People will need to take a number of precautions to reduce the chances of them getting ill. It is quite likely that additional (hopefully shorter) lockdown periods may be necessary to keep the infection rate under control.  

However, at some point, it is hoped that scientists will work out a vaccine that can be used to give the majority of people immunity to the virus.  Once this is in place and a mass vaccination process has given the general public herd immunity, people will be able to return to ways of behaviour more in line with what was seen before the pandemic struck.  Unfortunately, experts estimate that a vaccine is likely to take 12 to 18 months to develop even with a fast track approach.  So we should expect that this second phase will not occur for quite some time.  

There are undoubtedly going to be changes in the way people behave once lockdown is over.  In a word, we’re going to become more reclusive.  After 2 months of avoiding contact with others, it’s going to be ingrained in our subconscious behaviour patterns.  This will be reinforced by government mandates requiring people to avoid too much contact as a way to mitigate further surges in infections.

You may want to consider getting a background green screen so that you can limit how much of your home colleagues and clients get to see!  Many of the video conferencing products allow you to replace your actual background with a virtual background.  This works well if you have a solid background colour.  The software cannot handle a mixed background colour.  These can be purchased online or made by hanging a green sheet behind you.  

You cannot work on your bed or the lounge floor for the next 6 months, so if you have been working like this in the hope this work from home phase will soon end, I suggest that you get a desk that is large enough to work on comfortably.

Travel will be curtailed
We can also expect travel both via public transportation and air to be something people consider much more carefully.  The practice of popping on a flight from one city to another for a 2-hour meeting will become a much rarer phenomenon.  Companies may be more inclined to postpone or cancel large company events, including internal meetings, conferences and parties.  You can expect the end of year event to be subdued and local!  

The coming months are likely to be tough for many businesses though we believe that for many economies, there’ll be a rapid improvement once the lockdown restrictions are reduced.  For those businesses that manage to survive the lockdown and get through those first few months when the impact on the economy is likely to mean continued famine, the land of plenty could well beckon since the lean times will have thinned the competitive herd.  The companies and individuals that will do best will be those that adapt to the new realities.  The time to start thinking about how you will do so is now. 

Maybe go for a run, call some friends you haven't spoken to in a while, clear out your old clothes for charity or sharpen up your skills.  And Udemy is the ideal platform for this with a wide range of topics you could upskill yourself on. 

To make upskilling yourself even easier, we have discounted our entire course range for the next 30 days with discounts of over 75% across the board.  Feel free to share this post with friends or colleagues who might be stuck with little to do. 

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Until next time - keep safe!
Ian and Scott
* Brian Tracy is an American-Canadian motivational speaker and author of several self-improvement books.

What we have found though is that the data WHO provide does have some anomalies.  For example, we found cases where the total number of deceased in some countries would drop which is literally a miracle.  Digging into these, we found that most of the anomalies have an explanation of some sort. (eg Some deaths were incorrectly attributed to Covid-19 and this was later corrected.)  As a result, we decided that a few anomalies found in the inevitable chaos that dealing with a rapidly spreading disease introduces was acceptable. 

Once we found a source of data we were happy with, the next problem was getting this into a usable format.  The daily situational reports from WHO are published as PDF documents.  We had to take these and somehow get them into a data format.  This involved converting the PDF to Microsoft Word format and then copying the data from Word to Microsoft Excel. 

However, we still had more to do.  The way the situation reports gave data was not ideal.  For example, the number of cases and new cases were given in one field with the new cases shown as a bracketed number next to the total cases.  We needed to split out the new cases from the total cases and have these as 2 separate fields.

We now have an automated process where we simply past the data from the daily situation reports, and refresh our Excel data source.  This process takes around 5 minutes which is manageable. 

