Why brand awareness is the most important thing for an organisation now


Things sell themselves these days.

Whether we’re talking about placing products in front of consumers, or trying to persuade others to adopt a particular strategy in an organisation, the point at which we reach them is crucial.

The traditional approach of a funnel, where we go through defined stages is starting to show its age – because it can’t cope with the idea that consumers may know as much, if not more than product and service providers.

Take recruitment, for example.

For a long time, the only way for a person to understand what it was like working for a company was to ask friends and family who worked there, or apply for a position and spend some time working there.

So, they entered a funnel – experiencing the recruitment process, negotiating salaries, starting work, mixing with their colleagues, understanding the hierarchy and so on.

Now – they have access to much more information on the working experience at a company – especially if it’s a large one.

For example, Glassdoor has 5,021 review of Barclays, 8.596 salaries and 1,920 interviews with employees.

A prospective employee looking there will know more about how the company treats its staff than almost anyone else internally, especially the top management.

The democratisation of information has levelled the playing field in every aspect of organisational interaction.

Most service and product providers understand their products in detail, but spend less time comparing themselves with others than potential consumers.

The consumers therefore are more likely to have a better understanding of the market and trends and the differences between brands, just through the basic research they do before engaging with providers, than the brands do themselves.

This change in the way of how consumers interact with products and services has been called the customer decision journey by McKinsey.

In this model, consumers start with an initial consideration set, a collection of brands that they are aware of and may have been exposed to recently.

They then get information from a wide variety of sources – internet reviews, personal recommendations, traditional media – which all contribute to an active evaluation of their options. At some point, they reach a moment of purchase, where they decide to go with a particular option.

According to the customer decision journey model, this is where the hard work begins.

The postpurchase experience then shapes success or failure.

Many people, once they make a decision, experience a degree of anxiety.

The first thing they then do is to go online and check that they have made the right decision – looking for reassurance from others in the same position.

This works, sometimes, as they get more information, realise that they are with a good brand and are reassured. On the other hand, they may see more information from competitors that show them what the alternatives might be.

The trigger for entering a loyalty loop and making follow on purchases depends then on the quality of what they get and their ongoing assessments of the options open to them.

This continuing change in the way consumers make decisions is changing everything from sales to recruitment in an organisation.

And the starting point – the thing that one must do to even play the game – is to be included in the initial consideration set.

And that means that the potential consumer needs to be aware that a particular organisation exists – it needs to be discoverable.

Which brings us back to the importance of brand awareness: why it matters so much now, and why it will become even more important in the years ahead.

When will a new app or IT solution benefit our work?


For many of us, a standard work IT package consisted of a laptop or desktop and a Microsoft Office suite.

That has let us do most things for a number of years, and remains a solid foundation for the kind of day-to-day office work we need to complete.

In most functions, however, the number of tool options are exploding.

Take the graphic below from Scott Brinkler who writes the Chief Marketing Technologist Blog. It shows the marketing technology landscape where we can now choose from 5,381 solutions from 4,891 unique companies – and has grown from around 150 to 5000+ in six years.


A similar transformation, although less dramatic, is happening across other organisational functions.

What are the things that managers who are tasked with investing in tools for users that need information systems and tool developers trying to develop such tools need to keep in mind – given the inevitable competition they will face?

One approach comes from a paper by Mark T. Dishaw and Diane M. Strong that puts forward an integrated model that tries to explain the likelihood of a tool actually being used.

It combines two existing models, and the new, extended version is more effective than either alone.

First, the Technology Acceptance Model (TAM) suggests that actual tool use depends strongly on an intention to use the tool.

The strength of the intention depends on the user’s attitude towards use, which in turn is a result of his or her perception of how useful the tool might be and how easy it is to use.

The Task-Technology Fit Model (TTF) focuses instead on the ability of technology to support a task – and matches the technology to what the task demands.

This fit depends on the tool functionality and the task characteristics – and suggests that a rational assessment that matches functions to tasks will result in the best choice of solutions.

