Solving Complex Problems Scientifically

Standpoint takes an evidence-based approach to addressing issues for a regulator. We start with a central question or hypothesis that articulates a problem prioritized by the organization. Often these problems are creating a risk or a cost to the public or to the regulator, and may already have a task force or committee assigned to them. More often than not, the available information and data involves complex interactions and uncertainties, which can make objective analysis by a task force or team challenging.

We follow a scientific yet easy to understand process which provides working teams a clear path and well defined outcomes. How teams decide is often more important than what they decide. Better understanding of a decision process helps build stronger stakeholder consensus and implementation support for the outcomes, even when those outcomes are hard.

Starting with outcomes based questions ensures the work that follows has a solid foundation and will lead to answers you can use.

Questions to consider:

  • What are the leading causes of complaints, and what drives them?
  • Can program “x” be linked to quantifiable evidence of improvement of our key regulatory performance indicators?
  • Do we know where the major friction points in our intake process lie? Do we understand the impact they have on our key regulatory performance indicators?

There are many potential sources of data that could be used to answer the questions. A big challenge is often assessing what data isn’t required, and avoiding distraction by the many irrelevant data sources competing for your attention. A significant value delivered by Standpoint is the simplification and decluttering of the data landscape.

If data could be likened to food, then analysis is the myriad ways you can slice, dice and prepare it for consumption.

Understanding the audience, the right insights to be teased out of the data, and which analysis tools are most appropriate (and how to use them) is an art as much as it is a science.

The Standpoint team has rigorous scientific skills and expertise, and years of practical experience in the kitchen.

Charts and reports of data analysis can be delivered by many service providers, but that’s not enough. You need analytical interpretation in the unique context of the legal regulatory environment, which, quite frankly, not many outside of it understand. For example, how should the results be framed in context of the programs you’re delivering (or are planning on delivering), and the ultimate mandate of the regulator, protection of the public?

The ultimate purpose of collecting and analyzing all this data is to inform decision-making. But how do you best do that? Many teams faced with a table full of analysis and a room full of expertise often give up and resort to intuition and heuristics, which rarely leads to the best outcomes.

What’s often more important than what you decide, is how you decide. Standpoint has a variety of structured decision-making tools and processes available, and understands how to effectively facilitate their use with teams of executives, committees, and task forces.

Many good decisions and/or policy changes fail to close the loop. Gauging performance of the actions or implemented programs against initial expectations allows for adaptation and continuous improvement based on hard evidence, and builds stakeholder support and resource allocations and future funding of important projects.

Model Where You Are, and Where You Want To Be.

We begin by formalizing the goals and objectives of the task force and then develop a conceptual model of the system that is influencing the likelihood of the desired outcomes.

Standpoint guides this model development, but the approach is consensus-driven. This gets everyone on the same page, and improves support when it comes time for implementation.

The modeling process probes the following questions:

Define success – How can we measure our desired outcomes so that we know when they have been achieved?
Available alternatives – What proposed decisions, actions or policies are within-scope to address the problem?
Data and expertise – What data and/or expert opinion can we use to forecast the implications of different decisions or policies?
The unknown – What is driving uncertainty and how can it be addressed or accommodated?

Analyze the Data and Predict the Future

Next, we use a scientific approach to formalize the causal model to analyze and measure the benefits of past management actions and/or to forecast the probable outcomes of future actions.

This approach then generates recommendations to the task force that are focused on important things such as:

  • optimizing the resources of the organization and membership,
  • reducing risk to the public, and,
  • fostering continuous improvement through adaptive management