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The 6 factors that ensure change success

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How to ensure successful change – change management

Change management – The 6 important factors that ensure change success. We know that the claim that 70% of change programmes fail is false. However learning what can make change a better and more positive experience in organisations can only be a good thing. All too often organisations launch into change programmes with little investigation or research. Looking at what other organisations have learnt from their change experiences. Many organisations start change events with little if any recourse to any research at all. In effect the biggest failure is that people and organisations are often ill-prepared to undergo change. A new study finds that there are 6 failings of most organisational change programmes.

This briefing looks at a paper published in the new peer reviewed journal the International Journal of HRD Practice, Policy and Research.

From failings to success factors

The paper has some useful messages about the causes of failure in change and highlights the 6 important factors that ensure change success. However, it starts with the assumption that 70% of all organisational change programmes fail, which as members will know isn’t actually true. Anyway regardless of this problem, the paper does have some interesting insights into organisational change. Whilst the paper focuses on why change fails it is in essence showing the success factions. From these we can find the 6 important factors that ensure change success.

change management

The researcher cites examples of change failure like DHL experiencing a crisis as a direct result of such programmes failing to achieve their aims. They include stories of senior management being fired or resigning as a result of the change programmes not working.

They all inevitably conclude by making suggestions as to how better to manage the change / or help employees better handle the situation. The author of this paper, Bob Hamlin from the University of Wolverhampton, argues that organisations do something different. That they research other change programmes and their own organisations before taking the leap into a major change initiative.

He also argues that that Human Resources Development teams carry out the research and then work closely with management at all levels to bring about the change in a considered, timely fashion. This use of a research based solution and the use of HR to carry out the research is what caught my eye, as it is a novel approach, even though the author really needs to check his sources and assumptions a bit more closely.

Evidence-Based Human Resource Development

Human Resources teams frequently have a poor image among management. Their Learning and Development partners (the Human Resource Development practitioners) are often tarred with the same brush. As a result their suggestions carry less weight among management than they should, Hamlin argues. Further change management often sidelines these functionsThe paper calls for the Human Resource Development practitioners to gain more expertise in the business in which they work. The paper suggests, “to become truly expert, HRD practitioners need to use the findings of high quality management-related and HRD-related research to inform, shape and evaluate the effectiveness of their consultancy and change agency practice.”

3 sources for evidence-based change and human resource development

For evidence based human resource development to be most effective, the practitioner, Hamlin argues, should use the following three sources for evidence-based change:

“Mode 1 research which is about testing theory and generating conceptual knowledge,
Mode 2 research which is about generating instrumental knowledge to resolve real-life/work-based problems, and in some cases developing mid-range theory and
Use descriptive studies or the consensus view of a body of field experts.”

In building up the evidence base, HRDs are much more likely to improve their image within the company or department in which they are working and as a result will be in a much better position to help the management create change.

The 6 Failings

Hamlin found that there are 6 major failings which contribute to change failure. most of these failings centre around change management problems:

Leaders and managers not knowing the fundamental principles of change management.
Succumbing to the temptations of the ‘quick fix’ or ‘simple solution.
Managers not fully appreciating the significance of the leadership and cultural aspects of change.
Leaders and managers not appreciating sufficiently the significance of the people issues.
Managers not knowing the critical contribution that the HRD function can make to the management of change.
Trainers and developers lacking credibility in the eyes of line managers.

Commissioning Specific Research assessing the organisation

The author goes a step further. Rather than just using existing research ahead of the organisational change programme he suggests they go further. That change management needs to include dedicated, deliberate research into the organisation to make an assessment of the position of the company as it stands.

The author states, “When conducted with academic rigour, such organisation related research can lead to deep seated fundamental issues about the running of the organisation being surfaced and confronted. Examples might include those ineffective aspects of managerial/organisational culture, or specific managerial and employee behaviour that impedes or blocks innovation and change.”

Ultimately, Hamlin concludes, “both managers and non-managerial employees are more likely to accept the evidence of ineffective features of organisational life that impact negatively, or are likely to impact negatively, on the OC (organisational change) process, including their own individual performance or behavioural deficiencies. Additionally, they are more likely to advance personal opinions, reactions, and ‘theories’ that would otherwise not be revealed.”

