Applications & Use Cases · Study deck
IoT History: SHIFT and Resistance
A pump operator hears a proposal for another sensor and asks why the existing maintenance schedule is not enough.
Blueprint Bina is your guide for this deck.
After studying this chapter
Learning objectives
You will be able to:
- Explain: Scenario:: Your manufacturing company's VP dismisses a proposal to add IoT sensors to industrial pumps, saying "Our customers have never asked for this." You recognize this as paradigm blindness.
- Explain: GPS tracking enables usage-based pricing ($8K/year per unit revenue vs. $3K/year flat rental), predictive maintenance (40% reduction in breakdowns), and theft recovery ($500K/year losses prevented).
- Explain: Our customer survey shows 67% would pay for predictive capability -- they're not asking for 'sensors,' they're asking for 'no more surprise failures.'.
- Apply the SHIFT proposal framework to an IoT change.
Major section
Turn the Pump Objection into a Falsifiable Trial
The proposal aims to reduce that total to 30 hours in an equally long trial with comparable operating load.
- The predicted reduction is 40 hours minus 30 hours = 10 hours.
- Relative to the baseline, 10 divided by 40 gives 25%.
- The second-order effect might be better spare-parts planning.
Major section
Turn the Pump Objection into a Falsifiable Trial (continued)
If an early warning lets maintenance order a seal before a shutdown, the useful outcome reaches beyond the first alarm.
- Human behaviour can also change: technicians may inspect an asset only when a warning arrives.
- That shift can help, but missed warnings now matter more.
- Forecast anchoring appears when the team assumes customers will always buy pumps in the same way.
- The opposite error is to assume every customer wants a subscription.
Major section
Turn the Pump Objection into a Falsifiable Trial (continued)
A small site with spare capacity may value fewer visits more than a tiny increase in uptime.
- The raw total meets the target, yet it does not show that failure exposure improved.
- Include those stops when assessing the operational outcome, even if the original proposal mentioned only unplanned losses.
- The trial should test a response, not just count warnings.
- A useful SHIFT proposal names who can act when the new signal arrives.
Major section
SHIFT Proposal Framework
Scenario:: Your manufacturing company's VP dismisses a proposal to add IoT sensors to industrial pumps, saying "Our customers have never asked for this." You recognize this as paradigm blindness.
- "We should add IoT vibration and temperature sensors to our pumps, enabling cloud analytics and predictive maintenance alerts.".
Major section
SHIFT Proposal Framework (continued)
Market Risk:: If we don't do this, someone else will.
- Our customer survey shows 67% would pay for predictive capability -- they're not asking for 'sensors,' they're asking for 'no more surprise failures.'.
- Tesla didn't wait for customers to ask for OTA updates -- they defined the category.".
- Key Lesson:: Paradigm blindness is defeated by reframing around new outcomes (not new technology) and competitive threats (not customer requests).
Major section
Detect Paradigm Blindness
GPS tracking enables usage-based pricing ($8K/year per unit revenue vs. $3K/year flat rental), predictive maintenance (40% reduction in breakdowns), and theft recovery ($500K/year losses prevented).
- Leadership Objection: "Equipment theft is rare.
- Reframed Proposal: "15-20% of our $50M fleet sits idle while customers request equipment we can't fulfill.
Deck summary
Key takeaways
The proposal aims to reduce that total to 30 hours in an equally long trial with comparable operating load.
- If an early warning lets maintenance order a seal before a shutdown, the useful outcome reaches beyond the first alarm.
- A small site with spare capacity may value fewer visits more than a tiny increase in uptime.
- Scenario:: Your manufacturing company's VP dismisses a proposal to add IoT sensors to industrial pumps, saying "Our customers have never asked for this." You recognize this as paradigm blindness.
- Market Risk:: If we don't do this, someone else will.
Retrieval practice
Recall check 1 of 3
Blueprint Bina says: answer from memory, then check your reasoning.
Q1According to Clayton Christensen's Innovator's Dilemma framework, why do successful companies most often fail to adopt disruptive technologies like IoT?
Show answer
Answer: B Correct!
Retrieval practice
Recall check 2 of 3
Blueprint Bina says: answer from memory, then check your reasoning.
Q2A hospital administrator dismisses IoT-enabled hospital beds that monitor patient vitals and auto-adjust position: "Beds don't need to be smart. We have nurses to monitor patients and adjust beds manually. This adds cost without value." Which cognitive mechanism of paradigm blindness does this represent?
Show answer
Answer: B Correct answer is B.
Retrieval practice
Recall check 3 of 3
Blueprint Bina says: answer from memory, then check your reasoning.
Q3Place each historical reasoning step where it belongs so you can turn a technology forecast into an adoption hypothesis and a measurable strategic pilot.
Show answer
Answer: A IoT history teaches a sequence: separate technical possibility from adoption behaviour, inspect second-order effects, then reframe the opportunity as a pilot with an explicit decision.
Q4Complete the smart home automation rule engine:
Show answer
Answer: A dict.get() safely retrieves sensor values. Using callable conditions (lambda) allows flexible rule definitions.
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Answers
Answer key.
- B · Correct!
- B · Correct answer is B.
- A · IoT history teaches a sequence: separate technical possibility from adoption behaviour, inspect second-order effects, then reframe the opportunity as a pilot with an explicit decision.
- A · dict.get() safely retrieves sensor values. Using callable conditions (lambda) allows flexible rule definitions.