The EVIDENCE Model
The EVIDENCE Model provides a methodical approach to defining a problem and ensuring the solution is targeted specifically to mitigating the identified problem. The framework has eight stages grouped into three core principles. The first principle, critical thinking, includes three stages: Explore Challenges, Validate Problem, and Identify Outcomes. The second principle, creativity and innovation, includes two stages: Data Collection and Experiment and Prototype. The third principle, precision of language, includes the final three stages: Narrate Story, Compile Feedback, and Evaluate Results.
Explore Challenges
Generally speaking, people have an inherent desire to help others. But the desire to help others often leads too quickly into ideas to solve a problem. The first step of the EVIDENCE model is to Explore Challenges. This early stage is critical to the successful utilization of the problem and is likely to be the stage where most of your time and effort will be spent.
The problem is rarely self-evident. What is more common, and often confused as the problem, is the symptoms of the problem are apparent. It is the symptoms of the problem that people and organizations target for improvement instead of targeting the problem itself. Doing this will consistently result in failed attempts for improvement resulting in wasted time and money and, perhaps more importantly, contribute to disengagement amongst stakeholders because the underlying problem is not being addressed.
It can be challenging to know when you have identified the problem or uncovered another symptom. It is entirely possible that even after you think you have identified the problem, you may realize through this framework that what you thought was the problem is little more than another symptom. When that happens, circle back to this stage with the information you gathered and re-evaluate whether your starting point was a problem or a symptom.
Validate Problem
Now that you spent time exploring challenges and worked to ensure the problem identified is not merely a symptom of a more significant problem, you need to validate the problem exists. To begin, you must be cognizant that your perception, the lens through which you explore challenges, can alter your reality. We are all prone to believing in the existence of a problem that does not exist or believing the problem is more significant than reality. To put it simply, we either see something that is not there, or we make a mountain out of a molehill. Knowing the power of our own biases is the first step in recognizing our fallibility.
To combat the limitations of your perceptions and reduce the effect of personal biases, you must surround yourself with a diverse group of trusted advisors. Diversity is not just about representation across gender and ethnicity, but also across education and experience. Your advisors should come from varied backgrounds, both professionally and personally, and feel empowered to challenge your ideas, your beliefs, and your assertions. You need to make sure those who surround you not only support you but have the vision to see your blind spots. The group you organize will be imperative as you validate the existence and scale of the problem you wish to conquer.
In addition to surrounding yourself with a diverse group of advisors, you must also gather information to validate the problem. Information sources that may be beneficial to analyze the problem include previous attempts to solve the problem or a related problem. Reflecting on previous challenges and past accomplishments can offer insight into the validity of the problem and a course of action later when identifying outcomes. Institutional knowledge from members of the organization with experience can be a great asset as much as insight from new members of the organization who are unfamiliar with historical problem-solving efforts.
Validating the problem is not done in isolation. It requires input from others who should provide you a different vantage point of the problem. As you work to validate the problem, keep in mind that you may need to revisit the previous step, and explore additional challenges or consider the identified challenge in another way. Failing to validate the problem successfully will result may result in unnecessary or unforeseen consequences. For this reason, validating the problem is one of the most critical steps in the EVIDENCE model.
Identify Outcomes
It seems like an obvious necessity to clearly define outcomes as part of your problem-solving process, but far too often, the desired outcome is ill-defined if it is defined at all. Generic outcomes like “we must be quicker to market” or “we need to increase sales” do little to identify the outcome accurately. These forms of generic outcomes result in a vague or moveable target that makes it difficult, if not impossible, to measure the success of a new or altered process or product.
One way to accurately and precisely identify outcomes is to align your outcome with outcomes defined at a higher level. Suppose an executive has set a target to reduce costs by ten percent over the next year. If you set a target to increase sales by twenty percent, you are not aligned to the executive’s target and may hinder his or her goal. In contrast, if you set a target to reduce your printing costs by thirty percent, you are establishing a goal that contributes to the higher goal, and your targets are aligned.
Your positionality in the organization may require you to look up and down to align outcomes. Just like you must make sure your outcomes align with the higher organization, you must also ensure that outcomes derived by subordinates align with your targets and outcomes. You may need to define outcomes that support the stated outcomes from your superiors while also providing a goal by which your reporting organizations can also align.
In either case, whether aligning your outcomes up or down, outcomes must be quantifiable. Having a measurable outcome will ensure that all stakeholders can access if the actions taken were successful or not. Instead of saying, “we need to be faster to market” consider, “we will reduce time to market by ten percent.” Instead of saying, “we need to increase sales” consider, “we will increase sales by twenty-five percent.” It may also be necessary to establish a more direct target like “we will reduce time to market by six months” or “we will increase sales to $1 million.”
