Cense

Innovation to Impact

Evaluation for Change

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Change is everywhere it seems and while it can be said it is the only constant what we are seeing is an increase of change on a massive scale.

However, as the protesters across the United States, Canada and beyond are making clear: there is a big difference between talk of change, the process of change, and the outcome of change efforts. Evaluation can be a powerful tool to help us distinguish these things together as they can be conflated too easily.

Here are three things to consider when seeking to make these distinctions that can be applied anytime, but become more salient when focused on large-scale change efforts where much is happening simultaneously.

Document your baseline

A baseline is a starting point and while it would be great to have data from yesterday, if we are seeking to gather change-related data today that means this is your baseline. Too often baselines are forgotten because any effort to measure or track change needs to answer the question: change in relation to what?

How? Pick the most convenient, proximate moment to gather data. Aim to capture descriptive data of what is happening, time data (see below), and also any numerical aspects of the phenomenon you can. These can be such things as cases of something, number of participants involved, descriptions of the current situation. From this, you can later build a backstory that can help lead to the present moment.

For example, George Floyd was arrested and killed by a police officer on May 25, 2020. It is possible to use that as a baseline for what came next and later build the backstory by showing the many different incidents of a similar nature that may have happened locally, nationally, and beyond to illustrate historical patterns of things like police behaviour, protests, violence, racism or otherwise depending on what changes one seeks to make.

Gather real-time data whenever possible

It’s tempting to gather data after an event (e.g., protest, policy decision, etc.) has taken place (and sometimes that’s unavoidable), however, there is much evidence that we lose perspective and critical information in our post-event reflections that often fail to capture critical details of what actually happens.

How? During the COVID-19 pandemic we have seen many examples of this with live reports from doctors, nurses, and other caregivers working the front-lines of healthcare responses. We’ve seen infectious disease specialists giving interviews on television, exchanging data and opinion via email and Twitter, and through first-hand accounts of citizens dealing with the various policy decisions made. These micro-narratives can make for a strong experiential case for what is happening and what effects the event is having. Reviewing social media posts, proposing online diaries (e.g., selfie video testimonials) or using ‘speakers corner‘ sites or physical booths to allow people to document what they feel, think, say, and do in real-time will provide a more accurate and adaptive means of understanding what is happening as it happens, rather than just retrospectively.

Timestamp your data

Time is a critical contextual factor that can help us understand what happens, why it happens when it does, and to better make sense of the outcomes. The Greeks classified two types of time: Chronos (‘clock time’) and Kairos (‘relative’ time) . Determining what time (as in hour, date etc..) can help you to organize things in chronological order and see relationships between change-making efforts. Relative time — proximity — helps us see the effect of certain activities in relation to others.

How? Modern recording tools often have this built into them, but for the evaluator it is important to record when things happen and document the sequencing of things. Big events like the two we’ve used — the race riots and pandemic — have so many moving parts that it quickly gets difficult to remember retrospectively what happened in what order. This is critical if we want to develop a theory of change or explain what happened as part of the change process.

These three things are all simple and can be done with tools like phone cameras and gathering things in a spreadsheet. More sophisticated ways are available as well and, ideally, there is a method and plan prior to a change initiative taking place. But as we’ve seen, sometimes change just happens. If it does, you’ll be ready to capture it and learn from it before it comes to pass and be able to tell if it doesn’t.

Stay and be safe.

If change is something you need help understanding and documenting, don’t hesitate to reach out and contact us. Evaluating, supporting, and guiding change efforts is what we do.

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Better Data Collection

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With so many people working from home and using their communication devices to do many of the tasks we once did in other ways or are now doing much more often or differently it’s tempting to think: it’s a perfect time to reach people for my research project.

That might be true, but it’s also fraught with problems. Before you set out on your ethnographic journey through the lives of your stakeholders or prep Surveymonkey for its journey through the jungles of the Internet we suggest you take a pause and consider the following before venturing forward.