Conclusions – how to ensure successful change

Empirical research on previous situations can show the strengths and weaknesses of a proposed new change programme. Far too few organisations use the learning from other organisations to inform their change, usually from a “but we are different” perspective. It is always better to make an error in a new way than in a way countless others have done before. Further using an evidence based approach is much more likely to reduce errors and help to speed change up.

The overarching theme of the paper is to use evidence-based practices. From this paper we can extrapolate the 6 important factors that ensure change success:

The 6 important factors that ensure change success

How to ensure successful change

Therefore the 6 important factors that ensure change success:

Find out what research exists about the areas of change you are about to undergo. If necessary or if you don’t have the time or capability use outside sources like The Oxford Review to conduct a literature review for you.
Conduct research inside the organisation to discover what real-life/work-based problems there are that need solving by the change programme.
Create theories and test them
Get the managers to a place where they understand the fundamentals of organisational change including cultural change
Have the leadership and management understand the significance of the people issues involved in change
Leverage the expertise in functions like HR and L&D.

Reference – available to members

You might also like:

Evidence-based practice makes people more flexible and adaptable

Does a performance dip always occur during organisational change?

Heros

Organisational Hero

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You Are An Organisational Hero:

You are a striver

Not for you is the mediocracy of opinion based working

It is people like you that get things done

You are a practician

You delve

You have curiosity

You ask important questions

You ask the uncomfortable questions

You look for evidence to back up your practice

You get to the bottom of things

You don’t just spout forth your beliefs

without first seeing if they are valid

You understand the vital importance of evidence-based

practice in developing organisations and people

You know 99% of everything you are trying to do

has already been done and researched

You develop and create new knowledge and ideas

You are creative and critical

You are a critical thinker

You are the harbinger of knowledge

not the spreader of myth and mere fashion

You are a knowledge manager

not an unfounded opinion dispenser

You lead

You Are An Evidence-Based Hero

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The counter-intuitive side of evidence-based practice

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What is evidence-based decision-making? It may not be what you think? The counter-intuitive side of evidence-based practice.

Opinion-based decisions

When people make decisions about things on a daily basis, for example, what eat or what to wear, they usually do so based on their own opinions, likes, dislikes, personal taste, habits and a range of other criteria which stems from from their experience as well as recommendations from friends and other influences.

This is fine if the results of those decisions only effect the individual or their immediate friends or relations. The cost of getting a decision wrong at this level is usually a sandwich we don’t like or a pair of shoes that hurt or an argument. These are what is known as opinion based decisions.

As stated above their decisions and choices are largely based on the individuals’ own their likes, dislikes, values, beliefs, emotions and habits which drive and at the same time are often a result of their own subjective and idiosyncratic experiences of the world.

What we find is that many people including leaders, managers and employees fail to make a distinction between the self-oriented decisions which abound in their personal lives, and group, team or organisational decisions in their work environment. In effect they don’t shift their decision-making habits from opinion-based decisions to more evidence-based decisions.

Decision-Making

The counter-intuitive side of evidence-based decisions

This does not mean that the opposite of an opinion-based decision – the evidence-based decision is just to find evidence to support your decision.

An evidence-based decision is one where people try to put aside their own opinions, likes, dislikes, personal tastes, habits of thinkings, values, beliefs and emotions, and look for evidence, not to support their decision, but rather for evidence against their decision.

The problem with looking for evidence to support a decision is that we are human and very likely to filter and deny evidence that doesn’t support our views. The true evidence-based practitioner turns things around. They treat a decision like a hypothesis and then look for evidence that the decision is wrong. The problem is it is very easy to be convinced by something, especially if it fits our views and make the evidence fit the decision. It is called conformation bias and everyone does it. The only way around this is to arrive at a decision and then hunt out the evidence that doesn’t support that decision and then adjust the decision until you are at a place where the evidence against the decision is either minimal or has the least noxious consequences.

Side effects

Which brings me to the next principle of evidence-based practice – there are no side-effect free decisions or perfect solutions. If you think you have the perfect solution you, most likely, have missed something. More about this in my next post.

Side-effects

Cycles of evidence searching

In actual practice what tends to happen is that we cycle the evidence search. First looking for the evidence (different from data – see here) that builds our argument or position/decision. Then in phase 2 we then search for as much evidence as we can that suggests tat this is not the right course of action and then readjust the argument to accommodate the counter evidence. This occurs in a series of iterative or repeated steps until you have a position that is tenable and where you can live with the consequences. The advantage of this approach is that at least you will know what the likely consequences will be and that you can afford them. Reducing unintended and unaffordable consequences is a big part of evidence based practice.

