Common Biases and Fallacies in Capture Decisions and Black Hat Reviews

Not too long ago, we wrote a blog looking at common traps we see during events such as Black Hat reviews. Taking a different spin on what we frequently see in these sessions, we look at cognitive biases and logical fallacies that often derail Black Hat teams or any capture team.

Allowing these biases and fallacies to affect our analysis of a situation – such as competitors during a Black Hat review – compromises the effectiveness of analysis and follow-on decision making.  Defaulting to the ‘easy button’ in regards to how we think about competitors (which is how many of the tendencies function) shelters us from the threat they pose, without decreasing their actual competitive threat.

Consider some of the common biases and logical fallacies we encounter in events such as Black hat reviews and capture planning. Editor’s note: We use the generic “ACME Corporation” in order to protect the innocent. It’s also a tribute to Wile E. Coyote who embodies the follies of such flawed thinking. Be wary of falling anvils. 

Cognitive Biases, Logical Fallacies, and Black Hat Examples

Ad Hominem is a logical fallacy where we attack an opponent’s character or personal traits in an attempt to undermine their argument. By casting our opponent in a negative or suspicious light, we can avoid engaging in the actual argument itself.

Black Hat Example: “They might have all the right resources and experience, but their capture team is a bunch of arrogant jerks. It’s their way or the highway, they won’t try to tailor their solutions for this customer.” We can’t assume they are arrogant or inflexible or that they’re taking this opportunity lightly, especially if they have the resources and capabilities to win.

Affect Heuristic allows us to make decisions according to our “gut feelings.” While this can be beneficial in terms of survivability, it hinders logical decision making and evaluation by bringing emotional responses into play.

Black Hat Example: “ACME Corporation is going to be way too expensive.” Maybe they used to be, but they have proven their ability to be very competitively priced when they want. Reducing a decision to our immediate judgement and feelings often eliminates relevant evidence from the decision-making process – preventing us from seeing the full competitive threat.

Anecdotes or Appeals to Emotion rely on our personal experience or specific examples instead of valid arguments. A good salesman can sway an audience strongly to one viewpoint, even when the opposite is equally valid or even more relevant.

Black Hat Example: “This competitor was incredibly successful at FEMA due to their transition, management, and expert personnel. They can do the same for this customer” – a well-told story from an emotional, first-hand account, vs. “This competitor was faced a lot of issues previously for this customer” – a less well-sold, emotionally-charged example. Guess which anecdote was given more weight? 

Availability Heuristic or Recency Bias is a mental default that offers immediate examples, the first thing that comes to mind, when evaluating a competitor. We tend to overemphasize recent information when making decisions instead of evaluating a body of knowledge as a whole. This is the opposite of Conservatism Bias, noted below.

Black Hat Example: “We didn’t know ACME Corporation had those capabilities; they’re definitely the highest threat now.” While that may be true, new capabilities and strategies were presented on General Dynamics which caused the participants to view them as a higher threat than the more familiar and well-understood (but equally high-threat) competitors.

Confirmation Bias is our tendency to look for information that confirms our pre-existing beliefs, decreasing our objectivity. If we would like an idea to be true, we end up believing it to be true, led on by wishful thinking.

Black Hat Example: “This customer really wants model-based systems engineering.” This may be true, but are you just saying that because your company is strong in MBSE? Or, “That competitor would be better as a subcontractor, they won’t really pursue this.” Again, this may be true, but we need to ensure that we are not just looking for ways to discount their threat.

Conservatism Bias is our tendency to rely more heavily on previous information and discount new evidence or information. In the ever-changing government contracting space, this can severely hinder how we view the competitive landscape. This bias is the inverse of the previously mentioned Availability Heuristic or Recency Bias.

Black Hat Example: “Why are we worried about ACME Corporation bidding on this contract? Aren’t they the just the company that provided water and logistics in Iraq?” This participant’s inability to recognize that ACME Corporation is a fundamentally different company than they were in the early 2000s would have caused them to completely discount ACME Corporation’s competitive threat.

Halo Effect is a bias that impacts our overall impression of someone or something, frequently character-based. We might believe that if someone is a good person, they are likely smart as well. Or if someone is talented in one area, they will be talented in other areas.

Black Hat Example: “ACME Corporation is a major systems integration and strong in development and IT support, therefore they’re a sure bet for this cybersecurity work.” Not necessarily – ACME Corporation may not have as prominent a cybersecurity practice in most customer domains, but they have a significant role doing cybersecurity support in classified environments.  Companies can be vastly different in various domains.

Overconfidence Bias occurs when we place too much value on our own knowledge or fail to see the limits of our knowledge. We therefore perceive strategies or decisions based on our knowledge as less risky.

Black Hat Example: “Section M says the key personnel only need a Bachelor degree, but we know that only advanced degrees can really do this work, so that’s who we’re bidding.” Guess who “lost on price”?

Projection Bias or Mirror Imaging is our tendency to overestimate how much other people agree with us. We tend to assume that other people will think, believe, and behave in the same manner that we would.

Black Hat Example: “Well I would propose significant innovations in the following five areas…” Assuming that the competitor will act the same way the participant would is rarely true. Different competitors frequently operate in fundamentally different manners with a variety of resources; in Black Hatting against them, participants should shed their standard point of view and assume the mantle of their competitive team.

Semantics or Equivocation is when we attack the ambiguity or inaccuracy of specific words to distract from the actual ideas or issues presented in the argument. This can also present itself when we deliberately rephrase the argument (often by misrepresenting a term that can have various meanings) then attacking the rephrased argument instead of the original argument.

Black Hat Example: “The competitor can use their proprietary tools to provide better transparency into program management.” This statement was immediately countered with “this customer absolutely won’t stand for proprietary solutions!” The Black Hat team used ‘proprietary’ to show that the competitor had invested in these tools and would not be developing them on the customer’s dime. While other terms could have communicated the same idea, participants focused on the nature of the term ‘proprietary’ instead of the overall concept of using their tools to address the customer’s issues.

Recognizing a Problem is the First Step Towards Correcting It

These are by no means the only cognitive biases and logical fallacies at play in Black Hat reviews, but are those that we see repeatedly. While no one can completely eliminate biases from their thought processes, awareness of how biases may impact a Black Hat review or capture effort is the first step toward reducing their negative effects.

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