Data is the new fuel- it drives businesses towards exponential growths. It has the power to transform operational and add intelligent insights with its immense potential. The key, however, lies with understanding data and its insights.
Logistics, like other domains, can also leverage from the several advantages of data. It all begins with what to do with the collected data. Data Science will come into the picture with its amalgamation of statistical &…Continue
Added by Bhushan Patil on July 21, 2019 at 8:37pm — No Comments
Big data is the buzzword today, isn’t it?
We live in the golden age of what…Continue
Added by Hiren patel on June 14, 2019 at 7:42pm — No Comments
Deep Learning is picking momentum in Quantitative Finance, outside the obvious application to the prediction of asset prices (where to my knowledge it is not particularly effective) and spreading into the more serious application area of option pricing and risk management.
These two recent papers clearly demonstrate the benefits of DL as a pricing technology alternative to the classical FDM and Monte-Carlo in certain contexts:…Continue
Added by Antoine Savine on January 11, 2019 at 5:30am — No Comments
Summary: Purpose Built Analytic Modules (PBAMs) such as those for Fraud Detection represent a fourth way to practice data science, a new model for the good use of Citizen Data Scientists, and a new market for AI-first companies.
Added by William Vorhies on September 18, 2018 at 9:07am — No Comments
The main components of systems theory that readers might remember are “inputs,” “processes,” and “outputs.” The part that tends to get neglected is “feedback mechanisms.” These mechanisms tell the system the extent to which operations fit the environment. If there is lack of fitness, there is stress. One adaptive impulse is to make processes more complex and intelligent - i.e. sometimes described as the fight response. Another impulse is to give up and run away - i.e. the flight…Continue
In the “Ecology of Metrics,” I wrote about “alignment” being a type of metric; alignment can measure the extent to which an organization’s supply or capacity is matched against the demands or needs of the market. For instance, in a call centre, it would be highly desirable to have agents available to respond to calls at “precisely” the same time that clients are making calls. If alignment is off even by only 15 to 30 seconds, impatient clients might hang up and never call again. Similarly…Continue
Added by Don Philip Faithful on June 2, 2018 at 5:00am — No Comments
Although I deal with many different types of metrics, I believe they can be generally classified as follows: 1) time use; 2) alignment; 3) production; 4) performance; 5) service; 6) and market. In this blog, I will be providing some comments pertaining to each. Although I have yet to encounter any myself, I am certain that there must be text books on the issue of operational metrics and how to make use of them. However, I personally developed nearly all of those that I use. Although I do…Continue
Added by Don Philip Faithful on May 26, 2018 at 9:00am — No Comments
Sometimes when dealing with performance metrics, there are contradictory signals. For instance, although both are desirable, it is common for efficiency and efficacy to be in opposition. An agent in a call centre can handle lots of calls while at the same time getting few sales; this is especially true if the agent’s main objective is to do lots of calls. This is a highly efficient person albeit unsuccessful in terms of expanding the business. Conversely, another agent by spending a…Continue
Added by Don Philip Faithful on May 6, 2018 at 3:30am — No Comments
About a month ago, I posted a blog on “Technical Deconstruction.” I described this as a technique to break down aggregate data to distinguish between its contributing parts: these parts might contain unique characteristics compared to the aggregate. For instance, I suggested that it can be helpful to break down data by workday - that is to say, maintaining separate data for each day of the week. I said that the data could be further deconstructed perhaps by time period and employee: the…Continue
Added by Don Philip Faithful on April 14, 2018 at 8:00am — No Comments
In all business areas making decisions is a natural and integral part of any company’s management process. Doesn’t matter if it’s a small family business or a huge multi-national corporation. At some point or another they all need to make decisions to ensure their continued operation. And that’s exactly what a manager’s job in an organization comes down to – a constant process of decision-making to ensure continued growth and…Continue
Added by Marina Pilipenko on April 5, 2018 at 5:00am — No Comments
The term “technical analysis” usually refers to the study of stock prices. A technical analyst might use real-time or closing prices of stocks to predict future prices. This is an interesting concept because of what is normally excluded from the analysis - namely, everything except prices. Given that the approach doesn’t necessarily consider the health or profitability of the underlying companies, a purely technical approach seems to offer guidance that is disconnected from reality. Yet…Continue
