Concepts of Prioritization
Chapter 1: Introduction to Prioritization
1.1 What is Prioritization?
1.2 Impact and effort
1.3 Units of impact and effort
1.4. Definitions of base units
1.5. What are the dimensions of impact
1.6. What are the uses of dimensions?
1.7 Order of magnitude
1.8. Structure of the Product world
1.1. What is Prioritization?
The world of product management is diverse and complex, filled with various types of products, processes, and people. Prioritization is the study of how we can effectively make decisions and allocate resources to maximize the value of our products. Just as the laws of physics govern the events and phenomena we observe in nature, the principles of prioritization are the fundamental rules that guide product managers in their decision-making process.
The rules of prioritization are not arbitrary; they are discovered through observation and experimentation. Product managers watch how different products and features are received by customers, and how different teams perform on various tasks. Through this observation, they can begin to identify patterns and relationships that help them understand the fundamental principles that govern successful product development.
The principles of prioritization apply to all areas of product management, including product strategy, design, development, and marketing. By understanding these principles, product managers can make better decisions about which features to build, which markets to target, and which investments to make.
However, the rules of prioritization are not fixed and immutable. As the world of product management evolves and new products and technologies emerge, the principles of prioritization must be adapted and refined to reflect the changing needs and demands of the marketplace. The most successful product managers are those who can continually observe, experiment, and adapt their approach to product prioritization in response to new challenges and opportunities.
1.2 Impact and Prioritization
Impact is a tool for prioritization. Impact analysis is a way of evaluating the potential outcomes of different actions or decisions, just as mathematics is a tool for predicting the outcome of physical events. By using impact analysis, we can make predictions about the consequences of our choices, and prioritize the actions that will have the greatest impact.
Without the ability to analyse impact, we may have a difficult time understanding and explaining the potential outcomes of different decisions. Prioritization allows us to communicate our ideas and make informed decisions about how to allocate resources.
Ultimately, our goal in using impact analysis and prioritization is to understand and make the best decisions about how to achieve our goals.
1.3 Units of Impact
Prioritization involves comparing and choosing between various options or tasks which have impact and take effort. To make these decisions, we need to quantify the impact and effort associated with each option. To do this, we use units of measurement for both impact and effort. The units chosen for measurement must be standard and agreed upon, similar to where we have standard units for physical quantities like mass, length, and time.
For example, if we are comparing the impact of two projects, we might use units of monetary value, such as dollars or euros, to measure the expected return on investment. Similarly, for effort, we might use units of time, such as hours or days, to measure the amount of work required to complete a task.
It is important that the units chosen for measurement are standardized and universally recognized to ensure consistency and accuracy in prioritization decisions. The choice of units may vary depending on the context and the stakeholders involved in the decision-making process. In some cases, the units may be determined by industry standards, while in other cases, they may be determined by government regulations or internal organizational policies. Ultimately, the choice of units should be transparent and communicated clearly to all stakeholders involved in the prioritization process.
1.3.1 Who decides these units?
In the context of impact and effort units in prioritization, the decision on what unit to use ultimately depends on the organization or the team responsible for making the prioritization decisions. The choice of units should be based on the specific context and goals of the organization or team.
In some cases, there may be established industry standards or commonly used units for specific types of impact or effort measurements. For example, in software development, lines of code or story points are commonly used as units for measuring effort. In marketing, units of impact may include click-through rates or conversion rates.
However, in other cases, the organization or team may need to create their own units of measurement that are specific to their particular goals and context. This may involve a process of trial and error, as well as collaboration and consensus-building among team members to ensure that the chosen units are appropriate and effective.
Ultimately, the key factor in deciding on units is to ensure that they accurately reflect the impact and effort involved in the prioritization decision, while also being easy to understand and communicate among team members and can be used to measure organizational goals . By choosing the right units, organizations and teams can make more informed and effective prioritization decisions.
1.3.2 Fundamental and derived quantities
In physics, fundamental quantities are physical quantities that cannot be expressed in terms of other physical quantities. These are the basic building blocks of physical measurements. In the International System of Units (SI), there are seven fundamental quantities: length, mass, time, electric current, temperature, amount of substance, and luminous intensity.
Derived quantities, on the other hand, are physical quantities that are derived from fundamental quantities through mathematical relationships. For example, velocity is a derived quantity that is calculated by dividing the change in position (length) by the change in time. Other examples of derived quantities include acceleration, force, energy, and power.
