Welcome to DataSelf Analytics; the solution selected by leading ERP vendors for their own business’ analytical needs. Consider the following questions:
● Have you ever had to write-off bad debt – or had cash flow issues – because you couldn’t easily see what was coming due (or past due) from your clients?
● Have you ever been unable to fulfill an order because you were unaware that your stock was running low?
● Do you wish you had instant visibility into your company’s P&L numbers?
● Have you ever been surprised to learn that a top-performing product or salesrep has taken a sudden downturn?
● Would you like a way to leverage the statistics of past business activities and turn them into insightful – and accurate – future forecasts?
DataSelf’s “1-2-3 Advantage” lets your organization make more-informed business decisions by:
1. Transforming your data via our revolutionary ETL+ (for greater analytical insight)
2. Leveraging the industry’s best-of-breed analytics technologies (Tableau, Power BI)
3. Providing the greatest selection of “Insight-Forward” reports & dashboards (8,000+)
So . . . let’s get started . . . with a sample ERP environment pre-loaded with DataSelf’s most popular reports and dashboards. Go to: https://bi1.dataself.com/t/demo/views/DataSelfAnalyticsv2201/Home
Three Ways to Get Critical Insight from your ERP Data
1) Stay on Top of Sales Growth & Decline Knowing whether your business is growing (or not!), how you’re doing this year, quarter, or month versus last year, where you should focus your efforts (and where you shouldn’t) is crucial to your success.
● Click on the ‘YOY Variances’ button or tab. Like most DataSelf dashboards, the goal is to provide you with superior insight from the highest (macro) level to the (micro) lowest-level details.
● Let’s begin by selecting (on the far-right of your window) the specific time period you want to focus on.It currently shows Fiscal Year 2020, select months 1-9, and click on “Apply”.
● Start at the top-left.You have the ‘big picture’ view of your sales this year versus last year, and the variance (in dollars) and as a percentage.
● Just below that you have two more dashboards that give you a bit more detail – note the sales figures per month (and the variances in month #8 & #9), and, below that, a geographic representation that highlights the regions with the greatest sales growth and decline.
● Next check out the top-right “Customer” section – providing even deeper insight into the specific customers whose sales have increased or decreased the most this year versus last. Let’s see if we can find out why sales for the customer “ABC Venture” have dropped. Just click on their name to break-down this client’s sales by product/item.
● In the “Item” section (below), you’ll see the products this client purchased – and their sales totals and variances from last year to this year.
● You can use the ‘Sort’ icon in the “Var” (variance) column to see clients’ top product purchases by sales growth or decline. Click your mouse so that you can see this client’s top product purchases by sales decline.
● We can even drill-down into details of this client’s invoices for their top-declining products. With your cursor pointing at the first row of the “Var” column (the ‘Contrampl’ row), drag your mouse over this cell and the two cells that follow it (highlight the first 3 rows under the ‘Var’ column. A pop-up windows will appear; click on “Show Details”. Note how you are now taken to the “micro” level of detail (bottom-left) – the specific invoice details telling you exactly where, why, when, and how this client’s sales have declined. (This information can also be easily exported to Excel or PDF.).
● You can also focus your analysis on other KPIs such as gross profit, cost-of-sales, and quantity sold. On the right-most panel, click the “SA Measure” selection criteria drop-down list and try re-running this analysis with various different KPIs.
Without DataSelf, you’d need to write an additional report for each additional KPI.
● When finished looking at this dashboard, click on the “Revert” button at the top-left of the page (to restore the displayed data to its original state) and then click on the “Home” icon on the top-right of the page to return to the main DataSelf window..
2) Reduce Bad Debt & Get Paid Sooner Writing off bad (uncollectable) debt is one of least enviable tasks that a CFO has to perform. Using analytics to anticipate potential bad debt situations – and prevent them – can result in savings of thousands of dollars every year..
