It's time we stopped idolising failure in innovation

Failure, it seems, is in vogue.

We're told to "fail forward fast", "celebrate failure", give our teams "permission to fail", etc.

But have we gone too far? Have we inadvertently started idolising failure?

It is true that failure is inevitable in innovation. Just as risk is inevitable in earning investment returns.

But we should not lose sight of the fact that our ultimate objective is success rather than failure; returns rather than risk. Failure and risk are means to an end, not ends in themselves.

I recently heard of an organisation who set a KPI target that "at least 90% of innovations must fail". I think I know what they were trying to achieve. They wanted their staff to be bolder. Less incremental. And that would mean tolerating higher levels of failure.

But to actually encourage - mandate even - more failure is perverse. The obvious unintended consequence is that staff will be encouraged to sabotage perfectly good innovations!

Catchy phrases lauding failure had a purpose. That purpose was to break the mindset that failure was unacceptable. To reintroduce failure as an acceptable cost of innovation. But now I fear they have taken on a life of their own. And it is not good for business. Or for innovation.

To quote Frederic Etiemble, "a good idea doesn't have to become a dogma". (Source)

The original intent of those catchy phrases was to enable learning by doing. Its time we focused our attention back on that original purpose.
"Innovation does not require failure. Innovation requires you to run experiments. Experiments don't succeed or fail. They produce results from which you can learn."(Tweet this
What we really want, is a more scientific approach to innovation.

In science, experiments don't fail. They either prove or disprove an hypothesis. Or they're inconclusive. Either way, we learn something.

Scientists don't just throw random chemicals into test tubes and hope something interesting happens. Research programmes are carefully planned and structured.

So how should we go about innovating in a more scientific way?
  1. Be very clear on your goals.
  2. Break those goals down into the smallest testable experiments.
  3. Start with the experiments where the greatest uncertainty exists with the greatest impact first.
  4. For each experiment set a clear hypothesis. Know (1) what data you're going to collect and (2) how you're going to collect it to confirm or disconfirm the hypothesis before you start.
  5. Make sure you have a control group. You need to know if the hypothesis was confirmed or disconfirmed because of the experiment and not because of some other factor.
  6. Experiments are not commitments. Make sure you can stop the experiment any time you want.
Words matter. Our focus on failure will lead to failure. Let's change the language. Let's focus on success. Let's focus on learning. Let's focus on a scientific approach to innovation.

We need to move the narrative from:

  • "we tried a, b and c and failed - awesome job everyone!"
  • "we tried a, b, and c, and learned x, y and z." 

The successful innovators already get this. It is the unsuccessful ones, the not-yet-successful ones, who will be misled by lazy, populist slogans.

See also:

Using online research to build an evidence base

Business strategy must be evidence-based or it is just wishful thinking. (Tweet this)

But how exactly do you build an evidence base?

1. Get good at Google

You'd be amazed at how much quality data is available on the Internet. And Google is there to help you find (almost) all of it.

But using Google can be a bit like trying to drink from a fire hose. There is just too much information. And most of it is not very good. The bad an irrelevant information drowns out the useful information.

So you need to get good at using Google to sift through the dross to find those nuggets.

There are lots of good resources to help you use Google more effectively. It is definitely worth familiarising yourself with these. (Note: Not all search tips are equally useful for strategy. But I think that will be obvious enough.)

Some of the more useful tips I have found are:
  • Use quotes to specify precise words in a specific order. This can be helpful when searching for a specific quote, a proper name, or a specific report where you know the title.  
  • Put a minus sign in front of words to exclude them. For example, if you're looking for smartphone technology other than the iPhone, you could search for "smartphone -iphone".
  • Use the tabs. Click the "news" tab if you're looking for recent news stories. Click the "images" tab if you are looking for charts. This is particularly helpful as the better quality research sites will often use charts to represent their data and analysis.

Remember that most of the time you're trying to improve your search criteria to eliminate that which is not useful.

The other challenge can be to tap into the specific jargon which people use when writing about the industry you are interested in. If you've worked in that industry for a long time that's usually not a problem. But if you're an outsider or consultant, you should make a priority to master the language used.

It can be a bit hit and miss. Especially when you're starting with a new topic, line of enquiry or industry. So you have to keep trying it from different angles until you get it right.

2. Get good at scanning the results

No matter how good you get with Google, you're still going to need to process a lot of material to get the evidence you're looking for.