In the context of impact estimation, it’s important to use the appropriate units for both fundamental and derived quantities in order to accurately measure and compare impact. Suppose there is a project aimed at improving the user experience of an e-commerce website. To estimate the impact of this project, we may choose the unit of measurement as “customer satisfaction score,” which is a derived quantity. We can derive this quantity by taking into account multiple fundamental quantities (of the org) such as the number of completed transactions, the average time taken to complete a transaction, the number of user complaints, etc. By combining these fundamental quantities, we can arrive at a single score that measures the overall level of satisfaction of the customers. This derived quantity of customer satisfaction score can then be used as the unit of measurement to estimate the impact of the project on user satisfaction.
Example 1:
- Profit as the fundamental quantity
Example 2:
- AARRR as fundamental quantities
Example 3:
- User Engagement: This measures how often users are interacting with the product and how long they are spending on it. This can be tracked using metrics like time spent on the product, number of visits, and click-through rates.
- User Acquisition: This measures the rate at which new users are signing up for the product. This can be tracked using metrics like new user sign-ups, app downloads, and website traffic.
- Revenue: This measures the amount of money generated by the product, which can include both direct revenue from sales or indirect revenue from advertising or other sources. This can be tracked using metrics like sales revenue, advertising revenue, and conversion rates.
- Customer Satisfaction: This measures how satisfied users are with the product and can be tracked using metrics like net promoter score (NPS), customer satisfaction surveys, and user feedback.
- Operational Efficiency: This measures the efficiency of the internal processes and systems used to develop and maintain the product. This can be tracked using metrics like time to market, development costs, and bug rates.
By measuring and analyzing these fundamental quantities, a digital product company can gain insights into the impact of their product and make data-driven decisions about how to prioritize and improve their product.
1.3.3. Standard system of units for impact analysis
In order to facilitate effective impact analysis, it is important to have a standard system of units for measuring impact. This ensures that different people can use a consistent set of units to measure the same impact, which is essential for making valid comparisons between different impacts.
For instance, let’s say a company wants to assess the impact of a new product on customer satisfaction. If the product team uses a different unit of measurement for customer satisfaction than the marketing team, it will be difficult to compare the impact of the product across different departments. This may lead to confusion and potentially incorrect conclusions about the impact of the product.
Having a standard system of units helps to avoid this problem by providing a common language for impact analysis. For example, a commonly used unit of measurement for customer satisfaction is the Net Promoter Score (NPS), which is a scale that ranges from -100 to 100. Using a standard system of units like NPS ensures that everyone within the company is on the same page when it comes to measuring the impact of the product on customer satisfaction.
In addition to improving consistency and facilitating comparison, a standard system of units also helps to ensure that the results of impact analysis are accurate and meaningful. If the units of measurement are not standardized, it may be difficult to interpret the results of the analysis, and the accuracy of the conclusions drawn from the data may be called into question.
A standard system of units is essential for effective impact analysis, as it promotes consistency, facilitates comparison, and ensures that the results of the analysis are accurate and meaningful.
1.4. Definitions of Base units
In product management, base units are the fundamental units of measurement used to quantify the impact and effort of various product-related activities. These base units can be used to derive other units that help product managers estimate the impact of a particular project or feature, and make data-driven decisions about prioritization.
The most commonly used base units in product management include:
Users: The number of unique individuals who use a product or feature over a specific period of time. This is a crucial base unit, as it helps product managers determine the potential impact of a project on the user base.
Profit: The amount of profit a product generates over a specific period of time. This base unit is important for product managers who are focused on revenue growth and want to estimate the potential impact of a project on the company’s bottom line.
Time: Time spent by user over a period or during an occurrence or across n occurrences with the product
Satisfaction: The unit “NPS Score” is used as an example. Depending on the method of measuring satisfaction, this could be replaced with “Rating,” “Stars,” or another relevant unit.
The following can function as derived quantities
For example,
Engagement: The level of user engagement with a product or feature, often measured in terms of time spent or frequency/number of interactions. This base unit is useful for product managers who are focused on improving user experience and want to estimate the potential impact of a feature on user engagement.
Frequency: Frequency is the number of occurrences of a repeating event per unit of time. For example, number of times a user performs an action or uses the product over a period. It is strongly recommended that the event should be a direct contributor to revenue. An indirect contributor can be used but your business and industry should be aligned with treating as a fundamental unit so as to track it and put significant resources behind it. When such an event is defined, there is no requirement to have frequency as a separate dimension, inverse of time would be an appropriate dimension to help track the frequency.