Added by Don Philip Faithful on March 17, 2018 at 3:00am — No Comments
What most people call “analysis,” I refer to this as “guidance.” It is not guidance in terms of guiding the company; but rather, I provide a narrative to help guide people through the data - of which there is a great deal. I play the role of a tour guide. I remember when I was a teaching assistant for a social science class - and there was a contentious area that would likely be the focal point for essays - I said that it didn’t matter to me what “opinions” people expressed. Nobody had…Continue
In general, any expression of performance that applies to a department can, if the data system is configured properly, be stated in relation to individual workers. For instance, if # of sales contracts / # of customer enquiries = success rate, the success rate can be given for the entire dealership and also for each sales agent in that dealership. Due to the differences in performance between agents, it can be problematic to only make use of the aggregate. Some agents might be blamed for…Continue
Added by Don Philip Faithful on February 25, 2018 at 7:30am — No Comments
Since I am sometimes asked to explain phenomena in the absence of data, it becomes necessary to determine what data is required to explain phenomena. Some would say the best approach is to develop and test a hypothesis - to start filling a void of space with pinholes of light - until there are enough lit pinholes to provide a working theory. This is not to say that a few additional…Continue
Added by Don Philip Faithful on January 20, 2018 at 6:00am — No Comments
I once posted about making use of narrative objects. In this blog, I will be discussing an algorithm that supports the creation of these objects. I call it my “Infereferencing Algorithm”: this term is most easily pronounced with a slight pause between “infer” and “referencing.” I consider this a useful and widely applicable algorithm although I don’t believe it operates well in a relational database environment. Instead, I use “mass data files”: these contain unstructured lumps of…Continue
Added by Don Philip Faithful on December 31, 2017 at 8:00am — No Comments
I have written in the past about the difference between market demand and operational capacity - and how difficult it is to determine what exactly is being measured in relation to either. Has the demand for a product declined, or is the organization simply less capable of satisfying it? For example, the fact there are no bananas in the grocery store does not mean that there is no demand for bananas; but the absence of revenues from the sale of bananas might be regarded, rather erroneously,…Continue
Added by Don Philip Faithful on December 9, 2017 at 10:30am — No Comments
One of the biggest problems in data management and data science is being able to obtain “good” data. You need to gather sufficient data from a substantial array of subjects who fit your study’s requirements, and ensure the accuracy of the data... otherwise, any conclusions you draw could be biased or skewed.
But assume for a moment that your data is already solid. That’s no guarantee of success, unfortunately: It’s like having all the ingredients of a pizza in one place but lacking…Continue
Added by Larry Alton on November 22, 2017 at 4:30pm — No Comments
For my graduate paper, I studied perceptions of workplace stress through the critical lens of social disablement. Writing this paper was certainly an intellectual exercise that at the time didn’t seem to have many practical applications. I am therefore honoured to become better acquainted with the “mechanics” of quantitative alienation through my day-to-day duties. I respect the fact that I can’t share any substantial details about my actual work processes on a blog. It will therefore be…Continue
Digital transformation is underway in practically every industry in the world. Companies, businesses and organizations throughout the world are leveraging their assets, big data and analytics for an edge over their competitors. In fact, data analytics and big data have gained popularity to the extent that data analysis for differentiation is…
Added by Ronald van Loon on September 3, 2017 at 11:30pm — No Comments
I spotted an interesting book in my local library recently: The Final Report of the Truth and Reconciliation Commission of Canada . I thought to myself, our government spent considerable resources on this commission. I should at least browse through the final report. I flipped through the first few pages. I found a note saying that the contents are public domain. In this blog, I reproduce some of the contents of the report to create a setting for my discussion on operational data. …Continue
Added by Don Philip Faithful on August 6, 2017 at 5:00am — No Comments