Having found a way to get solid data in a usable format, we were able to build a visualisation using Power BI.  We can now update our visualisation with the new data on a daily basis and it's available for public consumption.  We published the dashboard to the Power BI server for access by anyone who wants to view it.  We've published the actual visualisation in it's own dedicated blog post click HERE to see it.  Our plan is to keep this updated as new data comes in. 

We hope you find this interesting. 

That's all for now...
Scott (and big thanks to Ian for all his hard work in making this visualisation happen!)

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The fourth video in my "Complete Introduction to" series focuses on Excel Power Pivot.  Power Pivot is another incredibly powerful feature within Excel.  It was first introduced to Excel in 2010 as an add-in, which was freely available to all Excel 2010 users.  In Excel 2013 Microsoft integrated Power Pivot into Excel, but sadly created separate licencing for the product so now you require a Pro Plus license to access it.

One of the most common challenges that faces Excel users is having two separate sets of data that need to be referenced for reporting purposes.

In this video I show you how to use Power BI to create a relationship between two spreadsheets in order to create a report using information from both.

The ability to manage and use data in an effective and efficient manner has become critical to the continued viability and success of most businesses. Data is the key resource to informing decision making. It can be argued that data has become as important as cash when it comes to running a sustainable and profitable business in today's complex and uncertain business environment.

So why is it that so few businesses have a strategy and plan for the training and skills development of their knowledge workers to develop data expertise and capability? Many of today's knowledge workers spend countless hours working with data using obsolete technologies and techniques. I am continually amazed to see how many businesses are still running old style Excel spreadsheets with quadrillions of formulas in a multitude of sheets that nobody understands. A lot of business are running a lot of its processes through spreadsheets, and ;ets not kid ourselves, this a potentially very dangerous situation!

Its probably fair to say that a lot of businesses are basically running on Microsoft Excel.

So my question to them is how many staff members have been properly trained to use the full Excel suite, including Pivot Tables, Power Query, Power Pivot and Microsoft Power BI?  We can even go a step backwards and ask how many businesses have trained their staff on the basics of data and visual analysis?

My own anecdotal evidence from having trained thousands of people in the past 15 years is that not many people have received proper training in these technologies and techniques. I normally find that people have a basic understanding of Pivot Tables, which they either learnt from the person sitting next to them or as part of a course they did which just touched on them, and have little or no knowledge of Power Query, Power Pivot and Power BI.

The reality is that data is useless unless it's transformed into information. I often see CEOs complaining that their companies are data rich, but information poor.

So what should businesses do? I would recommend that the people who are knowledge workers and regularly work with data should be identified and then trained in this field to improve their skills and capabilities. We have proven that by simply changing the way you use Excel, you can become 80% more productive in 20% of the time. 

People who are trained to analyze data and that can ask meaningful questions of data are invaluable to any business who wants to make good business decisions that are driven by all the data they already have.  These people are able to:

• work with all the different Microsoft technologies such as Excel Pivot Tables, Power Pivot, Power Query and Power BI
• understand the basics of data analysis - know different forms of analysis such as Key Metrics, Comparison, Trend, Ranking, Variance, Contribution and Frequency
• know how and when to effectively use visual analysis. Visual analysis can be extremely powerful for understanding patterns and relationship within data. But, far too often people use the wrong type of visual analysis for the type of data they are trying to understand.

So in summary, data is useless without the people who have the right skills to understand how to work with it and businesses should therefore focus first on ensuring their people have the right skills and training to work with data before attempting to make data driven decisions.

Every year, Gartner releases their annual Magic Quadrant for Analytics and Business Intelligence platforms.  In the report, they evaluate the strengths & weaknesses of the main service providers in the marketplace as well as providing a graph plotting these providers based on their ability to execute and their completeness of vision.
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For the past 12 years, Microsoft has been slowly moving higher, but since 2016, the movement has been significant, with them being one of the leaders for the past 3 years and now pulling ahead to take the lead in 2019.

The next types of analysis I'm going to focus on are Key Metrics and Ranking Analysis.

