Taming your Assumptions Mammoth II

This post is a continuation of https://adityarsmishra.medium.com/taming-your-assumptions-mammoth-c6fe403d4d36

The Noise Factor in Product signals

Lets revisit our signal equation

Signal-Final= {M0*S0 + M1*S1 + M2*S2 …. }

Every signal inherently has a noise component which distorts and changes how these signals reach you. The efficacy of your actions achieving the outcomes are dependent on your evaluation and reduction of noise in the incoming signals.

Remember signal processing?

Unfortunately, the input signal to a transmission line is seldom identical to the output signal. If you understand how the transmission line (the system) is changing the signal, maybe you can compensate for its effect. In terms of system theory, the problem is to find the system that changes the transmitted signal into the received signal. Source — Linear Systems

To help understand noise distortion, our original signal equation now changes to:

Signal-Final= {M0*(S0+N0) + M1*(S1+N1) + M2*(S2+N2) …. }

The noisier your signals, the riskier your assumptions.

Here are a few common sources of Noise

• Overfitting and Availability: Noise in customer signals introduced from listening only to specific customer audiences while ignoring others. For example, hearing from your most active users and not actively pursuing the customers who have churned or dormant. Another flavor of this is availability bias i.e. magnifying signals that are easier to access. A common one is PMs who over-rely on customer support tickets. Note, in many cases overfitting is helpful for example when you are creating a version 0 product for your early adopters.
• Misreading: Perhaps the most common and undetected source of customer noise. Is often introduced by non-perfect listening and stems from a poor understanding of UX research. Manifests through wrong/misleading customer interviews, interpreting feedback incorrectly. There’s a whole universe of biases that creep in UX (confirmation bias being the big one)
• Goal-driven distortion: Watch out for Signals from other teams that could be distorted by impending goals or individual success metrics. A very common one is the “too-early gotcha” by sales teams. In an effort to get that next big client through the door, product teams are often asked to build solutions that scratch only surface level problems. PMs need to dedicate enough time and energy to understand deeper pain points before jumping onto a signal and related execution.
• Assumption magnification : Perhaps the most fatal one that sinks teams and companies are unidentified feedback loops in ecosystems. This deserves a much deeper treatment but in short, watch out for channels of communication between all signal sources. This cross talk ends up magnifying the same signal over and over again, leading to abnormally inflated multipliers. More to come on this soon.

Feedback Loops magnify certain signals and can lead to riskier assumptions