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Living History for Developmental Evaluation

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Developmental Evaluation (DE) is an approach to supporting the evolution and development of an innovation. This means not only helping guide where an innovation is going but understanding where it is now and where it has been. Just like human development, an innovation is as much a product of its past as it is the present decisions and that past can help inform the strategy for moving forward. But how do we properly account for the past and present context in understanding what comes next? This is where The Living History method comes in.

The Living History method comprises a set of data collection, sensemaking, and design strategies that come together to reflect on how a project comes into being, develops a focus, and evolves up to the present context. It helps provide the ‘backstory’ to the present situation and provides a means of developing a baseline – another key part of a DE.

Why does knowing this matter? Taking a Living History of a program helps surface the path dependencies of a program or innovation. Path dependencies can include those habits of mind that form, patterns of behaviour, and general routines that can develop within a complex environment and consciously or unconsciously shape the context in which decisions are made. By understanding what these patterns are, we can better prepare to address them as the program unfolds.

It’s helpful to the biases and mental models that we hold in guiding our decisions to better account for them both when things work well, but also to help understand how things didn’t work out.

To borrow from the image above: the Living History method helps you use the data collected from preparing the climb, starting up to base camp, and setting the groundwork (the trials, failures, and victories) to initiate the climb as well as the data from the actual ascent to the summit.

Introducing the method

The Living History method is something we developed to ‘backfill’ much of the information that is necessary to understand the present context of a program. Many evaluators do this kind of work with informational interviews, document reviews, and site visits, however, the means in which this data is collated and made sense of isn’t always systematic, nor is it done in a manner that recognizes complexity (which is the space in which DE is meant to be employed).

A Living History involves building that historical narrative that has been constructed by program developers (founders, staff, stakeholders, etc..) and the activities that contribute to this narrative. It draws together these ‘stories’ from the data into an understanding of the present. This present space is where the existing narrative and current construction of the program (‘what is happening now?‘) comes together. It’s also space where strategy is developed and initiated to shape what is to come (‘where are we going and how are we going to get there?‘).

Below is an image that demonstrates this process.

Taking a Living History

A Living History can encompass many different data gathering techniques. Four of the most useful are:

  1. Document review. A thorough review of foundational documents that might include things like the initial application(s) for funding, ‘pitch decks’ used to generate funds or interest, program and policy manuals, staff reviews, board meeting minutes, evaluations, and annual reports (to boards, funders, stakeholders, etc.). Some programs may have an early program logic model or Theory of Change that can be examined. These can give insight into the planning structure, theories, and reasons for establishing the program.
  2. Interviews. Connecting with the program founders, board members (past and present), investors (and funders), as well as leaders involved in the initiative is critical. Having conversations with these people will help surface both explicit and tacit knowledge held by those that helped shape the program. These interviews can be critical in understanding the logic, political context, and social dynamics that underpin the direction of the organization. It is useful to determine not only the direction taken, but the directions considered. The reason is that these ‘unexplored paths’ may linger in the minds of people and serve as a source of tension or inspiration in moving forward.
  3. Site visits. It is helpful to understand that programs – even those that are virtual such as a website or app — originate in the physical world somewhere. Site visits, when possible, help gather information about organizational culture, physical resources, and relational barriers and facilitators. Take the example of the organization that starts up as a maker space in a garage and then evolves to a large corporate high-rise office. Is the culture that was established at the start-up maintained at a different scale or abandoned? We’ve seen this with organizations that began as a start-up, grew enormously, and then abandoned the culture that was created at startup for a more conservative corporate one despite holding on to the belief that things had not changed. Only by pointing out (seeing) the manner in which things physically changed (e.g., open space vs. closed spaces, size and shape of offices) was this able to be pointed out. Further, such visits can help determine developmental milestones such as large investments of capital.
  4. Timeline. A timeline is a simple method of connecting activities — actions + decisions — together in a visual means. This helps determine and organize data about what was done, but also when it was done. This can make an enormous difference in understanding things like time lags and exploring cause-and-consequence connections between actions, reactions, and other effects.

