same time service businesses like IBM and Microsoft were looking for ways to reduce the paperwork and improve communication in the software transaction. The two things were married and produced a clever, but unruly child that requires careful monitoring and constant praise.  Agile was never a strategy, but a bun fight and it is far from over.

2.Fiiddling with KPIs is not changing anything.
 In my early days as a marketer I was taught that if you are not meeting KPIs, it is easier to fiddle with the KPI than change your behaviour. This is a fairly universal principal of business and nowhere is it more fitting that the world of software.” I want it and I want it now, but I am not sure what it is and couldn’t communicate it to you even if I did . In any case, what if it doesn’t work?”  I’ll claim you didn’t deliver and /or you didn’t do it right. That is the scenario driving software engineers to do away with specifications and contracts and make the product owner responsible. Unfortunately, what they didn’t spot until too late was that in doing this, they sold their souls and became blue collar again, but that’s another story.  Now they estimate in Tee-shirt-sizes and look upwards and to the left as they declare how many tee shirts they completed this month. If they don’t like the design they simply say it can’t be done or will cost too much. That is roughly where the tyre meets the road toady

3. A racehorse designed by a vet and an art student will make a very ugly camel at best

I was a product Manager for a few years, it is a natural progression for a marketer cum software engineer and I know some of the best around the globe. Some are redundant and others struggling. Why? Who needs professional when you have the seat of your pants? I am not suggesting that Agile teams with a nominated Product Owner can’t or don’t produce good stuff, simply that; successful products need a market sized opportunity, or it matters not how good they are, products need to meet an unmet need and to do it so that they are a more attractive proposition that their competitors and so forth.
What I am getting at is this; iPhones are successful because they were driven forward by a brilliant visionary who had the courage to show us what we are missing and make us love iPhones. Bill Gates did this for the PC. In an agile world neither of these products would have happened.
The iPhone would have been an ugly mishmash of half-finished features rushed out to an imaginary deadline and reflecting the current tastes of the Lead developer and the Product Owner, usually in that order.  I suspect the PC would have been a typewriter with a glass screen and a coffee holder.

  1. Lying in the water and thrashing your arms about is not swimming.
    Anybody who seriously wants to make a change for the better needs to start not with the technology, but with goals, develop strategies and work their way down to the details of how.  If that happens to be agile, wonderful, there is then a powerful chance that you will make it work.
  2. Beware the evangelists, many are trainee terrorists

Understanding the shortfalls of anything is the first sign of expertise and even love. Don’t fall for the preachers they have alternative motives. Somethings and some teams lend themselves well to agile, but not everything and worst of all, when a good agile team has been doing the same thing for a year or so, they are no longer agile, they are simply where they were before with slightly different rules and rituals.

  1. Agile is a state of mind not a book or a methodology and must be championed and driven form the top down by people who know what they are doing and why they are doing it.