Let's revisit a core theme: the art and science of research, and how we translate it into tangible results. Today, we're focusing on a critical distinction that separates impactful research from reports that gather dust: declarative knowledge versus procedural knowledge.

Declarative Knowledge: This is the "knowing what." It's the theory, the facts, the frameworks. Think: "Market segmentation is..." or "Regression analysis is used to..." It's the stuff you learn in textbooks, read in journals, and discuss in strategy meetings.

Procedural Knowledge: This is the "knowing how." It's the application, the execution, the doing. It's the ability to use those frameworks, to analyze that data, to implement that strategy, and to navigate all the complexities of the real world. Think: "How to conduct a customer survey" or "How to build a predictive model" or "How to actually get stakeholder buy-in for your research findings."

The Research Paradox in Business (the Academia/Bootcamp Blind Spot):

In the years leading up to 2020 and COVID times of 2020-2022, businesses were investing heavily in research, eager to hire brilliant minds with impressive credentials and a vast arsenal of declarative knowledge. These researchers, skilled in commissioning reports, conducting market analyses, and generating mountains of data, were expected to drive impactful research. However, the "Death of UX" and the subsequent wave of major layoffs in 2022 served as a critical tipping point. The focus on the theoretical "knowing what" often leaves these researchers struggling to translate their knowledge into impactful action. Consequently, deliverables and reports lacked real-world impact, insights were shelved, recommendations were disregarded, and the business continued to operate with the same old approach. This disconnect exposed a fundamental flaw in the research paradigm, a "blind spot" where the value of academic rigor failed to translate into actionable business outcomes.

Why This Disconnect?

Often, it stems from an over-reliance on declarative knowledge. Some academic researchers and even research bootcamps, while valuable, can inadvertently prioritize theoretical understanding over practical application. This creates a gap that becomes painfully obvious when researchers transition to the business or industry side.

Academia's Focus:

The academic world often rewards deep theoretical understanding, methodological rigor, and the ability to contribute to the existing body of knowledge. Researchers are trained to meticulously design studies, analyze data with precision, and publish their findings, adding to the expanding literature. However, the emphasis is often on proving a hypothesis, not necessarily on solving a user or business problem.

Example: A PhD researcher can excel at conducting rigorous experiments and generating statistically significant findings, often producing comprehensive reports. However, when addressing complex business challenges like improving customer retention, translating those findings into actionable recommendations can be difficult. They may struggle to consider factors beyond the immediate data, such as the competitive landscape or internal company constraints, and to communicate their findings to non-expert stakeholders.

For instance, a survey might reveal that customers highly value personalized product recommendations. The research might conclude that implementing a sophisticated AI-driven recommendation engine would significantly improve sales. However, this seemingly straightforward recommendation could be impractical. The company might lack the technical infrastructure to support such an engine, the necessary data to train it effectively, or the budget to invest in its development. The recommendation, though statistically sound, becomes not actionable due to a lack of business context and implementation feasibility.

Bootcamp's Emphasis:

Bootcamps provide some training in technical skills like research coding and data analysis. However, they often lack sufficient depth or hands-on experience. Designed as crash courses, and a certificate to help get a foot into the industry, many graduates leave without the practical experience, comprehensive credentials, or broad declarative knowledge needed to understand when, why, or how to effectively utilize various methodologies. Some bootcamps are even biased towards specific platforms or methodologies, failing to provide a well-rounded curriculum within a limited timeframe. This can leave graduates unprepared for the complexities of real-world research industry challenges.

Example: For instance, a bootcamp graduate might be proficient in using a specific A/B testing tool/platform. They could quickly set up and run tests, generating statistically significant results about website design changes. However, they may struggle to design a truly effective test, lacking the understanding of user behavior, experimental design principles, or the ability to interpret the results in the context of the overall user experience. They might not be able to identify confounding variables, communicate the limitations of their tests to stakeholders, or collaborate with designers and product managers to implement the findings in a way that improves the overall user journey. The bootcamp graduate can run the tool, but their lack of broader understanding can limit the impact of their work.

In both cases, the transition to industry can be jarring. Researchers who are accustomed to focusing on theory, publication, technical correctness, and specific platforms may struggle to adapt to the fast-paced, results-oriented environment of a business. They may find it difficult to prioritize, to communicate their findings effectively, and to translate their insights into actionable strategies.

