Here is another question I have about being able to calculate this scenario in Access, or even at all for that matter:
I have a query that find the TOP 5 items sold in a given timeframe, and it groups by site. I use this to create a comparative chart between the site for ppt presentations. I do a lot of these but I have a problem with the presentation that I foresee they will have a problem with and it makes for bad metrics:
Some stores are bigger than others, and get much more supply. So a straight aggregate total of just qty of toping selling items, and comparing the locations is stacking the deck a little.
So if Site A gets 80% of the supply, and sells 500, Site B gets 15% supply and sell 75, and site C get 5% supply and sells 50 items, then Site C actually has the best sales for their size. I have exactly what I need in terms in the first chart (from my queries and such) to show the aggregate total, but what do I need to represent the idea mentioned above.
The factors that I have that go into this are:
ItemID - group by
Item - group by
qty sold - sum/descending (which is the variable that determines the Top 5)
Store/Location - Group By
and then I run a seperate query to get the total deliveries (supply) to each site
I realize that this may just be a lack of mathmatical understanding on my part, but can anyone help with this?
thanks
The first issue that I see isn't about SQL savvy; it's how to serve your data customer. What does he or she want to see? Metrics is a term with a holy ring, and for good reason: it's supposed to be what is used for the big business decisions, and it's scary easy to measure the wrong thing.
So I'd make sure I know what my customer wants. If you can't model it on a spreadsheet, you won't be able to develop your reporting effectively.
Every deck of cards is loaded. You have to know how they want it loaded.
Related
I know how many customers of each customer-size group each sales representative handles on an annual basis. Is it possible to calculate the likely time/effort required by each customer size based on this data set? Or said differently, I'm trying to find out if larger customers require more or less effort than smaller customers.
Is there a function or formula in Excel that will allow be to answer the above based on the data set below?
To add some context, in case it is helpful. There are 2080 work hours a year. I'm assuming they spend all their time with the customers under their responsibility. I also expect that the largest customers require more time than a small customers, but I dont know how much more. That is what I'm trying to figure out. Some employees do handle a lot more customers than others, so its probably best to look a the relative difference between the customer sizes for each employee...
Customer size is rated from 0 (very small) to 7 (the largest).
Below is a small data extract of a large Data table
we run an eCommerce store and constantly create & test new Facebook Ads. Now I am looking for a good way to create a scoring for these ads. Basically it is a very simple problem, but I can't get my head around it.
For each Facebook Ad, I have this data:
Budget Spent
Impressions
Clicks
Product Page Visited
Purchases
The most important event obviously is the purchase. So in a perfect world with huge amount of data per ad I would simply calculate the cost per purchase (= Budget Spent / Purchases) and know, which is my best ad. But here comes the problem..
On each ad we don't have much data. So let's say we have:
AD 1
50€ Budget Spent
10.000 Impressions
200 Clicks
50 Product Page Visits
2 Purchases
= 25€ per purchase
AD 2
50€ Budget Spent
10.000 Impressions
400 Clicks
130 Product Page Visits
1 Purchases
= 50€ per purchase
Simply based on the cost per purchase, I would choose AD1. But when I am looking at the data of the previous steps (clicks and product-page-visits), AD2 looks more promising.
How can I create a score value, that tells me which ad will likely generate the better cost per purchase in the long run, considering also the values of the previous steps?
That score value should take into account the data of the previous steps. So if we have less purchase-data, it should strongly rely on the previous data and if we have much purchase-data, it should rely less on previous data (and more on the actual cost per purchase).
I think of something like:
Use the click-rate as the base score (because we have much data for this)
then modify that score with the values of the following steps but in a weighted-way. So the more data we have on the following steps, the more the score moves toward that values.
Thanks in advance for your help!
Best Regards
Patrick
Heres the situation,
I've begun managing money for a handful of people in crypto markets. Each have a different sized account. Right now I am managing all of them individually, its a problem because its not scaleable and is time intensive.
So my question is how can I create something in google sheets to keep track of investor holdings in an overall fund? say there's 10 investors, each with $10,000. Each have 10%. But then a new investor comes in with 5%. How can I program this into an excel sheet?
Totally stuck. I need to be able to add/remove people, and adjust the total assets, holdings per person.
Running into a wall, and crypto forums are just exploding with activity. help.
Add a time variable (eg NumberOfDaysInvested) and multiply it by percentage each investor had originally up until new investors join in. That's a more fair way to divide the profits.
However, it still remains a problem that new investors can partake in profits obtained earlier - ie after just being an investor for 1+ days you will gain access to profits made by earlier investors.
I would suggest to look into dividing investors into funds and pools to separate them but still introduce the time variable. It will reduce overall work on your side and will be more fair.
I work for a hospital that is part of a larger network. We were recently asked by our corporate overlords to address the use of a specific laboratory test. in general, this test should only be performed daily, which should be considered to corresponded to a 24 hour period from last draw. sometimes, however, based on when people arrive to the hospital (e.g. 7pm), and in the interest of bundling labs for a single draw, they may be drawn sooner to coincide with routine testing i.e. 5am. it would never be necessary to otherwise need to repeat within a short (8 hour) window, particularly on the same day.
we have been asked to validate to see if we are adhering to this general practice, as testing any more frequent than that, say, within 12h of a previous test, has no real clinical value and thus adds unnecessary cost.