The first trick is to learn to recognise the reputable sources of information in the industry you're researching. Which are the quality edited journals? Which are the quality research companies? You can usually spot their URLs in the Google search results before you even click through to the page.

Then you look into the text itself. Which pages are spouting un-substantiated opinion? Which are written by lazy journalists trying to fill column inches or be the first to break a story without really understanding it? And which are providing high-quality, in-depth analysis backed by evidence and data?
"If we have data, let’s look at data. If all we have are opinions, let’s go with mine.”
- Jim Barksdale (tweet this)
Where there is data, is it of a high quality. Is it clearly described and defined? What is the sample size? Are the conclusions statistically significant?

What is the quality of the analysis? Is it clearly and logically reasoned? Does it make basic mistakes like confusing correlation and causality?

You have to kiss a lot of frogs to find a prince. When you're doing research you will have to scan and discard a lot of information. A lot of it is poor quality, repetitive, or not quite relevant to the topic you're researching. It takes time.

3. Focus on the contradictions and inconsistencies

Don't get lazy and only look for data which easily supports your views. Look for as wide a range of evidence as possible.

Data sources which contradict each other or contradict the opinions of experienced people within your business are often the most interesting.

Assuming the data sources are credible, and the experience people are indeed knowledgeable, these contradictions often lead to the best insights.

Instead of assuming that one or the other must be "wrong", dig deeper. Look for some explanation under which both can be right.

Have you found an exception to a rule? Something which is true under one set of circumstances, but not under another? Have you uncovered an implicit assumption or bias in thinking? Have you found something that used to be true but no longer is? If so, what has changed?

Such seeming contradictions and inconsistencies provide the starting point for more considered analysis, insight, and sometimes strategic breakthroughs.

4. Make excellent notes

Once you've found the evidence you're looking for, it is important to keep good notes. You need to be able to recall what you've found easily, whether its because you've got a report to produce, or because you're in a meeting and someone is asking you to back up what you're saying.

You can use a general-purpose note-taking tool, like Evernote. But general-purpose tools don't know what your notes mean. Nor do they know how they should be organised. So often, you end up searching through your notes just like how you were searching for them through Google in the first place.

Alternatively, you can use a special-purpose tool like is specifically designed for organising evidence for business strategy. It will organise your notes for you using familiar strategy analysis models. Evidence gathered in this way typically supports PESTEL analysis, Porter's 5 Forces analysis, and the Threats and Opportunities in a SWOT. will help you to connect the evidence you gathered directly to these analyses. It will also maintain the links back to the original sources of the information.

Not only will it make it easier for you to find them again, but it will help you develop your strategy analysis as you collect your evidence. supports this with a convenient 'clipping' tool. Once you've found a web-page of interest, simply highlight the relevant text and click the button. will pull it through into the app, categorise it and link it into your existing analysis. Follow these instructions to install the clipping tool in your browser. also integrates with will help you to ensure that your notes are clearly and accurately written.


Evidence is the bedrock of good strategy. Get good at finding and interpreting it. (Tweet this)

What are your top tips for researching evidence? I'd love to hear your thoughts or questions in the comments.

See also:

6 top tips for strategy analysis

Strategy analysis is the bedrock of good strategy. In this post, we look at 6 top tips for doing it well.

1. Know your tools

You can't be a mechanic without the right tools. Nor can you be a strategist without the right tools, frameworks and methodologies.

Using the right tools is the most basic requirement of strategy analysis.

You will need a wide range of tools at your disposal. You will need to know both how and when to use each one.

Remember that not all tools are useful in all circumstances. And that not all analysis yields results. Much of it will end up on the cutting room floor.

See: Essential tools for Strategy Analysis

2. Take an external perspective

Avoid being too introspective.

Companies have a tendency to tell themselves stories. Particularly about what they're good at. It's natural. They've invested time and energy into creating what they got. They want to believe they're good at it. They want to take pride in what they've done.

And if they tell themselves the same stories often enough, they start to believe they are true.

Strategy analysis requires you to look beyond those stories.

One way to do this is to take an external perspective. How do your stakeholders see your business and your market?

Your list of stakeholders should include your customers, distributors and suppliers. Anyone the business relies on to succeed. Consider existing stakeholders and target stakeholders.

Ask what your customers would see as your strengths and weaknesses - relative to your competitors. Ask how industry trends might affect your suppliers and distributors.