  1. Context counts. Every time we engage in social research we must account for context. In the current situation with a global pandemic, we don’t know what the context is. The epidemiological, social policy, economic, and communications landscape is changing day-to-day and is influenced on a global level. With so many areas changing at once, the ability to gauge or even state the context becomes nearly impossible without resorting to over-generalized or vague statements like “complex” or “uncertain”.
  2. ” Seeing is not the same as looking”. Physician and economist Anupam Jena provides a great example of how we can miss the forest for the trees without examining some of the things that are hidden in plain sight. In times of profound transformation, we might need to re-think what it is we see as that will shape what questions we ask, what data we gather, and what answers we discover.
  3. User-experience. What is the state of mind of those who are answering your survey or responding to your interview? You might be speaking to someone who hasn’t left their house in three weeks. They might have people nearby all the time. This will determine the willingness or ability to respond, the kind of answers that are provided, and the openness of the response (for example, people might not want to share highly personal data on a shared computer or where people might see them entering or speaking about it).
  4. Sensemaking. When we don’t understand the context or its entirely new we look for what we know. The challenge right now is that we don’t know what it is that we’re looking at. Unless our research or evaluation work is focused on the now and understanding how and what we are doing at this moment, about this moment, and for this moment we risk developing data that is examined through the lens of history (what we’ve done before), which will be another context altogether. We’ll be making sense of the past through the lens of today.
  5. Attention. Are we paying attention? When so much of what we are exposed to now is coming through screens — big and small — there is a likelihood that we are reading things quickly. Electronic reading is not the same as reading paper-based text and tends to encourage skimming. When what we have read is — save for the back of the cereal box at breakfast — almost entirely digital (for many of us) the likelihood of instructions being skimmed might be higher. Proceed with caution.
  6. Health. Lastly, how well are we? When the effects of being inside, isolated, and perhaps exposed to a virus are real, present and pervasive, your audience might not be in the state where the depth and quality of thought are what we need to get the responses we want. Many of us are not our usual selves these days and our responses will reflect that.

See differently, think differently and that goes for how we assess and do our social research.

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Developmental Evaluation Preparedness

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Pilots have a pre-flight check before they fly a plane. A developmental evaluation journey requires the same kind of preparedness.

Developmental Evaluation (DE) is an approach to strategic learning designed for understanding and supporting innovation. This approach to data-driven learning requires a specific set-up to do well. While we need a mindset, skillset, and toolset to do DE, we also need a receptive system to make it all work.

Here are the things you can do to lay the groundwork for doing DE and making it a success. Think of this as your pre-flight checklist for a journey of learning together.

These are attributes and may be found within individuals, but it’s better if they are distributed widely across the organization.

Mindset

The most important aspect of a Developmental Evaluation is creating the right mindset. This mindset is focused on complexity, adaptation, and development (vs. improvement, linear growth). A list of statements to examine whether you have the right mindset is available on Censemaking and can provide a start.

Some other mindset questions include:

  1. Openness to experience. A DE will likely take a journey that can’t be fully predicted, much like a road trip. An openness to a non-linear pathway toward a preferred destination and the willingness to adapt the path and the destination based on evaluation data and evidence is key.
  2. Tolerance for ambiguity. Few of us enjoy uncertainty, but we all need to deal with it when working on a DE.
  3. Self-awareness. We often get in our own way. Understanding how we think and the biases and perspectives we hold is important to knowing when they serve us and when they are a barrier to innovation. Mindfulness is a part of this quality.
  4. Patience. This is a skill and mindset quality. Knowing that things will unfold at a time and pace that might change is useful — and requires patience in just knowing that.
  5. Evaluative thinking. This is a form of thinking that gets us connecting our activities, outcomes, and effects and asks three key questions about how we know something (and what to do about it).

Skillset

Developmental evaluation is not for the unskilled. While many of the qualities inherent in a DE are natural to people, they are not commonly practiced in organizations. DE is an approach, and while a skilled evaluator might have many methodological skills to do much of what is in a DE, without the following skills — with the evaluator, the evaluation team, the organization, or all of them — you won’t likely succeed.