One can also have their own quantities setup as fundamental for their organisation’s purposes.
By using these base units, product managers can derive other units that are more specific to their product or industry. For example, a product manager at a social media company might use the base unit of “daily active users” to estimate the impact of a new feature on user engagement, while a product manager at a subscription-based company might use the base unit of “monthly recurring revenue” to estimate the impact of a new pricing model.
Overall, the use of base units is essential for impact estimation in product management, as it provides a common language for product managers to measure and compare the impact of various projects and features.
1.5. Dimensions of impact
In product management, the impact can be broken down into different dimensions. Dimensions represent the fundamental aspects of the impact that need to be considered when prioritizing features and tasks. For example, if the impact is related to user engagement, the dimensions of impact may include the number of users affected, the frequency of impact, the duration of impact, and the degree of impact on user satisfaction. By considering these dimensions, product managers can more effectively prioritize tasks and allocate resources to achieve the desired impact. The dimensions of impact can be thought of as the base quantities from which other units of impact are derived.
Example 1.1
Calculate the dimensional formula of Engagement from the equation
E = Number of users * Frequency per user * Time per user per usage
Solution:
Number of users — U and frequency per user — 1/T. Time per usage dimension is T — time
[E] = [U]* [1/T]* [T] = [U]
Example 1.2
Calculate the dimensional formula of Retention from the equation
Re = Number of users 1 month from now /Number of users today
Solution:
Both numerator and denominator are scalars without dimensions
[Re] = [1]/ [1]= [1]
Retention has no dimensions
1.6 What are the uses of dimensions of impact?
The dimensions of impact are used to help product managers make informed decisions when prioritizing features and tasks. By breaking down the impact of a task into different dimensions, product managers can better understand the potential impact of a task on the product and its users.
The dimensions of impact can also help product managers allocate resources more effectively. For example, if a task has a high degree of impact on user satisfaction but a relatively low frequency of impact, product managers may prioritize that task over another task that has a higher frequency of impact but a lower degree of impact on user satisfaction.
In addition, the dimensions of impact can be used to track and measure the impact of tasks over time. By monitoring the different dimensions of impact, product managers can assess the effectiveness of their prioritization decisions and adjust their approach as needed.
In product management, it’s important to ensure that the units used to express different dimensions of impact are consistent and compatible. This is known as the concept of homogeneity of dimensions, and it is essential for effective impact analysis. Essentially, when different dimensions of impact are expressed using inconsistent units, it becomes difficult to accurately compare and prioritize tasks based on their impact.
For example, if one task is measured in terms of its impact on user satisfaction per hour, and another task is measured in terms of its impact on revenue per day, it becomes challenging to compare the two tasks and prioritize them appropriately.
Therefore, by maintaining homogeneity of dimensions, product managers can ensure that different dimensions of impact can be compared and prioritized in a more accurate and effective manner.
Limitation:
Note that the dimension of [Number of users]* [Number of referrals per user] has the same dimensionality as 2*[Number of users]* [Number of referrals per user]. Pure numbers are dimensionless and dimension does not depend on magnitude. Dimensionally correct equation need not be actually correct but a dimensionally wrong equation must be wrong.
Example 1.3:
Test dimensionally if the formula Annual Revenue = (Number of users)² x (Annual revenue per user) may be correct
Solution:
The dimension of user = U , Annual revenue per user = D/U
Dimension of RHS = U²D/U = UD which does not match with revenue unit which is D
Hence the formula is incorrect
Example 1.4:
Test dimensionally if the formula Referral rate= (Number of users) x (Retention rate) * (Number of referrals per user) may be correct
Solution:
The dimension of user = U , Retention rate = 1 , Number of referrals per user= 1/U
Dimension of RHS = U/U = 1 which does match with LHS as they both do not have dimensions
Hence the formula maybe correct
The actual correctness of the formula is usually dependent on the business context
1.7 Conversion of units
In impact analysis for product management, it is often necessary to convert units of measurement in order to make meaningful comparisons and prioritize tasks effectively. It is important to ensure that the conversion of units does not alter the fundamental meaning or value of the measurement. This means that the conversion factor used should be derived from the relationship between the units, and should not introduce any additional factors or assumptions that would alter the meaning of the impact measurement.
By converting units in impact analysis, product managers can more effectively prioritize tasks and make informed decisions about the allocation of resources, based on a consistent and comparable measurement of impact.