Whether you choose to utilize percent-based or numbers-based outcomes, quantifiable measures essential for success as compared to generic forms of outcomes, remember that quantifiable measures are more simple to communicate, reduce confusion, and provide a clear target for success. Quantifiable measures are also easier to evaluate whether they contribute to any objectives established higher in the organization while also providing seamless alignment downstream with which subordinate offices can and should align.
Data Collection
Data, the fundamental requirement of an evidence-based decision-making process, is often an afterthought. Too often, organizational leaders are not well versed in the capabilities of their organization to collect, synthesize, and analyze data. Many consider the people in an organization who perform these duties wizards who perform magic to get the data. The methods used are not known and thus perceived as pressing the “easy” button to make the magic happen.
To begin the data collection phase, one must first identify data sources applicable to the challenge. This can be difficult in an organization that does not catalog and inventory their data assets. Maybe you have a few databases. Perhaps you have a bunch of spreadsheets. In either case, knowing what data you have and, more importantly, what data you do not have is imperative to ensuring the necessary data is used to solve any challenge.
Once you determine the data assets available, you must aggregate the data into shareable systems that make access to the information seamless. Data stored in separate files in disparate systems is of little to no use to you. It is essential to strive for automated processes that aggregate the data into systems that allow easy indexing of resources and facilitate the use of all available data. Doing so will dramatically reduce laborious, manual work that wastes time and reduces the accuracy of the data.
After you identify data assets and organize the data into easily accessible systems, you must ensure that stakeholders are included to review the data and provide context. This critical review process from subject matter experts is vital to make sure that the data is accurate and properly used in analytical methods. Otherwise, the resulting analysis will result in incorrect information that can negatively affect your ability to solve problems correctly.
The data collection stage is more than just quickly pulling information together to solve the problem at hand. Considering many problems will take time to resolve and thus require updated information, it is necessary to develop data collection systems that automate the collection of information to ensure timely and accurate access. Creating systems that streamline the distribution and sharing of data with requisite stakeholders will also ensure the data is verified and provided context to support the analysis.
Experiment and Prototype
The experiment and prototype phase is my favorite amongst all the phases of the EVIDENCE Model for one reason – I like building things. There is instant gratification that comes from quickly building a solution and getting feedback. The ability to quickly devise a solution is much more difficult, if not impossible if there is a rigid plan. I am not saying that planning is unnecessary or that a plan is not required. What I am saying is you should not feel beholden to a plan. In this phase, an idea and a general direction are better than scoping out a full project with a plan.
There is an expression in business you may have heard of: “fail fast, fail often.” Properly understood and correctly implemented, fail fast, fail often is meant to facilitate fast prototyping and early feedback to make adjustments. Indeed, the goal is not to fail dramatically. Still, a series of small failures and incorporating lessons learned have the potential to create quality solutions better than engaging in a full development project and waiting until the end to get the necessary feedback.
Another concept is, “think big, start small, and scale fast.” The rationale with this philosophy is to subscribe to an iterative or agile development cycle instead of the old school waterfall mentality. It is essential to know how a prototype will be operationalized. It is also vital to consider how the solution may need to be changed as it is scaled to a larger group of stakeholders. Envisioning a roadmap for the long-term potential of your solution will undoubtedly influence your prototype, but considering the future should not be undertaken at the expense of agility when experimenting and prototyping.
One last thing to remember during this stage – collaboration is not consensus. Diversity is important. Ensuring that stakeholders are represented is essential. But gathering a large group to develop a prototype is unnecessary to produce a quality product. Collaboration can be achieved with a small team that engages stakeholders when necessary to gather necessary input. The input received can be quickly incorporated to allow development to move forward. This input should not be confused with seeking stakeholder buy-in, which often requires consensus.
The goal of experimenting and prototyping is to create a solution quickly following an agile development process. Yes, the end solution needs to be developed in a sustainable manner, and stakeholders should be involved to ensure the solution is appropriate. But you should resist the urge to spend too much time planning what you want. Experience has demonstrated that people often cannot describe what they want but can critique something they tangible they can see, touch, and try.
Narrate Story
No doubt you have heard this phrase before, “a picture is worth a thousand words.” If that is truly the case, and I believe it is, why then are business presentations filled with bullet points littered with text ad nauseam? Graphics not only communicate more effectively than text, but research suggests our memories can remember images better than text. One study determined that people could remember more than 2,000 images with more than 90% accuracy even after several days from exposure. The challenge with incorporating graphics and images in presentations is selecting images that are applicable and add value. Additionally, as the narrator of the story, you need to find a balance between graphics or images and text to ensure the audience is not distracted and will receive the message accurately.