The TAM depends on perception and attitude while the TTF focuses on rationality and comparison.

In reality, we use both, and the extended model, shown in adapted form in the picture above, is an integrated model that selects from parts of the TAM and TTF and connects them with the hypotheses set out in the paper.

It turns out that this extended model explains more about actual tool use than either model on its own.

How can we use this when selecting and implementing a technology stack in our organisations?

To start with, this model gives us an approach to scope what is required in terms of both technical capability and user-centric capacity.

All too often we select a package based on the sales pitch and technical functionality, forgetting that the value it will add depends on how the people in our organisation use it – and they will default to using systems they find easy and useful.

And the quality of our choice will show up in the statistics of actual tool use.

How do we search for information in a data world?


The first thing we often do now when confronted with a question is to search.

We open a browser and go to Google and get going.

The proliferation of smart devices and AI assistants like Alexa and Siri will only intensify this approach – we can no longer hope to know everything because there is just too much out there.

This is well understood when it comes to marketing – experienced internet marketers know that they need to study search histories and trends and design content that addresses the way in which people search for content.

We are starting to see this in documentation and support pages for some companies, where instead of browsing through a list of topics we are encouraged instead to search or ask a question and the system tries to answer it or find relevant information.

It also has ramifications when it comes to training – the traditional classroom based approach to professional development can give employees an overview, but the individual challenges they face in their work are usually addressed through a search.

So, is it useful to have a simple model of the purposeful activity that people go through when searching?

Possibly – and that is what is shown in the picture above.

This is a representation of Marcia J. Bates’ 1989 berrypicking model of searching online.

In this model, the user might start with just one feature of a situation, to create a search query.

For example, this post started with the search query model of information search online in order to investigate current models out there.

That led to a paper which set out a number of models, from bibliographic or directory based approaches to linear models where the researcher moves systematically from a vague understanding to a focused one.

Looking at the variety of sources, the one that stood out, however, was Bates’ berrypicking model, because it matched how we do things now.

So that led to modifying the query to refine and gather more information on the berrypicking model, until a satisfactory completion point meant that the model could be expressed in the form of an human activity model, as in the picture and accompanying explanatory text.

So, why is having such a model in mind useful – and why is it any more useful than simply following a standard marketing approach of following a checklist and looking for Google keywords.

The key reason is that having the model in mind allows us to better organise the learning process associated with the creation and presentation of information online.

We can ask ourselves whether we have selected the key features that matter from the user’s perspective?

We can come up with search queries and match them against search engine data, especially around long tail searches.

We can also compare how our content matches up against other content from a variety of sources and come up with a plan to modify or improve what we are doing.

Finally, we have little control over when a user feels satisfied, but we can aim towards helping them move towards that point with well designed material.

Most organisations will find that they are in the middle of a transition to a user-centric, search based and information rich world.

Focusing on how users search will be essential for how businesses stay in business in this future.

What’s the difference between a plan and a novel?


We all make plans – from planning a trip to setting out a marketing strategy for the next five years.

There are many moving parts in a business environment – from internal capabilities, dynamics and politics to external influences like regulation and social transformation.

What differentiates one kind of plan in such a dynamic environment from another?

Is it success – if a plan succeeds is it a good one?

Or is there something about the nature of the plan itself – does a good plan have a particular architecture?

Take marketing on the internet, for example.

Search engine optimisation or SEO is something that many people try and sell – ways to manipulate search engines into ranking sites above others – and it was popular in the early days of the web.

So, is that something that we should do now?

Looking at Google trends – perhaps not. Interest in the term has steadily dropped over time as search engines have become smarter, using semantic analysis and tracking to provide hyper-personalised content.


SEO these days is more about making it easier for the engines to understand what we do rather than tricking them.

A plan based on taking a shortcut or tricking the system may work for a short while.

It can then form the basis of a story, which can be used to sell the plan to others – but it’s unlikely that the results will be reproducible to the same extent.

And that’s the operative word – what distinguishes a plan from a novel is that the former is designed to produce reproducible results while the latter is a narrative of what once was and what might be.