Let’s consider two projects for a digital product company:
- Project A: This project is aimed at improving user satisfaction by adding new features to the product. The impact of this project is being measured in terms of a user satisfaction score.
- Project B: This project is aimed at improving customer retention by improving the product’s performance and fixing bugs. The impact of this project is being measured in terms of a customer retention rate.
To compare the impact of these two projects in terms of revenue, we need to convert the impact units to a standard unit or common currency. One possible approach is to estimate the impact of each project on revenue by using historical data on the relationship between the impact units and revenue.
Example 1.5
Historical data shows that a 1% increase in user satisfaction score is associated with a 0.5% increase in monthly revenue, and a 1% increase in customer retention rate is associated with a 1% increase in monthly revenue.
If Project A is expected to increase the user satisfaction score by 5%, and Project B is expected to increase the customer retention rate by 3%, identiy which project has a higher impact on revenue.
Solution
Project A: 5% increase in user satisfaction score * 0.5% increase in monthly revenue per 1% increase in user satisfaction score = 2.5% increase in monthly revenue
Project B: 3% increase in customer retention rate * 1% increase in monthly revenue per 1% increase in customer retention rate = 3% increase in monthly revenue
Project B is expected to have a greater impact on revenue than Project A
By converting the impact units to a common currency, we can compare the impact of different projects more effectively and make better prioritization decisions.
1.6.3 Deducing Relation Among Quantities
In product management, the dimensions of impact can be used to deduce relationships among quantities and inform prioritization decisions. For example, let’s consider user engagement and retention as two quantities. User engagement may be measured by the number of active users, frequency of use, and duration of use. Retention, on the other hand, may be measured by the number of users who return to the product after a period of time.
By examining these two quantities, we can deduce that there is likely a relationship between user engagement and retention. It is reasonable to assume that a product with high user engagement will have high retention, and vice versa. By quantifying the relationship between these two quantities, product managers can make informed decisions about which areas to focus on in order to maximize the impact of their product.
For example, at a company, a 10% increase in user engagement results in a 5% increase in retention. In this case, we can use this relationship to estimate the impact of a new feature that is expected to increase user engagement by 20%. Based on the relationship we have deduced, we can estimate that this increase in engagement will result in a 10% increase in retention. From here, we can use this estimate to prioritize this feature against other potential projects that may have different expected impacts. One must also be careful about deducing causation when there is only correlation.
1.7 Order of magnitude
In impact analysis and product management, the order of magnitude is an important factor to consider when making prioritization decisions. It refers to the size or scale of the impact or effort involved in a given task or feature. When considering the order of magnitude, we are looking at the relative size of the impact or effort compared to other tasks or features.
A company may be using a simple Impact/Effort as a estimate to prioritize between features/tasks. Here, order of magnitude plays a significant role.
For example, if we are considering two features for a product, one that will have a small impact on user engagement and another that will have a large impact, we need to consider the order of magnitude of each impact. The large impact feature may require significantly more effort to implement, but the potential benefits may also be much greater than the small impact feature. By considering the order of magnitude, we can make more informed decisions about which features to prioritize.
In addition to impact, the order of magnitude is also important to consider when evaluating effort or resources required for a given task. A task that requires a small amount of effort may be a lower priority than a task that requires a larger effort if the latter has a significantly greater impact on the product.
Overall, understanding the order of magnitude of impact and effort is a key factor in making effective prioritization decisions in product management and impact analysis. By considering the relative scale of different impacts and efforts, product managers can allocate resources and prioritize tasks in a way that maximizes the overall impact of the product.
1.8 Structure of the Product World
In product management, prioritization is just one part of the larger picture of building and managing a product. The product world is a complex ecosystem with many different stakeholders and factors to consider.
At the highest level, the product world can be divided into two main categories: external and internal factors. External factors include things like market trends, customer needs, and competitor analysis, while internal factors include things like team capabilities, resource availability, and technical constraints.
Within this larger context, prioritization is the process of deciding which features or tasks should be tackled first based on their potential impact on the product’s goals and objectives. It is an important part of product management because it helps ensure that resources are allocated effectively and that the product is moving in the right direction.
Prioritization can be informed by many different factors, including the dimensions of impact, order of magnitude, and the effort required to complete a task. It is also important to consider the potential trade-offs between different features or tasks and the impact they will have on other parts of the product.