Read industry reports. Attend conferences. Join online forums. Get out there and talk to people.

If appropriate, get an external review of your analysis.

3. For insight, present data, facts and interpretation

Opinions are a dime a dozen.

As Jim Barksdale said:
“If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” (tweet this)
Strategy analysis relies on data. Facts. Evidence.

You can ask people for their opinions. But then use those opinions to work out what data you need. Does the data confirm or disconfirm the opinions? What does that mean?

Data can come from lots of different sources. Internal sources include operational and financial reports. External sources include industry reports and primary research.

Data can be presented in lots of different ways. There is an art to presenting data in the manner which best reveals its meaning.

Annotate your data with insights, conclusions and interpretation. Draw the story out of it. But be careful of inferring causality when all the data shows is a correlation.

4. Embrace the ambiguity

No matter how good your data, things are seldom conclusive.

If you've asked lots of different people and drawn on lots of different data sources, it's unlikely they will be.

Expect to find contradictions and gaps.

One way to deal with ambiguity is to use scenario planning.

Even then, strategy analysis is uncertain. Part of being in business is taking risks. Sometimes you just have to take a change. But make it an informed decision.

5. Keep repeating

Once you've completed your analysis, don't expect people to get it the first time.

Remember, you've been working on this for some time. You're familiar with the material. But your audience probably isn't. They're probably distracted by other things.

So keep repeating it. Keeping trying different ways to get your message across. Learn what works and what doesn't work. Keep repeating what works.

Don't make the mistake of moving to the next stages - articulation, planning and execution - assuming that everyone will remember the analysis. People forget - sometimes quite quickly. And then the strategy starts to drift away from the analysis. It usually reverts back to 'the way we've always done things around here.'

6. Never stop analysing

Strategy development and execution is not a linear process.

As Helmuth von Moltke the Elder said:
"No plan survives first contact with the enemy." (tweet this)
As soon as you start executing your strategy things start to change. Things don't work out quite the way you planned. Stakeholders don't respond as you'd expected. Competitors fight back.

So strategic analysis is an ongoing process. In fact, strategy is best thought of as a loop. Analysis, articulation, planning, execution and back to analysis.

See: the Strategic Learning Methodology

Book review of Subscribed: Why the Subscription Model Will Be Your Company's Future - and What to Do About It

We don't have to look too far to see the impact that the subscription-based business models are having on everyday life.

We no longer buy music - we listen to it on subscription from Spotify. We no longer buy films, we watch them on subscription from Netflix.

In the subscription economy, instead of paying a lump sum up front to own or use something forever, we pay a monthly or annual fee for the right to access that benefit for that period of time. As soon as we stop paying, we lose access to that benefit.

Even fairly capital intensive purchases like cars are being impacted by this change. Instead of buying a car outright, more of us are entering into Personal Contract Plans (PCPs) or other similar arrangements where we effectively pay a monthly charge for the right to use a vehicle. Of course, under a PCP we have the right to buy the vehicle at a predetermined price at the end of the deal, but the dealer's hope is that you simply trade it in for a new car on a new PCP arrangement and keep paying.

I think that the financial services industry, where I do most of my consulting, has always run on something like a subscription basis. When you open a bank account, you pay for it either through explicit charges or reduced interest rates until you close it. When you take out insurance, you pay a monthly or annual premium. When you invest or take out a pension, you typically pay a monthly 'usage-based' fee based on the value of your assets.

As a result, I am quite familiar with many of the challenges that subscription-based business models bring: typically providers' expenses are highest at the start of the relationship, and then they hope that the customers will stay long enough to become profitable. As a result, providers spend a lot of time worrying about how to reduce the costs of acquisition typically sales and marketing, distribution and onboarding) whilst also reducing the churn rate (the percentage of customers who leave during any defined period).

In their book, Subscribed, Tien Tzuo and Gabe Weisert take a broader view of the trend towards subscription-based business models and its impacts.

The subscription economy is customer-centric

The book sets the scene with some bold claims, such as that "companies running subscription models grow their revenue more than nine times fast than the S&P 500". In fact, there is a whole addendum of juicy numbers describing the rapid growth of subscription-based companies. Most of this seems to be drawn from the usage statistics of a "comprehensive billing and finance platform for subscription-based businesses", called Zuora. Disclosure: Tien Tzuo is the CEO of Zuora.

