Most organizations want or need to produce more than one product at a time. These multi-product organizations need a way to make economically rational choices regarding managing their product portfolios. They also need their portfolio management or governance processes to align well with core agile practices; otherwise, there will be a fundamental disconnect with the agile approach being used at the individual product level. This article lays out strategies for portfolio planning.
Definition of Portfolio Strategy
A portfolio strategy serves as a plan of action for deciding which items in the portfolio backlog should be worked on, in what order, and for what duration. The portfolio backlog can consist of various items, including products, product increments, or technical initiatives. For simplicity purposes, the word product in this article represents all portfolio backlog items. The purpose of a portfolio strategy is to guide the prioritization and allocation of resources toward the most valuable items in the portfolio backlog, ensuring that the organization’s goals and objectives are met efficiently and effectively.
A portfolio strategy is a complex, dynamic, and iterative process that involves multiple inputs, outputs, and stakeholders. Therefore, the decision engine must be flexible and adaptable to ensure that the company’s product portfolio remains aligned with the organization’s goals and objectives, even as market conditions, customer needs, and resource availability evolve.
- Market and customer analysis: Detailed information about the target market segments, customer needs, and preferences.
- Product portfolio analysis: A comprehensive analysis of the company’s product portfolio, including product segments (existing and new), market share, maturity, growth potential, and profitability.
- Resource availability: Information about the available resources, including budget, manpower, and technology.
- Prioritized product portfolio: A prioritized list of product segments, including existing and new products
- Resource allocation plan: A plan for allocating resources to support the development and growth of the most promising product segments.
- Senior management: The individuals responsible for making strategic decisions about the company’s product portfolio.
- Product management: The individuals responsible for managing the company’s product portfolio and ensuring that it aligns with the organization’s goals and objectives.
- Development teams: The individuals responsible for delivering the product increments and technical initiatives that make up the product portfolio.
- Customers: The end-users who purchase and use the products offered by the company.
- Investors: The individuals or organizations that provide funding to the company and have a vested interest in its success.
Portfolio decision engine:
- Input inflow strategies: Input inflow strategies use a company’s economic criteria to make go/no-go decisions.
- Resource scheduling strategies: To efficiently distribute a company’s restricted resources among its products for optimal economic results.
Portfolio Decision Engine
There are two core elements of the portfolio decision engine:
- Input inflow engine
- Resource scheduling engine
The input inflow engine balances the rate at which products are inserted into the portfolio backlog for resource allocation.
Input inflow engine
The goal of the input inflow engine is to apply an organization-specific economic filter to assess new and existing product ideas emerging from internal ideation, competitive analysis, and customers. The four key input variables that can help make tradeoff decisions are:
- Existing market penetration: Impact in terms of market share penetration.
- New market penetration: Applicability of the product to new markets.
- Competitive threat: Impact of competition on the products
- Confidence level: Confidence in building the product after assessing market, technical, and regulatory risks.
Now that we have defined variables let’s look at some sample scenarios:
A and B products have the same impact on existing and new markets. However, product A has a higher confidence level on market impact than product B.
Product A is a “go” while the teams work on improving the confidence level of product B.
A and B products with the same amount of impact on existing and new markets and have similar confidence levels. However, product A has a higher competitive threat. For example: chatGPT threat on Google’s search engine.
In this scenario, both products are a “go.” However, the resource scheduling engine (next section) will prioritize resources for product A as the cost of delay is HIGH because of higher competitive threat.
Resource scheduling engine
The goal of the resource scheduling framework is to allocate a limited amount of resources to a sequenced list of product items maximizing the overall lifecycle profits of the entire portfolio. We have to sub optimize individual products to optimize the portfolio. The three most essential input variables that can help make tradeoff decisions are:
- Lifecycle profits: Potential profits for each of the product items
- Cost of delay: Financial impact of delaying work or not reaching a milestone
- Effort estimates: Sizing estimates to build each of the product items
Now that we have defined variables, let’s look at some sample scenarios:
A and B products, with the same lifecycle profits, are needed to take a high-value customer live. However, product A has higher effort estimates compared to Product B.
A and B products have the same lifecycle profits and effort estimates. However, the cost of delaying product A is higher than product B. For example, Product A is needed to take a customer live that has an earlier deadline than the other customers.
Both products, A and B, have the same lifecycle profits. But, product A has a higher delay and effort estimate cost than product B.
Weighted short job is calculated as the cost of delay divided by the effort estimate. In this scenario, product A has the highest weighted value and hence is executed first.
Product A has a higher cost of delay, lifecycle profits, and effort estimates compared to product B.
Product portfolio management involves determining product priority, order, and duration. The “Input Inflow Engine” balances the flow of products into the portfolio backlog by applying an economical filter to evaluate new and current product concepts generated internally through competitor analysis or customer feedback. The prioritized product list from the Input Inflow Engine serves as inputs for the “Resource Scheduling Engine.” This engine allocates limited resources to a sequential list of products to maximize the overall profits of the entire portfolio over its lifecycle.