Ultimately, successful prioritization requires a deep understanding of the product and its goals, as well as a data-driven approach to decision-making. By carefully considering the different factors that contribute to the product world and using a structured approach to prioritization, product managers can help ensure that their products are successful and achieve their goals.
Worked out examples
- Find the dimensional formula of the following quantities
a. CLTV
b. Referral rate
c. Average Viral cycle time
d. Click through rate
Some equations involving these quantities are
CLTV = (Average Customer Order Value) * (Number of Sales per month) * (Average Retention Time)
Referral rate = (Number of Customers Who Made a Referral / Total Number of Customers) * 100
Average Viral Cycle Time = Total time taken by users to refer / Number of referrals
Click through rate = Number of clicks/Number of impressions
Solution
a. CLTV = (Average Customer Order Value) * (Number of Sales per month) * (Average Retention Time)
CLTV = Dollars [D] * Frequency [1/T] * Time [T] = D
b. Referral rate = (Number of Customers Who Made a Referral / Total Number of Customers) * 100
Referral rate = [U]/[U] = [1]
c. Average Viral Cycle Time = Total time taken by users to refer / Number of referrals
Average Viral Cycle Time = [T]/[U]
Evident from the dimensional formula is for one to reduce average viral cycle time as much as possible as [U] is in denominator
d. Click through rate = Number of clicks/Number of impressions
Click through rate = [1]/[1] = [1]
2. Find the dimensional formula of the following quantities:
a. Customer acquisition cost
b. CPC
c. Viral coefficient
Solution
a. Customer acquisition cost = Total Cost of acquisition/Number of users acquired = [D]/[U]
b. CPC = cost per click = Total cost per campaign / Total number of users who clicked * avg number of clicks per user = [D]/[U]
c. Viral coefficient = Average number of referrals per user*Conversion rate of referrals =Total referrals/total number of users who referred *conversion rate = [1]/[U]
3. If Lifetime value [L], Avg cart value in dollars[D] , Frequency of orders per month [F] are basic quantities, find the dimensions of average retention time
Solution
Lifetime value [L]= Avg cart value in dollars[D] * Frequency of orders per month [F] * average retention time
[Average retention time] = [L]/[DF]
4. Test dimensionally of the equation
ARPU = Growth rate * avg order value pernew user + Retention rate * avg order value per existing user
Solution
ARPU = Dollar/User = D/U
[Growth rate] * [Average order value per new user]= [1] * D/U= D/U
[Retention rate] *[avg order value per existing user] = [1]*D/U = D/U
Thus, the equation may be correct
5. Revenue of a product is given by Revnue = a*CLTV + b* Monthly Growth rate + c * Retention rate. Find dimensions of a, b, c
Solution:
Revenue = [D]
CLTV = [D]/[U] => a = [U]
Growth rate = Number of new users this month/Number of users at the end of previous mont= [U]/[U] =[1] => b = [D]
Retention rate = Number of users active this month/Number of users active last month = [U]/[U] = [1] => c = [D]
6. If conversion rate has formula Conversion rate= [(People who visit)^a]* [(People who click)^b]*[ (People who buy)^c] , find the values of a, b ,c
Solution:
Conversion rate = People who buy/People who visit
Hence a=-1, b = 0 , c = 1
Objective I
- Which of the following sets cannot enter into the list of fundamental quantities in any system of units?
a. CLTV, User base, Revenue
b. CLTV, CAC, User base
c. Growth rate, retention rate, engagement
d. CLTV, Average order value, User base
2. A dimensionless quantity.
a. never has a unit
b. always has a unit
c. may have a unit
d. does not exist
3. A unitless quantity
a. never has a nonzero dimension
b.always has a nonzero dimension
c. may have a non zero dimension
d. does not exist
Objective II
1. Choose the correct statement(s) :
(a) A dimensionally correct equation may be correct.
(b) A dimensionally correct equation may be incorrect.
(c) A dimensionally incorrect equation may be correct
(d) A dimensionally incorrect equation may be incorrect.
2. Choose the correct statement(s) :
(a) All quantities may be represented dimensionally in terms of the base quantities.
(b) A base quantity cannot be represented dimensionally in terms of the rest of the base quantities.
(c) The dimension of a base quantity in other base quantities is always zero.
(d) The dimension of a derived quantity is never zero in any base quantity.
Objective I
- (a) 2. (c) 3. (a)
Objective II
1. (a),(b),(d) 2. (a), (b), (c)