The picture above is from Peter Checkland and Sue Holwell’s book Information, Systems and Information Systems: Making Sense of the field and sets out the basic architecture of a research process – something that can be generalised to much of business.

We start with a framework of ideas – things we believe about our environment.

Taking the marketing process again as an example – these might include the importance of video, a belief in the process by which concepts go viral and the extent to which elements of the work can be outsourced.

The standard process is to them come up with a strategy, a plan and then apply it to an area of concern A – the sales process or pipeline management.

Directors set targets, managers review progress and the standard process rumbles on. Perhaps they hit targets, perhaps not – that’s not really important.

What’s important is the bits that are missing.

A set of ideas by themselves are just opinions. What makes them useful is setting out, in advance, the methodology that underpins our strategy and plans.

Our objective is to cause a change for the better in the area of concern that we are looking at.

Continuing with the marketing example – we may be able to see and measure the change in a metric like sales – but that is an output of the process.

What’s important is that having the intellectual structure in place – a framework F, methodology M and an application area A – then lets us reflect and learn about the system we have put in place.

It’s the learning that matters – and that’s what helps us adjust and refine our plan and create an approach that produces predictable results.

And this is perhaps the biggest thing we miss when we think about a plan in the narrow sense of having a goal or target and define success as hitting it and failure as missing it.

The journey we take and the lessons we learn are just as important – if not more so.

We often learn more from failure than we do from success.

How to take your company digital


Amazon is ruining things for many businesses – teaching customers that they can expect to get products and services quickly, have a great user experience, no errors, 24-7 availability and personalised interfaces – and save money and time.

What about everyone else? How should they think about transforming their organisations to stay competitive?

Tunde Olanrewaju and Kate Smaje from McKinsey set out seven traits in this article that they have discovered effective digital enterprises share – and that we can use as a blueprint for our own programmes.

Going digital is less evolution and more reinvention.

We need to set unreasonable goals, make choices about targets and strategies that make people around us nervous about the scope and extent to which things will change.

Someone, somewhere is working on an idea that will make our existing business obsolete, our products expensive or redundant and that will satisfy our customers more.

We need to work on destroying and rebuilding our business before they do.

And the skills we have in the organisation now are not the ones that will take us there.

We need to recruit for skills, not experience.

The capability that built our organisation is unlikely to be the same capability needed to build a new digitized one.

The kinds of people needed – developers, user experience designers, system architects – are likely to be in other fields and need to be recruited.

Most organisations will be better off in the long term with in-house capability because a digital transformation is a core strategic initiative.

Then, talent needs to be protected, perhaps in a Skunk Works.

Lockheed Martin’s Advanced Development Programs are referred to as the Skunk Works, a group given a high degree of autonomy and freed from bureaucracy, and told to get on with new projects.

It’s very hard to stick talent in the middle of an existing organisational structure and expect them to innovate.

The resistance from people used to business as usual is too much, and can slow everything down.

Nothing is sacred – challenge everything

When going through a transformation, every aspect of the business and how it works needs to be questioned.

Do certain processes have to be carried out? Are there things we can stop doing?

A formal way to this is a method called Final Cause Analysis (FCA).

We ask what is this for? over and over again – and focus on the essential elements we discover as a result.

We haven’t got a year – we need to move fast.

These days no one has 12-24 months to put a new system in place.

We’re talking weeks and months to getting working systems that we can test and refine based on customer feedback.

Lean and agile ways of working are taken for granted now.

There are more projects than we can do, so we need to prioritise based on value – follow the money

Our projects will help us increase revenue.

At the same time, and as importantly, they can help us cut costs.

We need to rank our projects based on contribution to the bottom line and then commit to a programme – putting money, resources and management in to get things done.

All of this effort and reinvention is focused on one thing – the customer.

Customers leave because they are unhappy – so successful digital organisations are obsessed with the customer and their experience (in a healthy way).

Digitization is not a choice – it’s just what we now have to do to stay in business.