Followers of this site may have noticed the trend towards discussing information, information science, and information organization. This is no accident. This entire section of the site – Information Science – is dedicated to this. The home page for this section might describe it as follows:
An introduction to the theory and practice of information services, which are defined broadly as the activities in which information professionals engage to connect people to the information they need, including information needs assessment, direct information provision, information literacy instruction, and intermediation for all stages of the information search process.
I have spent nearly 30 years in the area of “Information Engineering”. My experiences have well prepared me for project management, personnel management, leadership, public speaking, system analysis, information and database design, requirements definition, planning, and program execution. One of my first jobs after leaving military service was to work in the US Intelligence Community helping to direct operations of spy satellites. One project focused on how to distribute information across different databases and alert others to what today would be called “breaking news”. At the time, it was difficult to assess exactly how to extract data from one system, transform it into a package that could be transmitted, then load that data into the destination system – something that destination might not have been designed to handle. We were faced with many of the contextual and vocabulary problems that have made recent headlines – is speed to be reported in imperial or metric units? Today, we are still having many of the same discussions – and still hoping for the same magical outcomes – that Vannevar Bush hoped for in 1945.
During the course of writing these essays, I have come to realize that my team of competitive intelligence managers and experts is, in fact, a Reference Service. I recently started seeking insights, theory, and practices associated with information science. My career, which has spanned decades, has been in service of engineering information – tracking it, seeing what people needed, how they wanted to consume it, how people could build upon it. I expected to work in the data analytics area for the rest of my career. I moved sideways in my career as a competitive intelligence manager by adding in the statistical analyses that should inform one when making decisions, particularly any decision when dealing with sales personnel. Salespeople, it should be noted, are in the business of making persuasive arguments. So, when they tell you that a particular trend is “happening everywhere I look”; well, you should look very carefully and bring your best data analysis. They are probably stretching the truth.
My job is to help sales staff sell better: by analyzing the details of the sales cycle, I would see what the various issues were which impeded the timely execution of the sales cycle. Identifying which opportunity to pursue has been a ‘holy grail’ of marketing and sales teams and data science purports to be a possible approach to solving/addressing this problem. Should the sales rep pursue the sales opportunity with a known customer, who buys regularly but only after lengthy periods of consideration or should they pursue the new opportunity that the computer tells them is a ‘slam dunk’? In the high-tech world where I work, this is a question faced by employees nearly every day.
I started analyzing patterns of data in 2013 and by 2015 had amassed millions of rows of sales data. Various patterns began to emerge, and I started to seek out the data scientist teams at work to see if there would be an algorithmic approach or solution to analyzing this data to suggest sales strategies to the field sales teams. In essence, we would be playing ‘Money Ball’ with our offerings, working to maximize our offerings. It is our job to give salespeople the information they need to make a persuasive argument to their customer prospect. Typically, that consists of teaching them how the competition will position their own offerings, how they will price, how they will attempt to create desire and demand in the customer’s mindset. Unraveling that takes sales skill but it also takes knowledge – a lot of it – to supplant one desire for another.
In my day job as a competitive intelligence manager, I collect information and synthesize it into a digestible form. In that process, I must maintain the provenance of the information and I must obtain the information in an ethical, appropriate manner. I distill the information and evaluate it against the current knowledge framework we have and consider the impacts or changes that this new information represents. Consider the following example: suppose we live on the edge of a flood plain. If I detect a large rainstorm on the horizon, it would be ethical (and moral) to advise people to move out of a possible danger zone. It would be innovative to determine new techniques which predict this approaching storm. This would be similar to my advising my engineering colleagues to build new features into a product because customers increasingly expect them.
I did not expect to find myself engaged in creating and managing a Reference Service. Much of my prior experiences dealt with delivering, deploying, and customizing content management systems for customers. In my quest to understand information retrieval, information organization, and how people approach the task of finding information, I took various models, theories, and fundamentals and evaluated my experiences. I thought I was assessing new databases and information services as a practice of a new skill – one that I could use in evaluating new information services at work, or a new service that the team might provide to others; I did not know I would be forcing myself to completely reevaluate our approach to offering services.
These essays have been part of that journey of self-realization. I hope you enjoyed them.