The Evolution, Need, & ROI of Analytics

The origin and definition of the word ‘report’ is:

            “A description of an event that occurred, carried back to be told to someone who was not at the event.”

As businesses emerged in human civilization, “reports” were increasingly used to demonstrate accountability – what would eventually become audit trails.

2,000+ years later . . . and things haven’t changed all that much.

The reports that are included with an ERP application look at business activities that have occurred (e.g., historical sales, revenues, & expenses), or at the current state of business conditions (e.g., current stock levels, current open receivables).

And that’s fine because every organization needs to verify what has happened (especially for reporting to management and/or shareholders), and every organization needs retain a history of their business activities.

But modern businesses realize that their organization’s success didn’t depend on what had happened, but rather depended on what could happen, what should happen, and what will happen in the future. And so – about 25 years ago — “Business Intelligence” and “Analytics” entered the picture.

Businesses realized that by analyzing the past activities and performance (as opposed to merely reporting on them), businesses could predict and postulate on future activities and performance. Potential opportunities presented themselves – and potential pitfalls could be avoided.

Standard – “out of the box” – ERP reports typically provide pre-determined ways to view historical data. For example, a year-over-year sales report may look at gross revenues – failing to show geographic variances, over and under-performing products, and other mitigating factors.

Most glaringly, traditional reports do not “slice and dice” or “drill-down” into the data presented you. For example, a Salesperson Performance report may show that some of your reps are underperforming, but it doesn’t give you the flexibility (and interact-ability) to find out why – perhaps identifying specific products, regions, or even times of year when a rep’s numbers are abnormally low.

So – although Analytics are all about improving future success, their ability to do that depends entirely on their ability to do a better job than standard reports in analyzing the past.

A recent poll of organizations that were investing in BI were asked their reasons why – and the top three answers are telling:

• 60%  wanted to produce & deliver more sophisticated & flexible reports.
• 70%  gave monitoring cash flow as a top reason.
• 80%  stated that optimizing inventory was a chief concern.

Based upon the preceding information, you’d think that every business would be clamoring for Analytics; unfortunately, Analytics presented 3 initial challenges: Cost . . . time . . . and required expertise.

The first wave of Analytics solutions were expensive (hundreds of thousands of dollars), required months (not weeks) to install, configure, and deploy, and could be used only by some self-avowed ‘data geek’ down in IT.

And so only the largest organizations could benefit from the first wave of analytics. Small and mid-sized organizations could not justify the ROI of the technologies that would enable them to make better business decisions.

And then came the second – and current – wave of Analytics; with three key differentiators:

1. Affordability. Analytics pricing dropped from the hundreds-of-thousands of dollars to as little as $399/month.
2. Speed of Deployment. Deployment time for an Analytics solution went from months to days; today, clients can have an Analytics solution up-and-running in under a day.
3. Ease of Use. A natural language query (NLQ) interface allows non-techies to use plain English requests to create analytics. Second, analytics moved from being just a ‘tool’ to including hundreds – if not thousands – of ready-made analytical reports & dashboards.

For more on ROI, see the section titled “How to Sell Analytics / Key Questions to Ask”.