Other articles in this series:

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What’s the difference between data and evidence? Evidence-based practice

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Data v Evidence
Data
Not so fast
Evidence
Does it matter?
A test of evidence-based practice
Hypothesis
The crux of the matter between data v evidence is this…
Summary

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Data v evidence

Data v evidence: This is the first article in a series about evidence-based practice. In this post, I look at the critical difference between data and evidence and why it matters in evidence-based practice.

One of the cornerstones of evidence-based practice is understanding the difference between data and evidence. When people in an organisation understand this distinction between data and evidence, we tend to find evidence-based practice not only starts to become real, but also it enables people to make better decisions and judgements, and you may be surprised to find that people also become much more adaptable and flexible as well.

Now, these are big claims for something apparently as simple as understanding the difference between a couple of terms. However, in this case, understanding the distinction between data and evidence really actually changes the way people think and see things in organisations. This is why evidence-based practice has so much going for it, it does more than just improve practice

Data

Data

Before we get to understanding what data is, think about this: Data is data right? Data is either right or wrong. Now imagine that we have someone who believes Data = Facts and facts are either right or wrong. What does this person think the truth is? Usually, for these people, the truth is just a collection of facts. Collect enough facts and you get to the truth. The right way of seeing something.

This view assumes that how the data was constructed is also ‘correct’. That data just exists. They are immutable or permanent and unchangeable. The data is the data. They just are. You can’t challenge the data.
So let’s look at some hypothetical organisational data. Let’s take something that looks like solid data – a ‘fact’ in fact. Let’s take an organisations sickness data for example. The data for this organisation is:

[thrive_text_block color=”light” headline=””]

Average days sickness per person last year is 3.2 days
the average sickness the previous year was 2.9 days[/thrive_text_block]

On the face of it, there isn’t much to question here. The facts are the facts, the data are the data. Sickness is going up from 2.9 days a person to 3.2 days.

Because sickness is increasing we need to do something….

Stop

Not so fast

What if we find out that two years ago someone was considered to be sick if they didn’t turn up for work, but if they turned up first thing in the morning and later left because they were sick they weren’t counted as sick on the figures. Then this year HR decided to count people leaving work as well. Or what if they included sickness this year even if the person stayed at work but were ill (had a cold or a headache).

Hypothesis and evidence

What if not every manager records sickness in the same way, because they are busy or know someone is having problems and wants to cut them some slack. For example, Jamie is so busy he never records absence and Flo, another manager, records even the slightest abstraction, even someone who goes for a walk to clear their head? Or they forget or, or, or, …. as you can see there are many many reasons variability is likely to creep into any data.

So data is just data but on its own, it doesn’t have any validity or reliability (the two tests for good data. Validity = it measures or describes what it claims to, and reliability = it measures or describes it consistently). There is no such thing as 100% validity or reliability. There is always variation in any measurement or description and these variations can stack up. Due to the variations in components two apparently identical aircraft made next to each other at the same time can vary as much as 10-20% in weight from each other due to the compound effect of the cumulative variation.

In other words, a figure or number or a set of figures tells us very little about the context or whether the data is actually moving/changing or not. In other words, data is just a number or an observation. It has no context or real meaning on its own. 24 is data. I am on the floor is data. It is 5 am is data. These data on their own have little meaning and as we have seen, without understanding the context, how the data was collected, what data was actually collected and vitally what it is going to be used for, the data has little meaning. Data only becomes right or wrong in context.

Evidence

So whilst data can exist on its own, even though it is essentially meaningless without context, evidence, on the other hand, has to be evidence of or for something.

‘Evidence of or for something’

Evidence only exists when there is an opinion, a viewpoint or an argument. Academics and scientists call this the hypothesis. So if I am of the opinion that sickness has increased over the last 2 years in my organisation the question now becomes what is the evidence for my opinion? Well, that may well be the data I collected. So data only becomes evidence when there is an argument, a hypothesis or an opinion.

But surely that means data is evidence…. and why does this matter?

Does it matter?

Does it matter?