The Role of Sensemaking

Living History is not complete without sensemaking. Sensemaking is required because, like most interesting stories, innovating through complexity is messy and full of contradictions, gaps in logic, and remarkable things that can only be understood by sitting together with all the data in one place. These emergent properties — coherence that forms from diverse sources of information as part of the process of (self) organization — are what make a program a ‘whole’ and not just the ‘sum of the parts’.

Sensemaking is collaborative, discursive, and involves debate, reflection, and a process of drawing conclusions and forming hypotheses based on data and experience. It is the process of taking the strangeness of seeing things in chunks and putting them together. What comes from this process, which is a key part of Developmental Evaluation and design, is a ‘sense’ of what happened, what is going on, and what options might work next.

It helps you understand where you and your program stand now.

Moving forward (and backward)

The Living History method doesn’t end with sensemaking, it also is carried forward.

Developing a project dashboard for innovation evaluation is a helpful means to pull together the data collected from the past, the present, and then populating it as the program evolves. The Living History method views history as being co-constructed as the program evolves and thus thrives on having new data about the present (which is always a second away from being the past) added to the overall corpus of data.

New data, when combined with what has already been collected, can provide new insights into the bigger picture. As data is added and time passes, it is possible that new patterns will emerge, which can be insightful for making decisions. This data, collected now and going forward, will later be recombined as part of an ongoing sensemaking process.

A Living History can also provide a means to document the activities that have taken place up to the present moment by systematically, although retrospectively, capturing (mostly existing) data to show what has happened before, which can be useful for organizations and programs who are starting their evaluations later than they would have liked to.

Consider the Living History approach with your evaluation. By looking at the past you might find yourself better prepared to go forward. We can help.

Photo by Aaron Benson on Unsplash

Three Questions for Evaluative Thinking

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Evaluative thinking is at the heart of evaluation, yet it’s remarkably challenging to do in practice. To help strengthen those evaluative neural pathways, we offer some questions to aid you in developing your evaluative thinking skills.

To begin, let’s first look at this odd concept of ‘evaluative thinking’.

Tom Grayson’s recent post on the AEA 365 Blog looked at this topic more closely and provided a useful summary of some of the definitions of the term commonly in use. In its simplest term: evaluative thinking is what we do when we think about things from an evaluation perspective, which is to say, a point of view that considers the merit, worth, and significance of something.

Like many simple things, there is much complexity on the other side of this topic. While we have many methods and tools that can aid us in the process of doing an evaluation, engaging in the evaluative thinking supporting it is actually far more challenging. To help foster evaluative thinking we suggest asking three simple questions:

What is going on?

This question is about paying attention and doing so with an understanding of perspective. Asking this question gets you to focus on the many things that might be happening within a program and the context around it. It gets you to pay attention to the activities, actors, and relationships that exist between them by simple observation and listening. By asking this question you also can start to empathize with those engaged in the program.

Ask: 

What is going on for [ ] person?

What is going on in [ ] situation?

What is going on when I step back and look at it all together? 

Inquiring about what is going on enlists one of the evaluator’s most powerful assets: curiosity.

By starting to pay attention and question what is going on around you in the smallest and most mundane activities through to those common threads across a program, you will start to see things you never noticed before and took for granted. This opens up possibilities to see connections, relationships, and potential opportunities that were previously hidden.

What’s new?

Asking about what is new is a way to build on the answers from the first question. By looking at what is new, we start to see what might be elements of movement and change. It allows us to identify where things are shifting and where the ‘action’ might be within a program. Most of what we seek in social programs is change — improvements in something, reductions in something else — and sometimes these changes aren’t obvious. Sometimes they are so small that we can’t perceive them unless we pause and look and listen.

There are many evaluation methods that can detect change, however, asking the question about what’s new can help you to direct an evaluation toward the methods that are best suited to capturing this change clearly. Asking this question also amplifies your attentive capacity, which is enormously important for evaluation in detecting large and small changes (because often small changes can have big effects in complex systems like those in human services).

What does it mean?

This last question is about sensemaking. It’s about understanding the bigger significance of something in relation to your enterprise. There can be a lot happening and a lot changing within a program, but it might not mean a whole lot to the overall enterprise. Conversely, there can be little to nothing happening, which can be enormously important for an organization by demonstrating poor effects of an intervention or program or, in the case of prevention-based programs, show success.

