Finding reports, naturally

Another example of innovation in the seemingly mature world of BI can be found lurking within the unlikely setting of Progress Software (Progress acquired EasyAsk in May 2005). EasyAsk is a product which combines search capability with a natural language interface than can generate SQL to run against data warehouses. This unusual combination has led it to be used in many eCommerce sites, allowing for natural language inquiries to be translated into product offerings from web sites.

However the technology is a natural (excuse the pun) fit for a rather understated but very real problem in large organisations: actually finding existing reports or pieces of analysis. Most large companies have invested in licences of Cognos, Business Objects or other reporting and analysis software, but what happens after the initial project set-up has happened? The implementation consultants typically set up some pre-configured environments (e.g. a Business Objects universe) and perhaps a little training, and end user analysts then supposedly have at the data warehouse with glee. In reality most end users have no desire to learn a tool beyond Excel, so most rely on pre-built reports e.g. monthly sales figures, being set up for them by the IT department. A subset of end-users, typically people with “analyst” somewhere in their job title, are happy to do “ad hoc reporting”, though to be honest most of these characters could make do with a command line SQL interface rather than a fancy reporting tool if push came to shove.

The big issue is one of wasted effort due to lack of re-use. If one analyst spends a few hours coming up with a new take on sales profitability, surely this would be useful for others? Yet generally if a request comes down to produce a report, people start from scratch even if there are already perfectly good reports already produced by someone else in the company. They just do not know they are there.

This is where tools with strong search capability can help. Certainly this is not new, and Autonomy, FAST, Endeca etc can be helpful in tracking down existing information. Yet such tools are really designed for unstructured data rather than structured data. EasyAsk has the advantage that it provides end-users with the ability to do natural language queries if they don’t quite find what they need. The leading BI players have begun to realise how much of an issue this is in recent years e.g. Business Objects purchase of Inxigt. However there is plenty of room for a pure-play alternative, as this is a problem that is barely addressed in most large companies.

One complication that EasyAsk will encounter is a natural hostility in IT departments to natural language interfaces, since hoary DBA types (I started as a DBA, so can say this kind of thing) are never going to trust that a generated piece of SQL from a question like “find me the most profitable sales region” is going to get the right answer. EasyAsk addresses this concern somewhat by having subject dictionaries that are compiled with a domain expert (e.g. in HR this might equate the phrases “laid off” to “let go” to “fired” to “terminated”) in order to give its technology a better chance of formulating the right answer, and of course you can always switch on a trace to see the SQL generated to see what is going on and get it looked over by an IT type. However if a DBA has to check the SQL generated every time before approving a new report then this rather defeats the object of the exercise in the first place.

For this reason EasyAsk probably need to target end-users rather than IT departments, who will probably always be a tough crowd for them. If they can get to the right audience, then addressing the problem of making better use of all those pre-existing canned reports is a very real problem to which a large dollar value can be attached. They seem to have made an impression with customers like GSK, Forbes and BASF, and their technology is already embedded within several other companies’ applications. I recall from my days at Shell that this is a widespread issue in large companies, so exploiting existing BI investment should be a happy hunting ground for companies with the right value proposition.