Unreliability of Available Data
The unreliability of available data is another paramount cause of error in portfolio planning. The lack of a quality data metric that’s clear to understand and provides information that can be analyzed can force the PMs to make high-risk decisions that do not always pay off. This can occur, for example, when marketing and sales teams submit product win and loss reports to the product managers without providing a detailed analysis of the why a particular product didn’t sell and how they think the sell could have gone better. This can force PMs to rely on their judgment rather than solid metrics and factual feedback.
A Lack of Roadmap for Critical Themes
It’s critical to create a roadmap, however short it may be, for market-focused products. Lots of organizations do not have the rigor to create and maintain one. Without the roadmap, the stakeholders are in no position to prioritize and decide on parallel versus sequential streams of work to address multiple market demands and business goals.
While the new world of social media presents innumerable opportunities for the portfolio managers to exploit new channels and drive and measure sales, service and marketing yet not having a roadmap for determining the direction(s) to go for based on organizational drivers can leave the PMs with multiple costly campaigns and not enough return on the dollar spend. A lack of a roadmap also leads engineering divisions to undermine capacity planning, which results in a sloppy and risk-laden execution followed by potential launch delays.
Consider Google, which infamously closed a few of its new products like Google Health, Google Gears, Google Buzz, and others. Many individuals and companies who were using these products were taken by surprise as the overarching Google App roadmap was never created or shared. This forced many enterprise businesses to take a close look at Google’s overall roadmap with new products as Google can decide to kill any of its products based on its own adoption numbers. These businesses are questioning Google’s reliability as an enterprise platform partner, primarily for socially relevant sectors like education.
Mismatched Resourcing Results in Late Products
Most large enterprises are divided into silos, thereby resulting in the separation of duties and responsibilities. The product management divisions have either no or limited power and influence to determine the staffing and resourcing plans for the engineering units. This can result in poor planning of infrastructure, technology and skill-set needed by the engineering units for maintaining and extending the current portfolio.
I recently got a chance to work with the digital marketing division of a large financial company that wanted to create a rich, media-driven Web 2.0-enabled website to reach out to its customers. While the product owner team from the marketing division had good intentions for the product and worked hard to prepare a roadmap, it had no power to influence the key factors needed to define, design, build, and test the product. The tools used for the product development and testing were not appropriate for the product development work, and the people identified to do the work didn’t have the right set of skills resulting in inordinate delays of the launch.
A Lack of Objective Prioritization of Product Lines
Objective, data driven prioritization is a critical element that aligns the portfolio with the organizational strategy and divisional goals. More often than all, especially in large enterprises, the prioritization depends on which stakeholder shouts the loudest rather than the alignment of the product with the organizational goals. All the above factors (insufficient data, inaccurate data, and unreliable data) contribute to this behavior and the PM is rarely able to make objective decisions on critical product issues.