  • Facilitation. A DE is a collaborative endeavour. You need facilitation skills to engage the diversity of perspectives in the system and coordinate the discussion, feedback, and opportunities for everyone to engage with these perspectives.
  • Sensemaking. Sensemaking is a participatory process that involves taking data that may be difficult to understand, ambiguous in its conclusions, or incomplete and helps people make sense of what it means for the organization within the present context and strategic needs. Sensemaking for DE helps guide decision-making and strategy.
  • Complexity and Systems Thinking. A distinguishing feature of DE is the use of applied thinking from systems science and complexity to guide the entire process. This means creating designs and processes that are sensitive to detecting emergent properties, network effects, organizational behaviour (like self-organization), and non-linear or algorithmic change dynamics.
  • Dynamism. Complexity also requires that an evaluation be designed with consideration of the dynamics of the program, actors, and system. This means adapting or developing from a moving position, not a static position. It also involves designing evaluations that take into account the growth pattern and evolution of a program that suits the system. It’s about a design for changing conditions.
  • Visualization. System complexity is made more so by the inability to effectively ‘see’ the systems in our heads – there’s too much information. The ability to create system maps, visualize the dynamics and relationships within it, and facilitate discussion of those systems is critical to understanding where a program fits within it all. Visualization can be sophisticated or relatively simple in nature.
  • Design. What makes DE distinct is that it is about making modifications to the program as it unfolds using evaluation data to guide the strategy. These modifications require design and the skills — like with evaluation — require designing a program while it is moving. These developmental design skills are often overlooked and bring together service design and innovation with elements of systemic design.

Toolset

The toolset is the least specific of the three ‘sets’ for DE. Almost any method can support a DE, although unlike other approaches, rarely will there be a case where a single method — interview, survey, observation — will work on its own. A multi-method or mixed-method approach to data collection is almost always necessary.

Some additional tools or methods that are not common are ones we’ve advocated for and either developed ourselves or borrowed from other contexts. Three of the most important of these are:

  • The Living History Method. This meta-method brings together artifacts that inform the program’s early development and evolution. It recognizes that the present program is shaped by where it came from and that such a history can influence where things are going. Unless these conscious or unconscious patterns are recognized it is unlikely they will change. This method also helps record decisions and activities that often get missed when creating an innovation.
  • Dashboards. The wealth of potential information generated from a DE and available at our fingertips can overwhelm even the most skilled evaluator. Creating dashboards using simple tools and technologies can help organize the various streams of data. It also can allow someone to gain a sense of where there may be simple patterns laying within a complex layer of data.
  • Spidergrams. The spider diagram is a simple visualization tool that can work well in a DE as it helps pull various data points together in a way that allows comparison between them AND the ability to dive deep within each data stream.

Some additional perspectives on doing DE can be found in the guide (PDF) published by the McConnell Foundation by Elizabeth Dozois and colleagues.

Next time you are considering a DE, look at your present inventory of mindsets, skillsets, and toolsets to see if you have the right resources in place to do the work you need to do.

Need help? Contact us. We can help you set up a Developmental Evaluation, do one, or both. We’d love to hear from you.

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Innovation: Why Starting Points Matter

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If you’re looking to measure some form of progress or impact connected to your innovation (a product, service, or policy) then paying attention to the starting point is critical.

Evaluators call this a baseline and it’s maybe the most important line you can draw. A baseline is really the point of comparison for all you do. When speaking about improvements or change, this is the point you refer to when making those claims.

For something so important, it’s remarkable how few organizations capture baselines well. Let’s look at what it means and how you can do a better job of determining your innovation’s baseline.

Setting a baseline

An ideal baseline is set as far back from the present as possible at the start of your innovation journey. However, as many journeys have starts, stops, and tangents it might be that the start of the innovation journey actually ‘begins’ mid-way through a timeline.

If you are already started your innovation journey, the best time to set a baseline is now. It’s possible in some cases to use retrospective data (looking backward) to assess a baseline, however that can be fraught with certain biases that are unhelpful. If looking retrospectively, consider neutral data points like dates and times, concrete descriptions of product work, and use verifiable sources of data (e.g., work activities, prototypes, expenditures) to support that work.

When setting a baseline, there are some other tips we advise to enable you to capture the most possible useful data you can. If you are innovating in a human system, it’s possible that the innovation may have many effects that go beyond the most obvious so collecting the right data to capture these effects at the beginning is key.

