February 21, 2018
Fortune magazine recently did a piece on Shell, one of the pioneers in developing and using early warning systems. At Shell, the outputs are called “scenarios”.
The article indicated that the Shell early warning team “concluded that global demand for oil might peak in as little as a decade – essentially tomorrow in an industry that plans in quarter-century increments.” The piece goes on to detail what Shell is doing: “making some big strategic bets.”
What is of interest is that the rest of the oil industry now knows what She’ll is and will be doing. That raises an interesting issue: by acting and revealing what actions Shell, a dominant force in the oil industry, will take, Shell is giving its competitors, suppliers, and customers insights into its own contributions to making the oil industry look different from today. And that is also changing the future Shell has projected. That means that, if Shell is right about its scenario, by acting and broadcasting those actions, it may, nay will, cause the future to be different from what it would be absent it’s actions.
Of course, this means that, in a decade, when Shell measures it’s accuracy in predicting the future, it may find it was wrong. But, this is because it did\could not factor in the direct and indirect consequences of its response to what was then still in the future as well as the responses of others in this business ecosystem to its responses, etc. Yet, the scenario could still be extremely invaluable, even if they cannot prove it.
Is your brain still on straight? Welcome to a brave new world.
May you, your family, and friends all have a Happy Kwanzaa and a Very Happy New Year.
May you and your family and friends have a Very Merry Christmas.
December 12, 2017
Have a very Blessed and Happy Chanukah.
November 21, 2017
To you and your families and friends, have a wonderful Thanksgiving.
September 25, 2017
Our newest book, Competitive Intelligence Rescue – Getting It Right, has several cases that highlight issues in creating or adding a new competitive intelligence unit. In our experience, there are usually 7 major elements involved in that process:
- financial and personnel
- internal marketing
- customers and their needs, and
- products and feedback.
Here are my comments (brief) on some major training issues:
- Every member of the CI team as well as ambitious DIYers, should get some sort of CI training at least once a year. That can be almost anything: attending a local association’s chapter meeting, a national conference, or a commercial workshop, so long as CI is the main topic of the session(s) you attend.
- Communication skills deserve training – internal or external. Your analysis is not worth much if you cannot communicate its importance and significance to others.
- Regular training, say every three years, on legal and ethical issues is a must. If you can get someone from your legal team to participate. Also, the CI team should be conducting training on these issues for its internal customers. Aware customers make it easier to stay on the straight and narrow.
- Over time, additional training on various analytical techniques will not only upgrade your personal skill set, but it will help you in determining your internal customers’ needs, in selecting the right targets, and in selecting and managing your Ci products and outputs. Aim at doing this every couple of years.
- General management issues cannot be overlooked. They include things like succession planning, assessing employee performance, creating and managing networks, and well as on managing your internal clients’ expectations. Hopefully your firm already offers these to you and your peers. Take them.
This is not the first time I have written on these issues: Carolyn Vella and dealt with them in The Manager’s Guide to Competitive Intelligence. Also, please check out my past blogs under the Category “Education and Training’, and look at these three, for more on this:
September 9, 2017
The hurricane activity of the past weeks in the US is still sinking in for all of us, in particular the many residents of the damaged areas. They are in our prayers.
But for those of us in CI, there is a lesson.
The forecasters, private and governmental, were unable to predict the track of either Irma or Harvey more than 48 hours out. Yet they were working with dozen, perhaps hundreds of programs, vast amounts of computer power, decades of records, and real time data from space, hurricane penetrating aircraft, and ocean buoys.
Because real life is never 100% predicable. Keep that in mind when you find that you cannot totally predict a competitor’s reactions to your new product launch – or whatever.
Close enough is as much as humans (and computers) can come in the real world.