One of the reasons for the success of subscription-based businesses is that each and every subscriber has a unique identifier to which all the data the company collects about them is mapped. I am a little tempted to point out that they may be conflating two separate issues - customer-centric data management and a subscription-based revenue model.

The authors point to companies like Amazon, Google, Facebook, Apple and Netflix as evidence of their hypothesis. However, I think Amazon was a runaway success long before it introduced it's Amazon Prime subscription model, and on the basis that it exploited customer-centric data on the basis of unique customer identifiers right from its inception.

Amazon, Google, Facebook, Apple and Netflix are all examples of digitally native customer-centric businesses, who also happen to be (increasingly) subscription based.

The authors contrast this against 'traditional' businesses that mass produce and distribute physical goods. Such businesses tend to rely on Enterprise Resource Planning (ERP) systems. These are designed around physical goods - raw materials and finished products - and while they do a great job of managing operational efficiency, raw materials, inventory, purchase orders, sales, shipping and payroll, they do a lousy job of managing customer relationships and experiences.

The book does not discuss Customer Relationship Management (CRM) systems, but I think it is fair to say that CRM systems have gone a long way towards addressing this. However, they are largely still bolt-ons to the underlying ERP-style systems. The result is a far cry from systems built around the customer and customer experience from the ground up.

Instead, what it does describe is how companies:
"...set up customer service departments! When in doubt, build another vertical silo—they launched market services, technical support lines, warranty contracts, and maintenance groups. The customer had truly arrived—they had their own department now. And that department was located way down at the far end of the supply chain, just past the loading dock."
The authors argue that the battle between Amazon and Walmart is not between online versus traditional retail but between customer-orientated data-driven app-centric flexible and omnichannel retail on the one hand, and product-orientated retail on the other. (tweet this)

They conclude that:
"If you're still selling your product off shelves to strangers in five years, there's a good chance you're not going to make it to ten." (tweet this)

Changing consumer preferences

The book then goes on to talk about consumers changing preferences for services rather than products, for outcomes rather than ownership, and for constant improvement rather than planned obsolescence.

The authors describe how customers now "want the ride, not the car; the milk, not the cow." (I think this description is slightly misplaced as buying milk still represents the old manufacturing to sale model, rather than the move to a subscription-based model.)

This broad societal change is nicely summed up in the final chapter:
Once upon a time, we used to know the people we bought from—the butcher, the baker, the blacksmith, the farmer. We used to know the people we sold to, the neighbors in our village. All that knowledge got lost a long time ago, when the Industrial Revolution ushered in the product era. But it’s coming back in a big way.
I suspect this trend is fueled and reinforced by a growing awareness of the environmental consequences of mass consumption over the last century.

An added advantage of doing so is, of course, that company's doing so can learn by watching how their customers use their products and services. In the traditional product model, once the customer received the product, the manufacturer typically has little, if any idea, of how the customer used it or even if they used it at all.

With a subscription service, providers can gather data on an ongoing basis, analyse that data, and use that analysis to continually improve the product or service. Existing customers can benefit from those improvements immediately, often without needing to pay for a new version or upgrade.

So, even where businesses stick with a traditional product-based model, there is an increasing drive to package these with value-added services. For example, Fender now sells a subscription-based online video service called Fender Play, which teaches customers how to play their guitars. Not only does this create an additional revenue stream, but it also creates a more intimate relationship between the company and its customers and reduced the rate at which customers give trying to learn to play.

Apparently, International Data Corporate predicts that by 2020, 50% of the world's largest enterprises will see the majority of their business depend on the ability to create digitally enhanced products, services and experiences.

Market research needs no longer to rely on what focus groups and survey respondents say they want but can draw real-time data generated by what real customers actually do. (See also: Everybody Lies, the evolution of market research.)

The new economics

The authors argue that traditional businesses rely on advertising to sell individual products to strangers while subscription businesses rely on customer relationships to continue to provide services and upsell new services to loyal customers.

They devote a number of pages in the book to describing a challenge that traditional businesses face when making this switch, and which they call "eating the fish" (for reasons which escape me). By way of example, they describe a software business moving from selling on-premise software installations to SaaS solutions in the cloud. The economics change, they argue, from a large purchase and installation revenue followed by upgrade every few years to a smaller, recurring monthly fee, with the difficulty being that this means that revenues actually decrease in the first few years after making the change.