  • List out the resources that have been assembled to develop the innovation such as people, space, and other capital (e.g. funds). These are your starting inputs into the project.
  • Gather a project plan or schedule of activities early to help determine what happens after the project begins. This will help determine where deviations from the plan take place, when, and help you trace back what happens if or when those changes take place to the strategy. Capturing deviations is critical because it helps you go back to see what adaptations you make at the end. Without this data, these activities might appear to be random or haphazard.
  • Capture cultural/environmental factors. Using the STEEP-V (Social, Technological, Economic, Environmental, Political, and Values) model is helpful in knowing what to pay attention to. One of our clients experienced a major, unexpected removal of funding due to rapidly changing political priorities of a government that was supporting their work. By capturing these broader situational variables you can place your innovation work in a context.
  • Document the state of your organization’s readiness and preparedness, which may also include an assessment of innovation readiness. Many innovations fail not out in the market, but within the design studio. Changes to organizational priorities, resources, and personnel can scupper, delay, or change the plans for an innovation. Capturing the state of the organization is an important point as it will allow you to see where things go off track or where they are enabled because of the organization.
  • Develop a project charter and theory of change. While a project may change direction many times, a baseline assessment can help you reflect the desired outcomes and original purpose of the innovation — which are quite likely to change over time. Having this in place can help explain what changes take place and what adaptations take place.

Baselines are the key point for making any claims of change, improvement, or transformation. They are the point where we say “in relation to what?” when speaking about change.

Give yourself some time and use the baseline assessment as a chance to spur reflective and strategic planning about your innovation. You will be grateful you did and amazed at the results later on.

If you’re interested in learning more about baseline development and its role in supporting innovation evaluation, contact us and we’ll gladly help.

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Chief Learning Officer

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C-suite leadership roles focus on an organization’s most important functions. Time to introduce the role of the Chief Learning Officer.

Learning — easier said than done. Yet, learning is vital to the success of an organization that seeks to innovate to gain advantage or merely survive – which is most human service organizations these days.

Learning opportunities abound, yet these require energy and attention in order to take advantage of them. Organizationally, this requires leadership and resources to support people across the organization to learn within their areas of focus and across the institution and networks.

Everyone is responsible for learning and there are some great resources to support that effort, but without someone taking explicit leadership on making sure learning happens within the institution, it’s less likely to happen — at least happen in a way that is designed for innovation.

Introducing: the Chief Learning Officer.

Leading Learning

With the alphabet soup of C-s that we are seeing among organizations’ leadership teams adding another might not seem helpful. What we propose is less about formalizing the title of CLO and more about creating the function of what they can do within an organization.

We envision a CLO role as one that does the following:

  • Establishing a learning plan for the organization and the data structure to support that learning. This means instilling and building a culture of evaluation across the organization, which provides data and feedback on what is happening to allow staff at all levels to learn from what is being done. It involves showing what evaluation can do and co-creating ways to do it across the enterprise to add learning value.
  • Ensures that staff roles and functions include the ability to study and reflect on the work being done and its impact. This means establishing practices and procedures that link evaluation data to program activities. It also involves creating the means to bring in insights from outside sources (e.g., published research and reports, networks, professional communities, customers and clients). Structuring what we do and how and when we do it is part of this function to ensure that roles and learning needs are fit-for-purpose.
  • Organizing the evaluation of program activities and ensuring that staff at all relevant levels of the organization close to each program have access to the information about those programs and can make decisions about those programs without having to go through cumbersome layers of bureaucracy.
  • Create sensemaking channels and opportunities throughout the organization. This allows intra- and cross-departmental/unit collaboration to understand the bigger picture of what’s going on in the organization and industry.
  • Supports the development of self-sustaining communities of practice or learning groups on topics relevant to the organization, yet without specific roles or functions. Topics might include emerging technologies, leadership, creative thinking, or professional development.

Creating your CLO Office

A CLO would link the activities of the organization to the monitoring and evaluation data about those activities with the literature and trend data from outside the organization into a culture of learning within the organization.

This could be a full- or part-time position or something like a fractional CLO role like we can play at Cense.

Whether you create a CLO within your organization or choose to recruit learning support from outside, having a dedicated person shepherding your culture into a learning organization is something that will increase your innovation capacity exponentially.

For more information about how you can build this learning culture within your organization or the fractional CLO role, contact us. We’d love to help you out.