Tag Archives: agile strategies

5 Golden Rules for Flexible Project Management

13 Jun

I previously wrote about methods to improve two aspects of project management

  1. Knowledge capture, and
  2. Communication

A focus on the importance of capturing knowledge and improved communication was inspired by a recent publication by Raconteur (Project Management, raconteur.net, #0376, 22\05\2016). Within this Raconteur publication was a piece entitled “The Five Golden Rules of Project Flexibility” (p.4), and provides the inspiration for this article.

Flexibility is essential for sustainable success, but for human beings, it can be very difficult to think and behave with flexibility. Below, I’ll outline some reasons behind this difficulty, before revealing Raconteur’s 5 Golden Rules.

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Health Care and the Tacit Database

24 May

In a recent article (here), I discussed the potential of an organisation’s tacit database- an organisation’s frontline expertise and rules of thumb which are highly effective, but remain hidden from the wider organisation.

Tacit skills can remain hidden due to a separation between planners and frontline workers. For example, when a strategy is created by a planner (director, manager, board etc.) it is adapted to local conditions by frontline workers. This results in the strategy being changed, so it is more effective in a particular situation. Unless the adaptions are feedback between the frontline and the planner, these adaptions are lost, they become “ghost cases”. The adaptions represent the application of theory into practice, and unless this interaction is recorded, the opportunity to continually learn, improve and adapt is wasted.

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Detecting Errors in Strategy

19 Sep

This is a quick introduction to the Spiral methodology we’ve designed when applied to strategy error detection. When any organisation, policy unit or research team are putting together a strategy or plan aimed at realising future goals there are 4 levels of potential error they should be mindful of.

Level one is the acquisition of knowledge. The first port of call when making a decision on future direction is the collection of data. If you’re getting data from people or from any complex system (systems which involve people) then you need to avoid potential areas of bias such as memory decay or data fixation (Wilson and Gilbert, 2003) and capture expertise (Hoffman et al, 2006). The Spiral seeks to compensate for bias by applying research methods for data collection from complex systems which are designed to minimise the presence of bias. This wouldn’t be the primary source of data collection, but it would place assumption testing on all data and support insight.

Level two is the analysis of this knowledge. What scripts are people using to make sense of it? There is always a script at work when reading data, the script of the individual (the CEO for example) and\ or the script of the organisational culture. The methodological goal here is to ensure that the data is read with a broad frame, one which considers other potential scripts, as oppose to a narrow frame, one which only considers and analyses through a single script such as the more complex the analysis the less chance of blame. Changing the perspective on data, by simply changing statistics to frequencies for example, has incredibly powerful effects on decision making effectiveness (Kahneman, 2011, Gigerenzer, 2014).

Level three is the gap between planners and implementers. A simple way to illustrate this level is through communication. Within an organisation there is always formal explicit knowledge-the guidelines and procedures for example. Also within an organisation is the informal knowledge, how things really get done. Creating plans which only deal with the structural side of the organisation and expect appropriate changes in behaviours are doomed to fail (see Klein, 2013, Weick, 2009).

These plans fail because expertise and insight become diluted by procedures and processes. What manifests are large gaps in reasoning between planners and implementers. The aim here is deploy simple but effective research methods which close this gap and get reasoning on a similar level. The pay off here is clear intent- the ability of people to achieve objectives, independently, even when things go wrong. This increases innovation and reduces the cognitive load on managers by reducing the frequency of the question- what should I do next?

Level four is forecasting, the anticipation of future states. The other three levels all feed into forecasting, perception is information based (Hoffman et al, 2006). Research suggests that forecasting is particularly susceptible to bias (see Wilson and Gilbert, 2003 and Kahneman, 2011 for some good examples). With this is mind the goal is to use methods which reduce bias in anticipation, such as prospective hindsight (Klein, 2007). Not only can these methods make forecasts more realistic it can also improve general risk management, resilience and adaptability.

This has been a very short introduction to the four levels where errors can occur in strategies and plans. In a future article I’ll provide more detail on some of the research methods we use to locate and address these errors.

References
Wilson, Timothy D.; Daniel T. Gilbert (2003). “Affective Forecasting”. Advances in Experimental Social Psychology 35: 345–411
Kahneman, D. (2011). Thinking Fast and Slow, Allen Lane 2011
Gigerenzer, G. (2014) Risk Savvy: How to Make Good Decisions. Allen Lane
Klein, G. (2013) Seeing what others don’t: The Remarkable Ways We Gain Insights. Public Affairs
Weick, K. Making Sense of the Organization (Volume 2) The Impermanent Organization, Blackwell
Hoffman, R. Crandall, B, Klein, G.. (2006) Working Minds: A Practitioner’s Guide to Cognitive Task Analysis Cambridge, MA: A Bradford Book
Klein, G. (2007) The Power of Intuition: How to Use Your Gut Feelings to Make Better Decisions at Work. Currency

Decision Making in a Zombie Apocalypse

24 Oct

Having recently returned from New York and been lucky enough to get a close view of the comic and TV show The Walking Dead and its team, I began thinking about the cognitive challenges of surviving and thriving in a zombie apocalypse. This line of thought actually gave me some insight back into business and management too, the two fields clearly overlap.

Firstly a zombie infection is a public health disaster. The R0 is used by epidemiologists to calculate the number of cases one infected person (infected with SARS for example) generates within the general population. SARS has an R0 of 2-5, meaning 2 infected people, infect 5 healthy people, a zombie R0 could well be 10-10,000, so it’ll certainly bring society down before society brings down the infection. So, were dealing with the aftermath and this is what the Walking Dead focuses on.

Slow moving zombies tend to be predictable, they don’t seem to have intelligence in the sense that they can’t use their memory to predict and develop innovative adaptations. They tend to flock and herd in patterns that are hard to anticipate but due to the lack of intelligence should be relatively easy to prepare for, so you can structurally prepare with a fair amount of reliability. So, once you’ve established a habitable enclosure in this environment it should be relatively “simple” to develop a series of survival tactics you can make routine and intuitive; you can begin building a supply line for food and water with the aim of becoming self sufficient.

All this has been covered in the Walking Dead as groups of survivors develop well enclosed communities with supply lines and a clear plan for self sufficiently. The real threat however comes from other survivors. With resources so scarce and dangerous to obtain the opportunity to just take what is attractive and useful makes a lot of sense. And with no law or regulator to step in it’s all down to guerrilla tactics. These resource grabs can be sudden, brutal and unpredictable.

This is the irony, due to the relatively stable behaviour of zombies you can get used to them and adapt, with an understanding that there will be steady losses within the community. But, the other survivors, the remaining people, you can’t predict, some are brutal, others benevolent and others playing a game far too long to be able to draw any conclusions. And so it is in business, there are elements of the environment which you build a stable base on but when it comes to the behaviour of people, whether customers, markets or patients you need to be prepared for anything.

This is the decision making take away- be realistic about what is stable and predictable in your environment, and prepare agile strategies for dealing with the vagaries of people. It’s easy to think you can model behaviour and markets but when you take a look at life stripped to the bare bones you can see that the biggest threat or missed opportunity is rapid changes in people’s behaviour that nobody saw coming.