How to make Smarter Decisions by Using Info Explorer

Watch how power users sort, filter, and drill into their cubes to get at anomalies in the data and make more strategic sales decisions. (start webinar at 12:51)

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Video Transcript:

“So, as you’re setting up a lot of these different types of transactions within the system, we have a tool we call Info Explorer that allows you to manage the information and all the transaction data that goes through all of the various companies that you’re managing. And in many cases, clients have asked for custom Crystal reports to be able to manage the data more effectively within their organization. But what happens is, over time, you end up getting multiple requests for custom Crystal reports. And one of the ways to handle that more efficiently is to use a tool like Info Explorer that gives you multi-dimensional analysis capability, including the option to dashboard the information in a graphical format.

Some of the things that you can do within Info Explorer is use multiple dimensions to change the format of the data. If we take a look at something like sales order processing- for those of you that use either AR or Order Entry extensively, you can end up with a number of sales transactions going through the system. And you’ll know that many times, you’ve got information that different people are using, but for different purposes. So the format that they wanna see it in changes. In the case of a simple sales example, where I’m looking at my net sales by item, somebody might come along and say, “I’d like to see this information as customer sales by item.” In Crystal, or Excel, you need to create another template. Within Info Explorer, I simply drag the customer dimension down into the cube, and now I’ve got my customer sales by item.
There’s other tools, such as ranking capability or formula capability that you can use within the system. So we can calculate margin percentages using formulas. We have minimum-maximum capability, ranking capability, sum, or discounting the number of records. And then, we can also edit styles to create dashboarding within the cubes to spot anomalies in the data. And the nice thing about all that technology or online analytical processing, which is what Info Explorer supports, is that the sales ranking that we had initially, if I move the customer dimension back up into the cube, initially, we were ranking item sales by themselves. So we have a rank from 1, and it’s descending. When I introduce a new dimension customer number, notice what happens with the sales ranking. It now ranks the data based on the perspective that I’m looking at. So, it’s not just item sales, it’s now customer sales by item. So it’s ranking the customers within each item. So I’ve got a #1 sales customer ranking for item for item ‘florescent desk lamp,’ and I’ve got a #1 customer ranking within ‘halogen desk lamp.’ So, that’s more of the power of OLAP, is that as I change these dimensions around, my calculations within the cubes will change based on the perspective of the data.
So, you’ve got your customer sales by item. And then somebody decides, “Hey, you know what? I actually want to see the data slightly differently. I want to see item sales by customer, as opposed to customer sales by item.” Well, how do we do that? Again, with Crystal, you’ve got to modify the template and create another custom Crystal report. But in Info Explorer, all you do is grab the customer dimension and move it to the left of the item dimension, and now you’ve got your net sales for each item by customer. And again, we’ve changed the ranking. We’re now ranking item sales by customer, as opposed to customer sales by item.

So, this is a very, very simple example of how you can use Info Explorer to quickly and easily identify anomalies in the data, or trends in the data, or do a quick analysis of how you’re doing based on the dimensions that you have within the cube. So, if you just wanted to add margin percentage very quickly into the cube, you just drop that down, and now you can see not only how you’re doing in terms of raw sales data, but, if it’s profitable sales that you’re making with these customers.
The last thing I’ll show, in closing, before we pass it over to Mark, is filtering the data. So, within this aged listing of your AP invoices, there’s a couple more things I’ll show quickly in closing. We’ve seen how we can format the data based on moving dimensions around in the cubes, but also, filtering is another capability within the system. I’m looking at APO standing transactions here, and I do have the ability, using this little magnifying glass, to simply eliminate rows of data by unchecking the boxes, and it will remove those. And you know that you’re filtering a dimension, because the title goes to italics.
Now, that’s a very rudimentary method of filtering data. A more powerful method would be to right-click on the dimension and use what we call the pre-filter. The pre-filter allows you to choose any dimension within the cube and add parameters for filtering that particular dimension. So, if I took something like amount due, and I said, “I wanna see just amounts due that are greater than or equal to-” and you enter a value, let’s say $500, and hit enter. It immediately filters that Q based on that dimension, and the parameter ‘amount due greater than $500.’ And if I like that view because it’s the significant outstanding payables, then I can take a copy of that by simply saying ‘copy view,’ and Info Explorer copies that filtered view, and then I can right-click to rename it to more aptly describe what I’m looking at. So now I’m looking at AP outstanding greater than $500. And I keep that view as a new report on my desktop. I go back to my original AP outstanding transactions and remove the filter. So I’ve got one that lists all of the AP outstanding invoices, and I’ve maintained my filtered view as well. And then, if I wanted to graph that, I would go up and create a new chart for that. And I have different charting formats that I can use to show bar charts, pie charts, and other types of charts within the system. Okay?
And the last thing is the Drill through capability. It’s one thing to be able to collapse rows and columns within the cube to summarize by total and then break that up so I can have totals by vendor or break it up into individual line details. But what if I wanna see the transaction as it was originally entered within Sage 300? Well, I can simply right click and Drill through the cube right back into Sage 300 if I’m connected to the database. Okay? So I can see the perspective of the data from a transactional viewpoint, as opposed to just summarize within a cube.
There are several other tools that we could talk about, but given that we’re just trying to highlight some of the new tools that are available for you, we wanted to take the opportunity to do that for you today. So, thanks very much for your time and attention on that.

(Demonstration by Robert Lavery, Robert Lavery & Associates)