Story-telling is more than providing information. There are many factors involved in telling a good story. You should strive to create a message that is visceral and evokes emotion in the audience. Compelling stories are those in which the audience establishes a connection and can relate. Presentations, especially those in a business setting, must go beyond a recitation of facts and figures. The audience must appreciate the impact of the material and the consequences of action or inaction. In short, story-telling is a production, and the art of the show is just as important as the content delivered.
It is essential to understand the needs of the audience to narrate and share compelling stories. Some audiences have little time, and the story must be succinct and direct. Other audiences want to understand the impact of a decision both to the organization and to external stakeholders. Knowing your audience – the way they consume and process information – will ensure you craft an appropriate story that resonates with the audience. The worst thing you can do is develop the perfect story for the wrong audience. You must appreciate that the way your narrate and communicate your story can have an adverse reaction to those hearing your story and can result in the wrong outcome due to confusion or distraction.
Compile Feedback
Researchers have long known that feedback is an essential component in one's learning and development. Feedback allows us to learn quicker and more effectively when we can assess how we are doing and how we can improve. The use of feedback not only helps us perform better, but can also help the organization as a whole perform better. It is critical that you ensure feedback is purposefully targeted to maximize the effectiveness of feedback. Too often, feedback is sough with general questions such as "how did I do" or "what do you think?" These open-ended questions are likely to provide too broad a response that may not yield the valuable information you need to improve. When seeking feedback, make sure you incorporate methods and techniques that address specific areas that you aim to improve.
There are many ways to collect feedback: surveys, interviews, focus groups, and data analysis, to name a few. Each of these techniques offers unique benefits and challenges you must consider depending on the level of detail and resources available to collect and analyze the feedback. For instance, interviewing stakeholders can provide rich, valuable insight that may not be possible using other techniques. However, interviews are time-consuming to conduct, and analyzing the data will likely take the most amount of time. Surveys, on the other hand, are invaluable for collecting feedback from large groups and can be analyzed more easily compared to interviews. However, surveys are limited by the available responses. Before rushing to collect feedback, make sure you identify the parties that will provide feedback and define how the feedback will be incorporated to improve your outcome.
Effective feedback can promote learning when it is timely, personal, manageable, motivational, and is directly related to assessment criteria. Feedback must also be engaging to maximize its effectiveness. When possible, talk with those who provide you feedback. Ask additional questions. Discuss with your stakeholders how you interpreted their feedback. The goal of engaging with those who provide you feedback is to deepen your understanding of the information you received. You want to make sure you learned what stakeholders were trying to share with you accurately. Additionally, you may be able to glean additional nuggets of wisdom that were not initially provided. Remember, the point of engagement is not to argue or be defensive with others. You should not try to justify or defend your actions. You simply what to make sure you learn from what others are telling you and incorporate that knowledge in the future.
Evaluate Results
Congratulations. You've made it this far. You defined the problem, identified outcomes, gathered data, prototyped solutions, narrated your story, and gathered feedback. You're almost finished, or rather, you think you're almost finished. After all the work you've done, it's easy to understand why you believe evaluating the results is the last and, perhaps, the easiest phase to complete. If you think this, you're mistaken. Evaluating results is no less important than any previous step and requires no less effort either.
To begin evaluating your results, you first need to circle back to a previous stage – identify outcomes. It is important to juxtapose the results you attained with what you wanted to achieve. At a basic level, this can be relatively easy to assess if your identified outcomes were specific and measurable. In these cases, your success is binary – you either achieved (or surpassed) your goal or you didn't. If, however, your identified outcomes were broad and generic, it can be difficult, if not impossible, to accurately evaluate your results.
As you've journeyed through this process, one theme has persistent that is equally applicable now – socialize with a diverse audience. Sharing your results and how you interpret your evaluation will provide you additional benefits compared to evaluating your results in isolation. You need to discuss your results with stakeholders and seek their input about the journey and the destination. Sharing your results with others will also enhance buy-in with future endeavors because stakeholders will feel like they contributed to the process and witness the results of their effort. Excluding stakeholders from the results can alienate them and create animosity towards your intent, support, and motivation.
Finally, you must appreciate that the results you achieve are merely a snapshot in time. You cannot rest on your laurels by believing you are finished. Improving performance and changing organizational culture takes time and requires constant effort. It is imperative that you consistently scan your environment for new opportunities to seek improvements. Take the lessons you learned during this process and begin anew by exploring new challenges. You may have accomplished what you set out to do, but if you relax and believe this is as good as it gets, you're likely to find yourself facing more challenges, perhaps even more complex, then when you first started.