Key Metrics
Key metrics displays one key piece of information prominently (examples include total sales, total profit or total number of customers) and by using ratios you can get deeper insight and more information from your key metrics.  For example we could create key metrics for displaying the profit ratio (which is the total profit divided by total sales) where the  profit ratio is displayed as a percentage, this makes it easier to see what portion of your sales is profit.

Another ratio that can be calculated is the average sale per customer or the average profit per customer.  In this case you would divide the total sales by the number of customers and the total profit by the number of customers, so by using three key metrics you have now created three new key metrics using ratios which gives further insight into your data.

Ranking Analysis
Ranking analysis is about understanding the top/bottom values within a range.  The simplest form of ranking is to do a sort from highest to lowest or lowest to highest but there are many more rankings that can be done.

Top 10 or bottom 10 is one of the common method of analysis to highlight the items that are contributing the highest or lowest within your data set.  Filtering your items to only show the top 5, 10 or 20 makes it easier for you or your audience to view the most important items in a table, rather than displaying a long list of items.  A top 10 or bottom 10 analysis can also be combined with your column or bar graphs to restrict the number of items that are displayed in the graph.
You can also use a top/bottom percentage filter, in other words limiting the list of items to the top 20% or bottom 20% and this again easily allows your audience to focus in on the key values within the data set.

Regardless of what job you do, you will regularly make decisions, and in order to make these decisions, you need data.  Data surrounds us and, whether we know it or not, data informs our decisions so being able to analyse data means being able to make better decisions.

As technology has progressed, it's become easier to put systems in place to handle data, but it's also increased the amount of data we have available to us so we're constantly looking for easier ways to see the story behind the data.  The introduction of computerised spreadsheets was a big moment in data analysis because suddenly anyone could input information, run a formula or create a graph and find an answer and as these tools have progressed, the access to information has exploded!  

As a trainer and consultant, I've chosen to focus on data analysis and using Excel and Power BI in order to analyse data.  I spend a lot of time teaching people how to use these tools but I also spend time teaching different forms of data analysis because what a lot of people don't realise is that knowing WHAT questions to ask is as important, if not more important, than being able to put together an impressive dashboard. 

The two most basic forms of data analysis are comparison analysis and trend analysis so I'm going to start with them.

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Comparison Analysis

A comparisons shows you things like what items sells the most or which product is not doing well.  You can compare different months or regions to see where the biggest profit or lowest turnover is, you can also see how much of a difference there is between different products or time periods.  Tables are the simplest way to do a comparison analysis, or if you'd like to visualise it then a column or bar graph is best.  A pie chart is useful if you're only comparing two or three items but should be avoided for more than this. 

The column or bar provide a good indication of how large or small an item is in proportion to the other items that are being displayed.  If there are a large number of items in the graph then a bar graph is a better option as the labels are displayed horizontally and are easy to read.

Trend Analysis

Trend analysis is about understanding how data changes over time.  Trends can be understood by many different time dimensions such as year, quarter, month, day of the month, day of the week, week number, hour and second.
Understanding your data over different time periods will provide important insight into whether things are moving up, down, staying stable or is volatile.  The analysis of different time periods allows you ask a variety of important questions such as:

1. What time of year do we make the most sales?
2. Are there certain days in the month that we are more busy?  Are the first 10 days of the month more busy than the last 10 days?
3. Do we have busier times of the day, do we make more sales in the morning or the afternoon?

Each of these questions will give you insight that will allow you to make decisions on staff schedules to ensure you don't have staff sitting idle or irate customers because there are not enough staff to assist.
 
When working with trends you should use a line graph or area graph.  The line graph will provide a good understanding of the general trend over time.  A trend line is often added to the line graph and provides a good visual indicator of the trend.
An area graph is a good option for when you want to include a comparison and see how it is trending.  For example an item could start off small, but grow over time, an area graph is a good method to display this information.