This question also returns us to empathy and encourages some perspective-taking by getting us to consider what something means for a particular person or audience.  A system (like an organization or program) looks different from where you sit in relation to it. Managers will have a different perspective than that of front-line staff, which is different for clients and customers, and different yet from funders or investors. The concept of ‘success’ or ‘failure’ is judged from the perspective of the viewer and a program may be wildly successful from one perspective (e.g., easy to administer for a manager) and a failure from another (e.g., relatively low return on investment from a funder’s point of view).

This question also affords an opportunity to get a little philosophical about the ‘big picture’. It allows program stakeholders to inquire about what the bigger ‘point’ of a program or service is. Many programs, once useful and effective, can lose their relevance over time due to new entrants to a market or environment, shifting conditions, or changes in the needs of the population served. By not asking this question, there is a risk that a program won’t realize it needs to adapt until it is too late.

 

By asking these three simple questions you can kick-start your evaluation and innovation work and better strengthen your capacity to think evaluatively.

Photo by Tim Foster on Unsplash

Developmental Evaluation Trap #4: Organizational culture

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In this latest post in a series on Developmental Evaluation (DE) and its traps, we look at the innovator’s trap of culture. In a quote widely attributed to Peter Drucker

Culture eats strategy for lunch

Culture is basically “the way things are done around here”, which includes the policies, practices, and people that make what happens, happen. Culture can be a trap when we fail to prepare for the change in how we do things that comes with adopting a developmental approach.

Just as we might fear success (discussed in an earlier post), we may also not prepare (or tolerate) it when it comes. Success with one goal means having to set new goals. It changes the goal posts. It also means that one needs to reframe what success means going ahead.

Many successful sports teams face the problem of reframing their mission after winning a championship: what it takes to win the first time is different when the motivation, context, and opportunities shift because of that victory. The same thing is true for organizations.

Building a culture of innovation

We’re not naïve enough to think that we can simply offer you a few bullet points and expect you to change your culture overnight. It is a big, important job. However, there is much research on behaviour change and organizational development that we’ve drawn on to help get you started.

  1. Manage deadlines differently. Deadlines drive much of our organizational behaviour and strategy, yet research has shown that deadline-driven work is less satisfying, that people’s decision-making gets impaired under the stress of urgency, and that priority isn’t always given to the more important tasks. Consider developmental milestones, which are similar to what we use in other areas of life. It’s a mindset that looks at tasks, accomplishments, and expectations in an evolving context with adaptive targets.
  2. Planning your stops as well as your starts. Developmental Evaluation can not only help you build out your innovation, but it can also determine what needs to stop. This means making hard choices about what kind of activities you might continue, what needs to be stopped, and what new things you wish to build out. The Tamarack Stop Start Continue tool provides a practical means to guide an organization through the process of making these strategic decisions. Deciding what you will stop is just as important as creating innovations.
  3. Measure performance compassionately. New research has emerged to show that intensive performance measurement can actually hamper the performance of an organization. Collecting too much data or making it onerous to do, not disclosing the purposes of the data, not using data collected, failing to engage those involved in the program in the design of the data collections, or neglecting to collect context-rich data that can help understand the mediators and moderators of performance are ways to alienate people from evaluation and limit its use. A strong DE approach seeks to engage users, making for more effective evaluation overall.
  4. Give data back. Show those involved in the program and the evaluations associated with it what the data reveals and what decisions are made from it. By making evaluation data transparent, you build trust, but also a culture of innovation by showing the purpose of the data and the ways in which it is used to make decisions. This kind of accounting to your users and stakeholders is part of the culture development for innovation.

By getting the right data, using it respectfully, and making it visible are ways in which the culture of an organization can change through developmental evaluation and lead to the kind of system shifts that allow great ideas to emerge and flourish.

Interested in learning more about what DE is and how implementing evaluation in this manner can support your innovation efforts? Contact us to find out more.