To address this issue I was given a dataset that among other items includes all instances the lab was performed including collection date and time.
please see HIPPA-safe example below (to be clear, no real data and identifiers are not real); the actual dataset has over 4,174 entries corresponding to 1,328 unique persons. everyone had at least one test performed, not everyone had >1.
I THINK what I want to do is an IF formula that reads the antecedent cell to 1) check if same person and 2) if so, perform a subtraction of the time stamp to display the relevant difference in time, which I can then filter, create histogram, etc. does this seem like a reasonable approach? is there a more preferable method to facilitate analysis? do any other forms of analysis come to mind?
=IF(B2=B1, D2-D1, "n/a")
example data set with formula:
any other forms of analysis come to mind?
By the looks of it you should consider taking the values under "Results" into account, assuming there is a band that might be considered 'normal' readings. The "one in 24 hours is sufficient" rule of thumb may well be appropriate for a series of values within the 'normal' band but not so much so if readings are close to 'danger level'.
That is, in some cases a higher than 'standard' frequency of monitoring may be in the patient's interest, even if not hospital policy, so it may be worth separating the "less than 24 hours interval" readings into those where the higher frequency provided information of little value (eg readings remaining within a 'normal' band) from any that crossed into or out of the band and/or large changes in value. This though may be more a matter of statistical analysis than programming and depend upon whether any action might be taken as a result of such "extra" readings.
Morning guys,
I'm hoping that one (or more) of you can help me.
I have been tasked with creating a dashboard which needs to display trends and have a dynamic frontsheet, preferably with drop-down or data forms so as to update a chart / graph.
The information itself is incredibly limited - the scope of the document is tracking a value (0-4) assigned to a staff member's ability to fulfill a task, e.g. 'Quotes - 4', 'Cancellation - 2' and so on. So the metrics are limited to:
Month (a worksheet for each month of the year and one front for the dashboard)
Team (Presently 6 teams, but this is likely to increase over time, so hopefully the solution facilitates relatively easy incorporation of new teams)
Employee (Self explanatory)
Task (Presently 25, but as above - subject to change)
Score (the 0-4 value referred to above)
So as you can see, it's a very simple dataset. The sheets are presently set out with six grids with data validation lists for determining Team and Score (dropdowns for easy data input), with the Task being pre-written and the employee entered manually by the user.
What I'm hoping to do is have a frontsheet with dynamic tables that update accordingly when a dropdown and/or data form is changed. The key focus is on getting the staff members up to 4s for all tasks, so ultimately, the charts will display trends for the individual teams (one chart for each team - 6 charts) on a month-on-month basis and also a dynamic table which can reflect specific information (e.g. employee performance on a specific month, or number of '3s' achieved by a specific team to date).
I've read a reasonable amount on this, but seem to have overwhelmed myself with the sheer amount of options. However, the options can be narrowed given that I'm working on a large corporate network that doesn't really facilitate downloads (so add-ins or anything extraneous to Excel 2007 'out-the-box' isn't an option) and preferably without the use of VBA (1. I'm quite a novice insofar as VBA, 2. Easy distribution and maintainence of the document might be marred by VBA?), though I appreciate that my requirements may dictate VBA to be essential.
Does anyone have any suggestions around how best to proceed creation of this dashboard?
Any and all help is appreciated and I apologise as a newbie if I've contravened any conventions around forum etiquette.
Thank you all for your time,
Rob
There are a couple of things that you need to consider in a task such as this:
a) what sort of output do you require?
b) how are you going to manage the data?
For a) I'd separate it further into the basics of what's required (time series charts of employee and/or team performances [how will team performance be measured? average, % achieving 4, or ?]) and then the bells and whistles of drop-downs. Focus on the basics, the other stuff first the whizzy stuff can come later. Getting b) right is vital - you are going to be extracting subsets of the data to build the charts you want to display. Get b) wrong and you'll just create a horrible task for yourself.
In your position I would consider re-organising the data into the form of a table. Excel's help defines what is meant by a table, but in essence it is a list of your observations where each observation simply comprises the score for a particular month/team/employee/task combination (so each observation comprises 5 values). The observations are arranged as successive rows of the table with the first row being the header row which will contain suitable labels such as "Month", "Team", "Employee", "Task", "Score". The real advantage of using a table such as this is that Excel provides a heap of in-built facilities for manipulating them - look up the help for Sort and Filter on the Data tab. In your case there is an even more compelling reason for using a table - you can use the Pivot Table and Pivot Chart facilities for analysing and displaying the data. If you have not used these before some time and effort spent learning about them will pay dividends. Once your data is organised and you know how to use Pivot Tables and Charts you should be able to prototype sum output very quickly.
If you do decide to organise your data as a table you can still keep a nice friendly looking grid of 6 team "tables" (different from Excel's use of the word) as a data entry facility to enter each month's scores by employee and task. You will need to find a way of getting each month's data from the data entry "tables" to the main data table. (Easiest way would be to use a bit of spare worksheet under the data entry tables to reproduce the entered data as a series of observation rows and then use Paste Special Values to append these rows to the end of the main table of observations. You can use VBA to automate the copy/paste operation if you want, you just need to figure out a way of identifying how may observations are currently in the main table and precisely where you want the paste to end up - COUNT() or COUNTA() is a useful friend here). Main problem to avoid (whether automated or not) is to avoid appending same entered data more than once to main data table.
Have a look at http://www.mediafire.com/download/x64swkp689k10a1/DataEntrytoTable.xlsx for a simple example of some of the above thoughts