The long-term advantage, however, is that instead of starting each year with zero sales on the books, subscription businesses start each year with a stable recurring revenue stream.
"You're talking about shifting from an asset transfer model to a long-term relationship."
The authors contrast the old imperative as being to sell more units, increase the price of those units, or decrease the cost required to make them, whilst the new model is driven by the imperatives to acquire more customers, increase the value of those customers and hold on to them longer. (I think they slightly miss the opportunity to serve those customers at a lower cost, but their point is well made.)

Crucially, this requires a shift from a sales mentality - make the sale and move on - to a service mentality - win the customer and then stay as close to them as you can.

More subtly, current accounting practices do not distinguish between historic sales and recurring revenues. The traditional manufacturing and sales model is very transaction and backwards-looking, whilst the subscription model is more relational and forward-looking.

As an aside, I would note that the insurance industry has been grappling with this for years, and insurance accounting allows for the recognition of anticipated revenues in the form of 'embedded value'.

However, this change in thinking could be a double-edged sword. I half suspect that it is part of what allows so many startups to burn through so much cash acquiring new customers in the hope that they will stay long enough to become profitable. Sadly, as we've have seen, if this does not come to pass, the investors may be left with little to show for it.

Churn rates

The aforementioned addendum included some annual churn rates which, if I am honest came as a bit of a surprise to me. These were:
  1. B2B: 27%
  2. B2C 30%
  3. B2A 26%
  4. Corporate Services 37%
  5. Telecommunications 26%
  6. SaaS 24%
  7. Media 33% 
For all the aforementioned benefits of the subscription economy, these seemed high. I was left wondering if customers who simply buy products might not stick with them for longer, on average, than that. Or perhaps, as we move towards this new business model, we're discovering just how poor many companies are at keeping their customers satisfied.


Subscribed is packed with analysis and examples of industries and companies grappling with this fundamental and far-reaching change in business model.

I would highly recommend it to anyone with an interest in business models. If you're still in any doubt, I will leave you with the authors' conclusion that a subscription business is...
"...also a much happier business. Why? Because subscriptions are the only business model that is entirely based on the happiness of your customers."

When life gives you lemons, think like Juan José Méndez Fernández

Image of cyclist with one leg and one arm with the caption Don't tell me you can't
Juan José Méndez Fernández is a cyclist from the Catalan region of Spain. He has competed in the 2004, 2008 and 2012 Paralympics.

It was this picture with the caption "Don't tell me you can't" that caught my eye. What an inspiration!

My mind immediately asks: what if he falls over - he has no way to brace his fall? Surely there are easier sports for a man with only one leg and one arm?

But I guess that is the point. For whatever reason, he wanted to be a cyclist. And he didn't let what most of us would consider almost insurmountable limitations stop him. He adapted, and he succeeded.

Lessons for business strategy

Of course, I quickly moved on to consider what the lessons from this are in business strategy.

In business strategy, it is important to start from a balanced and realistic analysis of your current situation. There is no point in sugar-coating things. I am sure Juan did not start by simply assuming he was just like all of the other cyclists. I am sure he started by realising that he was different and that he adjusted his training plan accordingly and found someone to help him get onto the bike and upright, etc.

So too, in business strategy, we recognise weaknesses and threats alongside strengths and opportunities in a SWOT Analysis when developing strategy, and risks and issues in a RAID Log when executing it.

You can categorise these negative factors in strategy development and execution using a simple matrix:

Be optimistically realistic

Someone once accused me of being too pessimistic because of the attention I pay to weaknesses, threats, risks and issues. It seems, sometimes, that the world only wants optimists. But I counter that the world needs neither pessimists nor optimists but only realists; that by paying sufficient attention to weaknesses, threats, risks and issues you are able to succeed despite them - or even, if you are really clever, because of them.

Unfortunately, the literature plays to unrealistic optimism. People focus on success - what worked - and forget about all the difficulties and challenges along the way. Failures, and the lessons learned, fall by the wayside.

But being aware of weaknesses, threats, risks and opportunities is only the first step. What do you do about them?