Developmental Evaluation Trap #3: Fearing Success

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What if you tried to innovate and succeeded? This fourth in a series of posts looking at Developmental Evaluation traps explores that question and the implications that come from being good at innovating.

A truly successful innovation changes things — mindsets, workflows, systems, and outcomes. Some of these changes are foreseeable, some are not and they are rarely ever uniformly positive. Take the strange situation that many non-profits face: most will put themselves out of business if they truly succeed in their mission.

Or consider the corporate manager who is looking to get her or his staff engaged. The benefits of staff engagement are many, including contributing more to the organization, but that also means they will ask more of the organization and require more.

The trap with Developmental Evaluation (DE) is that it provides a window into the organizations’ innovation strategy and disrupts the way in which it learns, adapts, and designs its products. It tests assumptions, meaning that some myths that an organization holds might be challenged. DE emplores organizations to use evidence to support decisions, not just precedent.

DE also provides a means to account for the work that is performed in the quest to innovate (not just what is produced), which sounds like an enormous perk for those who are used to being judged solely on production, unless you really didn’t want to put the work in and are content to simply produce the most marginal of products.

What fear looks like

The most problematic form of fear is self-sabotage.  Self-sabotage refers to the behaviours we engage in — individually or as a group or organization — that keep us from taking the actions we believe will lead to success. The reasons might have to do with social norms. If what you’re doing is normal, then it probably isn’t innovation. Innovating means deviating from what others are doing.

Risk is another fear-factor. Doing something different requires risk-taking and that means holding yourself up to possible criticism, disapproval from others, or financial costs (among others).

Further complicating things is that risk-taking and social behaviour are often linked together.

Fear also manifests in actions not taken. It may manifest in not pursuing opportunities or pursuing only those that are safe. It may be ignoring problems or asking the kind of questions that focus attention away from what is important, to what is easy. Often we see organizations seek to collect lots of data on something unimportant because it’s safer than collecting data on something that matters but is much riskier.

Fear can further manifest in things like over-researching a topic (never having ‘enough’ data’), deferring decisions, blaming the timing (“It’s just not the right time to innovate”), or complexity (“it’s too complex”).

Practical fear-fighting

How do guard against your own fear of success? There are some things we can do to better utilize lessons gained through approaches like DE to assist innovation efforts.

  1. Innovation therapy. Mental health professionals often go through and remain in some form of professional therapy or guided reflection to enable them to attune to their biases, work through their personal issues, and hone their skills with another professional. The same process of ongoing, guided, reflective practice and ‘treatment’ is beneficial to organizations as well because it creates that same social norm to talk about fears, challenges, and ambiguities. Create space for reflection, discussion, and problem-solving in your regular meetings. Make the time for innovation.
  2. Create outcomes from processes. DE is a great tool for showcasing the work that goes into an innovation, not just the innovation itself. Regularly collect the data that goes into the process — ideas generated (quality and quantity), rough sketches, prototypes, and hours worked, to name a few suggestions. These can help show what goes into a product, which is an end in itself. This makes something that seems abstract more tangible.
  3. Make change visible. Make work visible through evaluation and visual thinking – including the ups, downs, sideways and showcase where along the journey you are along a process (e.g., use a timeline)
  4. Create better systems, not just different behaviour. Complex systems have path-dependencies — those ruts that shape our actions, often unconsciously and out of habit. Consider ways you organize yourself, your organization’s jobs and roles, the income streams, the system of rewards and recognition, the feedback and learning you engage with, and composition of your team.  This rethinking and reorganization are what changes DNA, otherwise, it will continue to express itself through your organization in the same way.

These are all part of the developmental evaluator’s toolkit, which is basically a core part of innovation itself. DE can be a means to help you confront your fears, not deny them. Try these out and see how you can avoid the trap of self-sabotage and to become better innovators and learners.

Want to learn more about how to do DE or how to bring it to your innovation efforts? Contact us and we’d be happy to help.

 

 

Developmental Evaluation Trap #2: The Pivot Problem

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In this third in a series on Developmental Evaluation traps, we look at the trap of the pivot. You’ve probably heard someone talk about innovation and ‘pivoting’ or changing the plan’s direction.