Data is only evidence in the presence of an opinion or argument, otherwise, it is just data and has no meaning on its own. The problem is and why this matters, is that the moment you form an opinion you start to select which data you are going to use to support your argument.

For example, if you are the opinion sickness is increasing you most likely aren’t going to include data about how many goldfish are pets in your town for example. You are however likely to use the data on a system about how many sick days have been taken over the last, say, 2 years.

A test of evidence-based practice

So using these data we see:

[thrive_text_block color=”light” headline=””] Last year there was an average of 3.2 days sick per employee, and
the year before there were 2.9 sick days per employee.[/thrive_text_block]

Hypothesis:

So does this support your opinion that sickness is increasing?

On the face of it, someone might come to this conclusion. Sickness is increasing.

But what if I told you that one employee has been receiving cancer treatment and as a result has racked up about 150 days sickness last year? How might that have affected the figures?

[thrive_text_block color=”light” headline=””] Evidence has perspective – data doesn’t.[/thrive_text_block]

Research

The crux of the matter between data v evidence is this:

Ah ok, what happens if you look at the sickness rates over a ten and twenty year period?

If we do that we find that:

20 years ago the average sickness was 15 days per person per year.

Now what is your opinion/hypothesis/argument? Is sickness increasing or decreasing? (last year it was 3.2 days on average).

What if we found that 10 years ago the sickness rate was 1.5 days a year. Now what?

Is it increasing or decreasing?

Knowing all this now significantly changes your opinion and any actions you might take or propose.
Is sickness going up or down given all these data?

Or is it just that there is some random natural variation in the data? You know, stuff just happens and some times people just get randomly sick and there is no real pattern, it just looks like a pattern seen from the perspective of two years of data.

Knowing the difference between data v evidence is very important, particularly for evidence-based practice.

Summary

When looking at the difference between data v evidence we find that:

Data is just data and has no intrinsic meaning on its own.

Evidence has to be evidence for or of something; an argument, an opinion, a viewpoint or a hypothesis.

The evidence you use depends on your argument. As we get more evidence or different types of evidence our argument might change.

~~~

In my next Thursday blog I will take this a bit further and look at the effects of believing in facts has in evidence-based organisations.

Resources Tests

Is your organisation evidence-based or opinion based? Take the test

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The evidence-based test: How evidence-based is your organisation or company really?

Evidence-based v opinion based. It makes a difference across a range of organisational indicators and predictors. Using the latest research evidence we have developed a short quiz to tell you how evidence-based or opinion based your organisation is. There are just 7 questions covering all the areas the most recent research suggests is important in an organisation. You will get a full report and analysis at the end of the test – free.

Oxford Review

What type of organisation do you work for? Take the test

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There are two types of organisation: opinion based and evidence based. The different affects the organisational culture, decision making and a whole raft of other organisational indicators. Take the test and get the report.

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Making evidence-based practice work. Part 2 – solutions

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This post follows on from the previous post Making evidence-based practice work: The 3 key challenges

In this post I will look at what the research findings are: evidence-based solutions

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Solutions

The researchers discovered that there are two primary pre-requisites for successful implementation of evidence-based practice: evidence-based solutions.

Primary pre-requisites for successful implementation of evidence-based practice

Management involvement

The first is management involvement in the whole process. This is in line with a whole slew of studies highlighting the key role middle managers play in innovation and change in organisations. Where organisations have failed (Kodak, Polaroid, Nokia, etc.) time and time again it has been shown that the perspective and lack of agility and ability of the middle managers have been central to the failure. Aligned managers, particularly middle managers hold the key to successful implementation and evidence-based solutions.

Providing relevant and understandable evidence

Secondly, the researchers found that providing access to relevant and understandable evidence (research) about practice and findings that inform decisions was a major pre-requisite for success.

This second issue of providing relevant and understandable evidence is easier in clinical situations where practice, in hospitals and healthcare for example, is usually closely associated with universities and academics. Outside of this it is important to find a reliable source that makes the latest thinking and research accessible and practically relevant.

Finding relevant and understandable evidence

The Oxford Review is an example of one of those sources of reliable, up-to-date, relevant, actionable and understandable evidence for consultants, coaches, leaders, managers, L&D, OD and HR practitioners. Indeed The Oxford Review is aimed at just this -enhancing evidence based practice; the foundation of every professionals work. Find your evidence-based solutions …

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