To make matters worse, the research world is constantly evolving. To truly drive impact, researchers need more than just a solid foundation of knowledge. They need to be creative, able to think outside the box and develop novel approaches to complex problems. They need to be adaptable, able to adjust their methods and strategies as new information emerges and unexpected challenges arise. And they need to be flexible, willing to embrace new technologies and learn new skills throughout their careers.

Procedural Knowledge: The Engine of Impact & Accelerant's Approach

This is where procedural knowledge becomes the secret weapon. It’s not just about running the analysis; it’s about the following:

Selecting the right methodology: Choosing the most appropriate research approach for weighing the User and Business problems. This involves understanding the strengths and limitations of different methods (qualitative, quantitative, mixed methods, etc.) and how they align with the business's goals within your company.

Data Wrangling & Interpretation: Knowing how to collect, clean, and analyze data effectively. This includes understanding data sources, identifying biases, and drawing valid conclusions.

Communication & Storytelling: Presenting findings in a clear, concise, and compelling manner. This means tailoring the message to the audience, using data visualization effectively, and crafting a narrative that resonates with stakeholders. This is often a skill that's lacking and can be a major differentiator.

Implementation & Change Management: Developing actionable recommendations and helping the business implement them. This requires understanding the business context, identifying potential barriers to change, and working collaboratively with stakeholders to overcome those barriers.

At Accelerant Research, we've built our model to address this critical need, and combat the issues I've described:

Teaching Hospital Model for Jr. Staff: We immerse our junior researchers in a "teaching hospital" environment. They work closely with senior staff on real-world projects, gaining hands-on experience, repetition and learning from the ground up. The diversity of our clients, varying methodologies, and emphasis on triangulating multiple data sources and complex mixed method research programs provide our Jr. staff with opportunities and an environment to "fail forward". This allows them to develop strong procedural knowledge and build confidence in their abilities.

Strategic Senior and Leadership Hiring: We intentionally recruit senior leaders and researchers with exceptional storytelling and critical thinking skills, emphasizing mastery of craft essential at the leadership level while acknowledging the ever-evolving landscape of knowledge. This intentional approach to staffing senior roles typically requires individuals with both agency and in-house experience. This allows us to deeply understand our clients' and our own internal landscapes, and effectively translate those insights for our project teams, a quality reflected in our work. These individuals provide mentorship and ensure our deliverables are technically sound, insightful, impactful, and effectively communicated.

Real-World Impact: The Power of the "How"

Let's look at some examples:

Customer Journey Mapping: A researcher with strong declarative knowledge might understand the theory of customer journey mapping, including frameworks and methodologies. They might know the importance of identifying touchpoints and pain points. But a researcher with strong procedural knowledge can actually conduct interviews with customers, analyze qualitative and quantitative customer data, identify key pain points in the customer journey, and generate recommendations to design a new customer experience—including content, messaging, and process improvements—that leads to increased satisfaction and loyalty. They not only understand the concept but can execute the process from start to finish.

A/B Testing: Knowing the principles of A/B testing, including statistical significance and experimental design, is one thing. But a researcher with strong procedural knowledge can design experiments, considering user behavior and business goals. They can analyze the results, accounting for potential biases and confounding variables, and translate those results into concrete changes on a website or in a marketing campaign that drives conversion rates. This includes understanding how to implement the changes, track their impact, and iterate on the design.

Predictive Analytics: Understanding the math behind predictive models is important, but a researcher with procedural knowledge can build a model that accurately forecasts sales, identifies at-risk customers, or optimizes pricing strategies, leading to improved profitability. This includes not only selecting the right algorithms but also cleaning and preparing data, validating the model's performance, and communicating the results to stakeholders in a way that informs business decisions.

The Bottom Line:

In the business world, research is only valuable if it leads to action (action take or avoided). And action requires procedural knowledge. It requires the ability to not just understand the problem, but to solve it. It requires creativity, adaptability and flexibility to drive impact. It's the difference between generating a report and driving real, measurable change. At Accelerant, we’re committed to fostering this holistic approach, equipping our clients & team to transform insights into impactful outcomes.

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