During the TTM Generation, a phase-review process was generally used to integrate decisions across projects, and these phase reviews prompted some very large questions. What projects fit our strategy? Do we have the right mix of projects? Have we deployed our R&D investment in an effective manner? How can we better balance our entire pipeline of projects to eliminate resource bottlenecks?
Many companies initiated basic portfolio analysis shortly after they began confronting these questions, but they tended to do it periodically. Analysts began to collect some information from all projects in order to evaluate project characteristics such as the distribution of R&D investment across the portfolio by type of project, or the return on project investment compared to project risk. An individual or a group was sometimes assigned the responsibility of being the portfolio manager. As portfolio analysis proved very helpful in guiding better product development decisions, executives and portfolio managers began to ask for more and more analysis.
The problem was that all portfolio data had to be collected manually, because product development teams were all using independent and inconsistent practices and systems to manage the information on their projects. Some team managers and members stored project data in spreadsheets on their personal computers, some created this information for presentations, and some used formal planning documents to define the information. Some important information, such as information vital to project-risk analysis, was not even collected by some project teams. This was even worse if a company wanted to manage multiple portfolios across multiple divisions.
The collection of portfolio data was time-intensive, usually taking many weeks or even months, and by the time the information was rounded up, much of it was already out of date. Projects had progressed to a new phase and had new information. Development teams revised their information based on what they were learning. And new projects were initiated. Moreover, some teams reported data to the portfolio manager that were different from the data used to get approval of their projects.
Spreadsheets were typically used as the repository of this manually collected information, and portfolio and pipeline charts were then created from these spreadsheets. In some cases, these spreadsheet tools were quite complicated, with programming that enabled data to be entered into worksheets that automatically moved the data to the right spreadsheets, which in turn produced the portfolio and pipeline charts.
Because of the need to collect all of the project data manually and enter it into the spreadsheet tools to produce charts, portfolio and pipeline management was done periodically, typically when there was some sort of problem or pronounced resource constraint. Companies managed their portfolios and pipelines on an annual basis, or sometimes more frequently, but, generally, they did not have the people available to perform this management continuously.
Data collection wasn't the only problem. Sometimes, portfolio managers were so impressed with the charts that they lost sight of the underlying data. I recall a meeting I once had with a VP of R&D. He proudly showed me charts on the distribution of R&D investment by type of project (platform, major product, minor product, or enhancement). When he finished explaining his conclusions, I asked him a few questions. Did the investment information used in the analysis include the entire investment for a product? For example, was the $10 million project with $7 million completed and $3 million remaining included as $10 million, or $3 million? Did the chart represent investment over the previous years, or the expected investment for this year? Did it include just the active projects, or past and future projects? If the chart represented the investment for this year, how much was unallocated, and where was this amount? He didn't know the answers, and began to doubt what was really represented on the charts he was using to make decisions.
Companies in this stage generally concluded that portfolio and pipeline management was essential to running the business, but they were frustrated by the labor required to collect the data, how quickly the data "spoiled," the inability to do the analysis whenever they wanted to, and the lack of flexibility in ways to look at it. These limitations formed the requirements for the next stage in portfolio and pipeline management.
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What you need to know about… Project Management Made Easy! Project management consists of more than just a large building project and can encompass small projects as well. No matter what the size of your project, you need to have some sort of project management. How you manage your project has everything to do with its outcome.