Dealing with Weaknesses in Strategy Development

  1. Strengthen your weaknesses. If your organisation is weak at something you can address this directly. You can train existing staff, hire new staff, improve existing or develop new processes, upgrade equipment, move to a better location, undertake research, etc.
  2. Partner with someone who has strengths where you are weak. You don't have to go it alone. A partnership could work especially well if you can find a partner who is strong where you are weak and weak where you are strong.
  3. Avoid competing in areas where those weaknesses matter most. For example, if you lack retail marketing capability, stick to wholesaling or B2B markets; if you can't manufacture at volume, find a niche; segment your market and focus on those customers who value what you are good at more highly than what you're not good at.
  4. Take advantage of your weakness. When Spencer Silver was doing laboratory research into how to make stronger adhesives, he accidentally discovered a very weak adhesive. Instead of writing it off as a failure, he invented the Post-it note, where the weakness of the adhesive is its very strength.

Dealing with Threats in Strategy Development

  1. Monitor your threats. Make sure you have systems in place to monitor your threats as they evolve and to communicate that information to the appropriate people in the organisation.
  2. Neutralise threats. Consider what steps you could take to prevent threats from materialising. For example, in the case of a regulatory or political threat, could lobbying help to reduce the likelihood or impact of the worst possible outcomes?
  3. Prepare yourself. Take steps to prepare yourself for the possibility that the threat turns bad. For example, if it is a technological threat, start to research how it works. If it is an environmental threat, start investing now in greener options.
  4. Map out your scenarios. Scenarios are an effective way of dealing with high levels of uncertainty (whether positive or negative). See also: Scenario Planning for Business Strategy
  5. Develop your strategy assuming the threat materialises. If the likelihood of it happening is more certain, you can simply develop your strategy around the assumption that the threat has materialised - treat the threat as if it were a weakness, and proceed as outlined above.
  6. Adapt. If the threat emerges differently to what you anticipated, at some point you have to change your strategy. Whether it is a small tweak, or a full pivot to a completely different strategy, don't be afraid to change. History is littered with failed businesses who stuck doggedly to their plans when all the evidence suggested that change was required.

Dealing with Risks in Strategy Execution

Dealing with risks in strategy execution is, in many ways, similar to dealing with threats in strategy development.
  1. Monitor your risks. Risks are, by definition, things that might go wrong, but have not yet gone wrong. So the first step is to actively monitor them. What indicators or signals might suggest that the risk is either increasingly or decreasingly likely to happen? Are you equipped to detect subtle changes in those indicators and signals, to communicate those changes to the key decision makers and to respond rapidly to material changes?
  2. Mitigate your risks. What can you do to reduce the likelihood that a risk does happen, or the impact on your organisation when it does? What safeguards can you build?
  3. Avoid your risks: Sometimes a risk is simply too great, and you need to come up with an alternative, less risky solution.

Dealing with Issues in Strategy Execution

An issue, as we know is a risk that has happened.
  1. Escalate the issue: The first thing to do is to make sure everyone knows that the issue has occurred.
  2. Solve the problem: Can you, or someone else in your organisation (see the previous step) fix whatever it is that has gone wrong? (This is often referred to as remediation.)
  3. Go back to the drawing board: Issues are seldom a reason to go back and revise your entire strategy, but they are often a reason to go back and change your tactics for execution. Don't stick doggedly to your plan, as if the issue has not arisen. Can you work around the issue?

Finally, if you ever find people getting too focused on the negatives in your strategy, remember the saying:

The people who think it can't be done should get out of the way of the people doing it.
Source unknown. 

PS: I could not find a proper source for the original image. If you know who made it, please drop me a note in the comments below so that I can give proper credit.

The most popular posts on strategy development and execution in 2018

Happy New Year to you all!

At the end of another year - where does the time go - I took time to reflect on the most popular posts on the Strategic Coffee blog during 2018.

Here they are:

10. What is a SWOT Analysis

Love it or loathe it, the humble SWOT analysis remains one of the most popular frameworks in the book, coming in in a respectable 10th place. See also 11 techniques to help you do a better SWOT analysis and The consistently popular SWOT analysis.

9. McKinsey 7S Case Study

This is the only case study we've ever blogged. Client confidentiality usually prevents us from writing case studies, but this one was kindly submitted by a reader. Perhaps you have another you'd like to share with us?

8. The BCG Matrix

The BCG Matrix is a portfolio analysis tool which can help you decide which subsidiary business, product or service lines you should invest in, hold or dispose of.

