Cense

Innovation to Impact

Activity Analysis

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This simple technique is among the most powerful at eliciting a lot of information. When we look at an existing service, it may be easy to describe what people do to deliver, manage, and receive the service in simple terms. For example, an exchange between a bank teller and a client might be described as simply as a person walking up to a desk, asking for money, inserting their bank card, receiving money from the teller, and leaving.

An Activity Analysis would break this down even further. It would involve tracking the experience of the client. It would denote what the client did from the moment she entered the bank, what she saw, what she smelled or experienced, her feelings or thoughts, and the steps she took toward the desk.

You might ask how long she took, whether she stopped en route to the desk, knew where it was (did she ask for directions?) or did she wait in line and for how long.

We can also track what the teller was doing up to and including the moment of engagement with the client. What tasks was she doing? Where was her focus? What is she thinking or feeling?

This is a micro-method version of A Day in the Life, which is another method that helps us understand what our service clients do and use.

How to do it

Activity Analysis can be done as a group, facilitated by a leader to help organize and manage the activity. It’s a great way to get people talking about all that is going on with the actors, the environment, and the tasks. By opening up the discussion and walking through each step in the journey through the service with each actor, everything that shapes the environmental conditions, and the tasks that are performed, you’ll reveal an enormous amount of data about what actually transpires with even the simplest transaction.

This can be used to seed further questions like:

  • What infrastructure is needed to support the interaction?
  • What would be ideal?
  • How might this interaction look different?
  • What other variables could affect the journey and the outcome?
  • What could be done or introduced to make this better?

Activity analysis is something that can be done in small groups over the course of 20 to 60 minutes, depending on the complexity of the task and the amount of knowledge the participants have of the task or activity.

This simple analysis can reveal information about flows, resources, outcomes, and processes that are in place to support your service and help you see what’s not only in place, but what is possible, too.

This can be a great way to bring people together as well as lead your service design and evaluation efforts. If you want to implement this approach in your organization and need help, reach out to us. We’d welcome hearing from you.

Forecasting

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You might not have a crystal ball, but you can still envision the near-future by using a simple strategy called forecasting to plot your strategy for the coming months. Here is how.

Fundamentals

A forecast is a data-driven prediction of possible outcomes that can be used to generate scenarios. The first item required is data. This can be qualitative, quantitative, or mixed and from primary or secondary sources. Most often, forecasts are a combination of these.

Checklists have been found to be useful tools to help organize data that contribute to forecasts. Pull together those sources you have and then organize them in a manner that allows you to build a narrative — a story — of what has happened to allow you to better anticipate what might happen.

Forecasts work when there is some expectation of a linear progression from time to time (with some variation). Time series data — data gathered on the same topic/issue/item multiple times over in succession — is among the most popular sources of data. This will allow you to see patterns and spot trends that lead you to now.

Add Imagination

Once you’ve developed a model of the present situation, the next stage is to imagine what might happen in the near future. Forecasts are generally useful for predicting near-term (e.g., 3-, 6-, or 12-months) outcomes and are less useful for longer-term assessments.

Next match data from other sources — social trends, government policy documents, census data — to create scenarios. For example, seasonal trends can change the near term. ‘Seasons’ like ‘back-to-school’, holidays, flu trends, weather changes can all affect how present data can mislead us for future activities. The COVID-19 pandemic provided an example of the various ways in which an economy can re-open, a healthcare system can respond, and what ‘back-to-school’ looks like.

From these data points, work together as a team (this is always better done in groups because different people will see data differently) we can start to envision possible futures and outcomes.

Look for amplifiers and dampeners. What things might make an existing trend more pronounced and what might dampen that trend, or extinguish it altogether. In discussion as a group you can

Structuring Forecasts: Tips & Tricks

Begin your group work together with a few simple ‘rules’ to guide your discussion. Start with limiting any feedback or critique of ideas at the start. You want to explore why something could happen, not assess the likelihood of such activities at first. This opens our minds up to unlikely scenarios.

It’s helpful to have someone on the team who can play the role of the ‘black hat‘ – the person whose role is to illustrate why something won’t work. Edward DeBono’s ‘thinking style’ roles can be useful here in helping us structure a way to look at the data and ideas from different points of view. Building on these different perspectives, it’s important to build a variety of scenarios and attach a level of anticipated likelhood to them. (e.g., high, medium, or low) and timing (e.g., imminent, soon, long-term, etc..)

Build out as many scenarios as the data suggests might be useful. This is often three to five, but rarely nine or ten.

From these scenarios, ‘walk them back’ to the present using an approach of asking “what happened just before X” and repeating that of each answer until you find yourself at the present. This allows you to start building pathways of potential causality.

While it may be that none of the scenarios come into reality, there are likely to be pathways that resemble them. When you find these, your team can use those to examine the assumptions that you hold with each one of them and use that to develop a strategy around them to better increase your anticipatory awareness and adaptive capacity to learn and act.

Taken together, this method can help you to see what might be coming and plan accordingly. It is a powerful means to explore near futures and design your organization to be better suited to living in them rather than having to play catch-up.

To go even deeper, the Future Today Institute has developed this useful ‘Funnel’ model to guide forecasting that might be useful to you as well.

FTI-Funnel ToolDownload

If you want to develop forecasts, contact us. We can help you see what might be coming and design your team to better meet it.