Given the staggering quantities of data that confront us on a daily basis, the challenge becomes a matter of 1) choosing the best “algorithm” that will enable us to make the wisest decisions and 2) using the results of that algorithm to improve operations.
At Objective Arts we build software for deploying algorithms in business operations. But what is an algorithm? We feel that one critical part of describing our software lies in clarifying terms. The software industry is plagued with overloaded and vague terms, jargon, and ‘buzzwords’. As a result, it has become all too easy to misunderstand and misconstrue concepts. One example taken from recent media attention is the term “Big Data.” Few people can clearly define what “Big Data” really means. Even among those who can define it, there is usually a great deal of discrepancy in their interpretations of the term. Ultimately, it seems that nobody can accurately define what “Big Data” really means.
“Algorithm” is also a buzzword of sorts. Fortunately, the term does have some concrete definitions. Wikipedia defines it as “a step-by-step list of directions that need to be followed to solve a problem”. For computer scientists, this is an entire field of inquiry. However, their focus is on efficiency of software code. Another form of algorithm is the recipe a cook uses Our emphasis is to employ numeric recipes to reduce uncertainty and risk (see Douglas Hubbard’s insights in ‘How to Measure Anything’). The fundamental problem Objective Arts is trying to solve is the lack of standardized data to make decisions. Algorithms in our systems typically consist of numeric formulas or a series of “if this, then” statements. These two entities can be combined and configured into very complex organizational advice recipes. For your organization, the means to solving a “problem” becomes a matter of generating a series of algorithmic results that can reduce uncertainty at any level, be it for an individual practitioner, or for an entire organization.
At Objective Arts, we also focus on finding and employing those algorithms that have the greatest likelihood of adding value. Given a choice between an untested algorithm devised by a person with a few years of experience, based on anecdotal data, and an evidence-based algorithm created by an academic researcher who has spent two decades researching and publishing an idea, we will nearly always employ the latter.
But a key feature of our software is that the customer gets to select which algorithm(s) they would like to employ. Our job is to provide the best mechanism to 1) Effectively and efficiently implement that algorithm through software, and perhaps more importantly to 2) Efficiently integrate that algorithm to solve business problems and make wise decisions. Deriving “answers” or “advice,” though necessary, is not sufficient. If software does not help a customer act efficiently and effectively on a large number of operational decisions, it is not doing its job.