Let’s look at two concepts, information and knowledge. Information refers to ideas, operations, numbers, facts, groups of facts etc. From schools to the corporate world, when someone doesn’t know something a teacher or corporate trainer provides instruction to help the person acquire the information.
If we examine all of the information a teacher hopes to impart, we can group it into a skill area. Skill areas might include reading, computer literacy, mathematics, leadership, or history. After taking all of the information in a skill area knowledge emerges.
Knowledge, then, bestows one of the greatest powers a person, or people, can have. If a person can’t read, he or she has very limited job options. Or if a person doesn’t know about biology and germ theory, sicknesses and deaths will sharply rise. And if people don’t know history, they have no way of learning from mistakes of the past (think about political scandals, wars, or people like Bernie Madoff who ran the most heinous Ponzi scheme ever).
We probably do not have to work hard to sell you on the genuine power of knowledge. But if you haven’t had much experience with Chartlytics and the base of power we draw from (i.e., Precision Teaching, Standard Celeration Charting), then you may not know how much knowledge you have missed out on.
At Chartlytics we offer a method for applying the science of measurement and data monitoring to any target piece of information, skill, or behavior. The process vetted through research and many strikingly similar approaches incorporates the following method:
Pinpoint behavior with the utmost precision.
Record pinpointed behavior with the most sensitive metrics available to humankind.
Change the program or instruction if Standard Celeration Charted data and subsequent metrics indicate learning has not taken place or not occurred fast enough.
Try Again if the learner has not made progress, use special procedures to help the learner succeed and reach his or her potential.
The above cycle yields precise, enlightening data (the kind of precise data that occurs in other natural science fields like Physics). When taken together as a body of information, the chart reader obtains hard won knowledge. Chartlytics helps generate such hallowed knowledge vital to performance change through metrics and analytics.
Metrics and Analytics
A metric refers to a standard of measurement. Metrics begin with counting, timing, or tracking data. The metric then sums the data or places it into a ratio. As an example, web metrics have a thing called a clickthrough rate or CTR. A CTR counts how many clicks a web ad receives and divides that number by how times a website shows the ad. Think about CTR the next time you click on an ad with your favorite celebrity drinking milk, big data has its eyes on you!
Chartlytics focuses on three big time behavior metrics for directly measuring behavior: frequency or rate (the king of all metrics), duration, and latency.
As an example, a teacher might count the number of math problems answered in one minute. The count, say 18 correct digits written and 3 incorrect digits written over one minute, provides a frequency. The frequency comes to 18 correct and 3 incorrect digits written per minute.
If the teacher took each daily frequency and placed the data on a daily Standard Celeration Chart (SCC) a new metric merges - celeration. Celeration tell us how fast the pinpointed behavior changes. In the figure below see how each frequency comes together to form a new metric.
Chartltyics presently offers the following metrics: Accuracy pair, Accuracy ratio, Celeration, Bounce or Variability (Three total metrics - Total Bounce, Up Bounce, Down Bounce), Outliers, Accuracy Improvement Measure (A.I.M.), Frequency Multipliers (aka Frequency jumps), Celeration Multipliers (aka Celeration turns), Bounce Change, and A.I.M. change. All of the previously mentioned metrics helps us see the targeted behavior in the right light. Namely, such precision metrics provide a level of information dramatically superior to typical nonstandard linear graphs (NSLG) and their reliance on using words instead of metrics (e.g., describing trend as moderately increasing, describing variability as highly variable). Would you rather have words or numbers to detail your data?
An analytic uses metrics to produce insight, prediction, and a deeper understanding of the data. In other words, the process of using data relationships to improve decision making and obtain new understanding of behavior falls in the domain of analytic.
An analytic from Chartlytics answers the questions, “Did an instructional program lead to better work productivity” or “What intervention program best helped my student learn to read?” Large scale analytics show what programs work best to rapidly teach student complex math and how many change interventions does it take to turn around struggling students.
As we describe the Chartlytics suite in greater detail, we will move into explaining the Manager’s Dashboard and the Supervisor’s Dashboard. But for now, know that both informative metrics and forward looking analytics help Managers and Supervisors see patterns and the big picture of the targeted behavior.
In fact, at Chartlytics we believe if you can find another web app or paper-driven system that has better metrics and analytics, you should leave us for them! We have one main goal, helping all performers reach their latent potential as efficiently as possible. If someone out there can help someone more quickly, humanely, and significantly than Chartlytics, as applied scientists and committed performance engineers we feel you and your performers deserve such a system.
And yet, we have found no method or procedure equal to the Chartlytics system. Based on the power of the science of measurement and optimized decision making, performance information becomes performance knowledge.
Metrics and analytics lead to knowledge
The following graphic depicts a reality everyone must closely examine for developing true knowledge: the past, present, and future.
Time’s arrow, or the arrow of time, came about in 1927 created by the British astronomer Arthur Eddington. Eddington put forth that everything travels one way. Therefore, making decisions directly relate to the quality of information one has. Precision metrics summarize, quantify, and qualify the past. The better the data, the more penetrating analysis one has in the present. And with such high value analytics at hand, projections and planning for the future promote sound judgement and quality navigation.
Poor decision based on low resolution nonstandard linear graphs (NSLG) and crude metrics cost business organizations millions of dollars, waste time and resources, and result in the loss of a competitive advantage. When applied to learning at the school level, poor decision can have truly devastating effects. Students do not learn to read well or at all, mathematics becomes a mystery instead of a joy, and science no longer inspires wonder but becomes a subject to avoid.
We make a decision and take action. Basing judgements and analysis on high-quality data, as opposed to personal intuition and low-quality data, engenders superior decision making and performance excellence.