7. Harvey Balls Font

Harvey Balls, sometimes called Booz Balls, are those little circles with 1, 2, 3, 4 or no segments coloured in. They are useful for indicating high/medium/low, or degrees of strength without being as specific as using numbers would suggest. This post provides a link to a font you can install to make them incredibly easy to use in, say, Word, Powerpoint or even Excel.

6. How to use Porter's Value Chain Analysis

At one time, I thought Porter's Value Chain had fallen from favour, replaced by more modern alternatives such as the Business Model Canvas. This post's position on this list suggests otherwise.

5. How to use a RAID log

A RAID log is a staple tool in project management. Here, we adapt it for use as a strategic management tool.

4. Using the McKinsey 7S Framework to assess strategic alignment, strengths and weaknesses

The McKinsey 7S analysis makes a second appearance on this list in position 4. This time, it is a more conventional post explaining how to use it.

3. How to draw a Strategy Canvas in 4 easy steps

The Strategy Canvas, popularised in Blue Ocean Strategy, is a visual tool for differentiating your proposition to set it aside from the competition.

2. How to design a Target Operating Model (TOM)

In an environment where businesses must increasingly compete not just on what they deliver (products and services) but also on how they deliver, Target Operating Models are a key consideration for strategy execution. 

1. 9 essential tools for Strategy Analysis

And finally, in the top stop, our ever-popular compendium of the 9 most essential tools for Strategy Analysis. This includes a number of those lower down on this list, plus several more.

In reviewing this list, it strikes me first of all that all of these articles are very practical guides on the basics of how to develop and execute strategy. I think this practical focus is heartening in a subject which can sometimes tend towards the theoretical on the one hand, and the hyperbolic on the other.

Secondly, I notice that many of these articles were written some years ago - albeit that many of them have been updated several times since they were first published.

That may point to the perennial nature of the subject - in a field which is constantly searching for the next big thing, many of the basics of how we do so have not changed terribly much.

But it may also point to the nature of SEO (Search Engine Optimisation). Most of our readers find the blog by searching on Google or Bing and search engines favour content which has been there for a longer time.

Do these posts reflect the kind of content you'd like to read on strategy development and execution? We're constantly looking for new content to keep the blog fresh, so why not let us know what type of content you'd like to see during 2019 by dropping us a note in the comments below? I'd love to hear what you think.

Customer experience - get the basics right

Today, I was asked to print, complete, sign, scan and return by email a form from a financial services business of which I have been a customer for over 12 years. Fortunately, the form was only a single page. On that form, however, I was required to write my full name, not once, but three - 3! - times.

A good place to start is to assume that your customers hate doing data capture. There are probably three reasons for this:
  1. it is laborious and time-consuming - think: the opposite of enjoyable.
  2. they may not have all the information to hand - OK: I did have my name to hand, but that same form also required me to fill in a tax reference number, which I did have to look up, and which I had also given them on previous occasions.
  3. they're worried about the consequences of providing incorrect information - we've all been there, some forms can be inordinately complex and cause quite a lot of anxiety.
So a good customer experience should avoid data capture wherever possible. There are a number of ways of doing this:
  1. use the data they've already given you - never ask a customer to give the same information twice.
  2. build data connections to partner organisations in an ecosystem - for example, a workplace pensions administrator should get most of the member data it needs from the employer. (If your business does not yet exist within an ecosystem, your should start identifying one and integrating with it post-haste as you can be assured that your customers are using your product and service within some broader context.)
  3. build links to independent identity providers like Yoti or HatDEX, or even using Google, Facebook and/or Linkedin identity management services, depending on what is most appropriate to your business.
  4. use AI to determine and present useful defaults.
In this day and age, it is no longer acceptable to expect your customer to do extra work because your systems are inadequate and disconnected. Put the customer at the centre of your business and build a customer experience that is convenient to them.

See also:
Ironically, just after drafting this I received an email from Spotify asking me to provide them with some customer feedback. I usually complete such surveys for products and services I really like because I really want them to get even better. So I did. To my surprise, the questions included:
  • Have you ever tried Spotify? Yes, I am a loyal paying customer. I presume that is where you got my email address from!
  • When last did you listen to Spotify? Actually, I am listening to it right now. If you checked your records, you would see that.
  • How likely are you to subscribe to Spotify's premium service? Not very likely to be honest. A second subscription would seem unnecessary while I am still paying every month for the first.
Spotify, I hope you will try harder in future - I love your services, and I'd really like to help.