● Click on the ‘High Risk Debt Customers’ button or tab. Like the previous analytics, this one provides you with big-picture details via two dashboards (on the top-left), followed by consolidated customer details (on the lower-left), and then finally customer aging specific details on the right.
● Using the same techniques as described in the previous section, note how you can control the order in which records are displayed, note how you can drill-down into one or selected records, and note how you can use the selection criteria window on the far-right to view only specific aging buckets, clients, salesreps – or even “risk quotient” (e.g., high-risk clients only).
● When done viewing this dashboard, click on the “Home” icon on the top-right to return to the main DataSelf window.
3) Avoid Inventory Shortages One of the most valuable aspects of DataSelf Analytics is its predictive abilities; for any organization that keeps stock, the ability to avoid – or at least minimize – inventory shortages translates directly to increased revenues.
By virtue of its ability to dynamically pull data from multiple sources (including multiple applications that are not themselves natively integrated), perform sophisticated calculations on that data, and then predict potential shortages or stock outages, DataSelf can enable an organization to take pro-active steps (e.g., increase quantities on future purchase orders) to increase the probability that they be able to fulfill future orders.
● Click on the ‘Inventory Planning Workbook’ button or tab. This dashboard is a little different from the last ones you’ve looked at; note how (at the top-left) there is a description of the specific calculation used to make an accurate forecast of inventory needs. The calculation used here can be easily modified to take into account additional factors specific to your organization – and not require you to use a “one size fits all” equation.
● Take special note of the number in the Projected (‘Proj’) column; the one of greatest interest is the last one – “Projected Excess/Short”. In addition to using the selection criteria window on the far-right to control the time-range of your projection, you can opt to view only specific demand-levels, items, and classes. Of special interest is DataSelf’s ability to let you postulate on various outcomes based on one or more variable factors – in this case, a variable rate of increased sales (e.g., 10%) over the specified timeframe.
● When done viewing this content, close the window – and you’ll be returned to the main DataSelf window.
4) Using Natural Language Querying
Natural Language Query (NLQ) is the option to build your own analytics in DataSelf using nothing more than plain English phrases. Similar to using a web search tool like Google, this enables non-technical staff to request analytical insight without having to know how to create a BI-fed report or dashboard.
Note that you may be required to enter login credentials when accessing NLQ; to do so, simply login to https://bi1.dataself.com/ and specify the value of DataSelf#1 for both the username and password.
Follow these steps to see how quick and easy it is to use NLQ:
● Click on the ‘NLQ – Natural Language Query’ button or tab. We’re going to use this option to analyze sales per salesperson in the year 2022.
● In the box titled “Search fields or values”, type in Sales by salesperson in 2022 and press your ‘Enter’ key. You’ll see a window like the following:
● You’ve got instant insight into the performance of your sales staff – for any timeframe you’re interested in.
● Now – in the same field in which you entered your initial query criteria, type in by month (confirm that you wish to “group” your results by month), and press Enter. The dashboard instantly changes to this:
● Now you can see the ups-and-downs of your salesreps by month – and you can continue to add filters, sorting, and drill-down until you get the precise information and insight you’re looking for.
● See the drop-down list on the top-right of the dashboard – it currently defaults to ‘Line Chart’ – and you can change that to a number of other formats.
● Select Text Table and you’ll get this:
● From here you can download this information to Excel or other formats for further use or editing.
● Click Clear All to begin a new NLQ request. At your convenience, try other NLQ scenarios, such as Top 10 items by sales in Q1 2022, and Sales by state by year as a map.
This completes your tour of DataSelf Analytics for ERP solutions. If you’d like to try out DataSelf Analytics for your organization, go to: https://www.dataself.com/dataself-advanced-analytics-order/
For details on pricing, go to:
And if you’d like to speak to one of our staff about your analytics needs, please go to:
Thanks very much for your interest in DataSelf Analytics; we look forward to working with you..