This presentation in to enlighten students about the resources and material they should use to identify their research question. It also highlights to students the performance assessment tasks that they need to do and produce.
Please click on the link below:
Below is a link for a Performance Assessment for “Analytics for Healthcare Professionals”. Please click on the link below.
Medical Education Performance Assessment for Analytics for Healthcare Professionals
Here’s a visual display of who I am:Carol Anne Hargreaves Profile
What is all the fuss about Big Data? Everyone is talking about Big Data, Hadoop, Map Reduce, etc
Let me tell you, you can have all the data in the world at your finger tips but it doesn’t mean anything, if all you do is store it. And, that is a costly affair and a big waste of time, money and lost opportunities of owning a gold mine!
There are many examples, of use cases, how many businesses have used their data to make decisions faster (almost real time), smarter (not gut feel, but listening to the data & what it is telling you) and timely (data also has a use by date)!
Using statistical techniques, we are able to run algorithms that identify patterns in the huge data sets. These patterns help businesses identify insights that allow for smarter, faster, timely decisions!. For example, Google used search terms by region in the United States to predict flu outbreaks faster than was possible using hospital data.
Other examples, using sensor data from ships, you are able to build statistical models that will predict more accurately when a ship needs to be serviced or repaired at the right time (instead of calendar days) based on the engine (heat, vibration, sounds, age, engine type, number of gears, gear type, distance travelled, average speed, etc). Statistical models can identify which ships will need to serviced, together with the probability of the engine failing. Using this information, Big Data Analytics will save the business lots of money as the service will be cheaper than actually repairing the ship engine once it fails. By preventing a ship from breaking down, Big Data Analytics will save the business millions of dollars as there will be less delay (repair time is longer and more costly than service time) in doing business as usual. A shipping business can reduce total repair time and reduce costs of repair.
Building a business intelligence system is the first step in better understanding Big Data. A business intelligence system is typically, a dashboard which displays bar charts, pie charts, trend plots, and these days are highly interactive and can tell a story in a few minutes. Data Visualization is key! It is your starting point to understanding key variables and metrics related to your business profitability and Return on Investment. One thing, whatever you decide to have on your dashboard, make sure it delivers actionable insights. Which means if the “traffic light system is red, the business user needs to know what to do versus if the traffic light system is green”. Many businesses are developing creative ways in visualizing their data and are making it much easier for the user to see and understand the patterns instead of complex model outputs and formulas.
Big Data Analytics can also help transport related organisations where the next accident is likely to take place and the probability of the accident occurring. This is very useful, as the police, ambulance, fire brigade, re-routing systems can all proactively make decisions based on the information provided by Big Data Analytics. The result being the police, fire brigade, ambulance, etc can strategically position themselves so that they are more likely to be at the right place, at the right time, so that the incident is cleared quicker, the patients are transported more quickly to the hospital and the traffic jam is cleared more quickly. The amount of money that is saved by using Big Data Analytics is massive. The amount of lives that can be saved, because of the use of Big Data Analytics is also big.
So, I can go on and on sharing many examples but I guess the question that needs to be answered is “Where do you start?”
I recommend taking an agile approach. Start with a business problem, one whose solution is achieveable in a reasonable space of time. Start small, “like a baby just born and take baby steps, with your mother (someone with experience and the expertise, who knows better) to help you along the way. Yes, you may fall as you take your first steps, everyone falls, it is okay. Get up and soon you will be waling confidently, and then running and enjoying the data mining. Like mining gold as you see the benefits reap!
Please let me know if you have any questions on Big Data Analytics….its not easy to cover everything here!
Supply chain analytics helps you to better understand your business processes end to end. Many organisations in the supply chain industry have lots of data but are not making good use of it. By applying statistical techniques and analysing your data you can certainly make better decisions based on what has happened in the past, and based on what is currently happening, and based on what is likely to happen in the future.
By drawing a diagram that footprints your process from the raw ingredient selection – to the distribution to the machine at the manufacturing factory – to the employee working at the machine – to the quality test – to distribution to the inventory warehouse – distribution to the retail store – to the back office – shelf- teller – transport – customer. Easily more than 10 processes.
As a start, visualization is the best starting point. Simple plots such as bar charts, trend charts, box plots and pie charts of the average time, minimum time, maximum time, standard deviation, time between events, can easily help businesses better understand what has happened.
But the power of supply chain analytics is in what is likely to happen. Knowing this, gives a business the power and time to be proactive and innovatively decide on what to do, based on the forecasts, This will give your business an advantage to differentiate itself from its competition and thereby gain a competitive advantage.
Forecasting models can easily be automated using statistical modelling techniques and deploying these models into the business operations. But it is important that once these forecasting models are deployed in the operating system, they should be monitored and over time, alerts should also be placed in the operating system when there is a change in the direction of the activity or when the quality of a product is below required standards, the machine operator should be alerted.
It is important that operational analytics are shared among all the stakeholders and departments so that all parties have almost real time information and this will allow the whole company to make proactive decisions always using the latest information. This means that better decisions will be made as they are based on the latest data which is the most accurate information.
Supply chain forecasts also allow a business to plan more effectively. Once the forecasting models are built, what if scenarios may be used to compare and adjust the forecasts based on your business goals and constraints.
Using real time insights businesses will be alerted to when they are overstocking or under-stocking, and thereby help businesses to make adjustments early and avoid loss in sales. These overstocking and under-stocking insights can contribute to tremendous savings for the business, which means increased return on investment. And, that is usually the goal of the business…increased return on investments!
Not sure, if I have convinced you enough that measuring and analysing your supply chain data helps you to make decisions faster, smarter and at the right time. Timing is the essence and the key to improving your supply chain operations.
Of course, there is much more that I can discuss here. But, please let me know if you have any questions.
Analytics for Business 