The term pivot comes from the Lean Startup methodology and is often found in Agile and other product development systems that rely on short-burst, iterative cycles that include data collection processes used for rapid decision-making. A pivot is a change of direction based on feedback. Collect the data, see the results, and if the results don’t yield what you want, make a change and adapt. That sounds pretty familiar to those looking to innovate, so where’s the trap?

The trap is that the decisions made aren’t grounded in data or the decision-making is flawed in how it uses data. In both cases, the decision to change direction is more arbitrary than evidence-based.

What do we mean by this?

The data problem

When innovating, it’s important to have the kind of data collection system in place to gather the necessary information required to make a useful decision such as whether to continue on with the process, make a change, or abandon the activity. James Dyson famously trialed his products hundreds of times with ‘tweaks’ both large and small to get to the right product design. A hallmark feature of this process is the emphasis on collecting the right data at the right time (which they call testing).

Dyson has since expanded its product offerings to include lighting, personal hair products, industrial drying tools, and an array of vacuum models. While the data needs for each product might differ, the implementation of a design-driven strategy that incorporates data throughout the decision-making process remains the same. It’s different data used for the right purpose.

Alas, DE has given cover to organizations for making arbitrary decisions based on the idea of pivoting when they really haven’t executed well or given things enough time to determine if a change of direction is warranted. Here are three things that one needs to heed when considering DE data.

  1. Process data. Without a clear indication that a program has been implemented appropriately and the constraints accounted for, how do you know that something ‘failed’ (or ‘succeeded’) based on what you did? Understanding what happened, under what conditions, and documenting the implementation behind the innovation is critical to knowing whether that innovation is really doing what we expect it to (and ensuring we capture the things we might not have expected it to do).
  2. Organizational mindfulness. The biggest challenge might be internal to the organization’s heart: it’s mindset. Organizational mindfulness is about paying attention to the activities, motivations, actions, and intentions of the entire enterprise and being willing (and able) to spot biases, identify blind spots, and recognize that, as much as we say we want to change and innovate, the reality is that it is disruptive for many people and something often unconsciously thwarted.
  3. Evaluability assessment. A real challenge with innovation work is knowing whether you’ve applied the right ‘dosage’ and given it the right amount of time to work. This means doing your homework, paying attention, and having patience. Homework comes in the form of doing background research to other, similar innovations, connecting to the wisdom of the innovators themselves (i.e., draw on experience), and connecting it together. Paying attention ensures you have a plausible means to connect intervention to effect (or product to outcome). This is like Kenny Rogers’ Gambler:

you got to know when to hold ’em

know when to fold ’em

know when to walk away

know when to run

An evaluability assessment can help spot the problems with your innovation data early by determining whether your program is ready to be evaluated in the first place and what methods might be best suited to determining its value.

The decision-making problem

Sometimes you have good data, but do you have the decision-making capabilities to act on it? With innovation, data rarely tells a straightforward story: it requires sensemaking. Sensemaking requires time and a socialization of the content to determine the value and meaning of data within the context it’s being used.

Decision-making can be impeded by a few things:

  1. Time. Straight up: if you don’t give this time and focus, no amount of good data, visualizations, summaries, or quotes will help you. Time to substantially reflect on what you’re doing, discuss it with those for whom it makes sense.
  2. Talent. Diverse perspectives around the table is an important part of sensemaking, but also some expertise in the process of decision-making and implementing decisions — particularly in design. An outside consultant can assist you in working with your data to see possibilities and navigate through blindspots in the process as well as be that support for your team in making important, sometimes difficult, decisions.
  3. Will. You can give time, have talent, but are you willing to make the most of them both? For the reasons raised above about being mindful of your intentions and biases, having the right people in place will not help if you’re unwilling to change what you do, follow when led, and lead when asked.

Developmental evaluation is powerful, it’s useful, but it is not often easy (although it can be enormously worthwhile). Like most of the important things in life, you get what you put into something. Put a little energy into DE and be mindful of the traps, and you can make this approach to evaluation be your key to innovation success.

Want to learn more about how to do DE or how to bring it to your innovation efforts? Contact us and we’d be happy to help.