#business intelligence usage

[dataspace]

The Novice's Approach to... "What... If Analysis"

When folks talk about what they want to do with business intelligence, "What... if?" analysis is rarely number one on their lists.  On the other hand, it is most folks' number two (usually after "provide users with easier access to data" and before "predictive analysis").  It's interesting, however, that "What... if?" analysis is rarely actually performed in real life.

WHAT IS "What... If" ANALYSIS?

What if analysis is exactly what it sounds like - looking at your data as if some situation was true.  For example

WHAT would our profits be IF our unit cost was reduced by 2%.

WHAT would happen to our profits IF we spent 5% more on marketing but it produced a 5% increase in revenues? A 0% increase?

WHAT would each salesperson have produced last year IF we didn't carry our  vanilla-flavored chocolate pudding?

WHY IS IT SO HARD?

It isn't.

AN EXAMPLE

Here is a simple example from QlikView that asks the question, "What would happen if our revenues changed by X%?"

In this example, the user can modify the revenue forecast.  As the example shows, if you don't expect there to be any changes in revenue, the 'as is' and 'simulation' amounts will exactly equal each other.

On the other hand, let's see the predicted results of 25% increase in forecast revenues:

Now the user can see the difference graphically.  This analysis could also, of course, be shown as a table so users could analyze the actual, What..If figures.

BEHIND THE SCENES

You can do What If analysis with any BI tool.  The trick is to insert prompts and variables into your reports that users can change.  Then, use those variables as figures or multipliers in your reports.  Just about every BI tool supports the use of variables.

In the example above, the slider bar sets a variable called vRevenueIncrease.  The magic is in the graph.  Basically, the graph charts two lines: the forecast revenue AND the forecast revenue * vRevenueIncrease.

While we've shown a slider bar, most BI tools give you a few ways to enter variable values.  

BE CAREFUL

When you do "What..If" analysis, make sure to consider the cause and effect relationship between variables.  For example, if you model a 5% increase in revenue you'll show a great improvement in profitability.  However, that profit improvement is really illusory if you haven't also modeled the increase in cost of goods sold and the other costs associated with an increase in sales (By the way, a 5% increase in sales price, as opposed to unit sales, might properly show the related profit increase so long as the increased sales price wouldn't also lead your customers to purchase less).

Also note that, most BI tools make it difficult to store variables between sessions or to save multiple scenarios.  So, if you want to keep what you've created, export it, print it, or lose it.

Anyhow, thanks for your time.  Feedback is encouraged & appreciated.

[dataspace]

Dance Moms and the Future of Business Intelligence Acceptance

If you've read my posts about business intelligence you know that I'm fascinated by the fact that many BI and analytics systems just don't garner the usage that their sponsors envision for them.  This can be tied to a number of factors including a failure to align analytics with business processes, mismatches between BI tools and user requirements, corporate culture issues, and organization design matters (I covered this point in my last post).

But, I've recently started to believe there is another factor that, in the long run, bodes well for BI usage.  This change relates to the general comfort with data and technology in society.

When I graduated from college (1984, if you must know), the IBM PC was relatively new and 15 megabytes of disk storage was huge.  In fact, most PCs didn't even have hard drives - they had floppy disks.  There was no Apple Macintosh.  I, actually, wrote term papers using a mainframe word processing program that formatted them in batch jobs!

So data, and even computer, comfort was developed only by those of us who were interested in the concept (i.e. most people created their term papers with a technology we called the type-writer).  Most of us also remembered and feared HAL9000, the computer in 2001 A SPACE ODYSSEY, 

As a result, many of us harbored, and still harbor, a basic fear of computers and technology.  Our children, on the other hand, grew up with computers and they aren't afraid to press buttons (as evidenced by the number of viruses and hidden background processes recently discovered on our home computer).

Consider your own situation for a minute.  Do you know someone, perhaps your spouse, parent, or in-law (or, frequently, all three) who seize up with fear at the thought of trying to program the TiVo, downloading apps onto the iPad, or clicking the wrong link in their web browser?

Now, compare these folks to your kids.  Do your kids suffer from the same fears?  Most likely the answer is, "No."

These same kids are the knowledge workers of tomorrow.  They've grown up with the concept of computers and the concept of searching for data.  On the whole, the next generation of corporate leaders are just more comfortable with data and computers.

I guess what I'm saying is that, in the future, BI will be more easy to integrate into organizations because today's kids know how to record Dance Moms (Tuesdays at 9 pm, 8 Central, on Lifetime) on the TiVo.  Gd help us :)

Would love to hear your thoughts!

[dataspace]

Ensure BI Usage by Building A Data Driven Company

When building an analytics system, don't let some BI vendor convince you that everyone in your company will create their own reports; They won't.  Virtually every new BI effort starts off with this goal of instant user self sufficiency.  But remember, while BI and analytics are marketed as the Viagra of data self-sufficiency; actual mileage may vary (OK, I believe I mixed a few industries and metaphors there but I think I've made my point).

When they realize that the Viagra approach just provides false (and expensive) hope, the next place most companies turn is to having a set of experts in IT use the shiny, new BI tool to create predefined reports for users.  While a step in the right direction, this not the right step to take for two closely-related reasons:

Virtually every BI effort starts with the premise that distributing reporting responsibilities to the business will reduce the reporting demands on IT. Having IT create reports largely shifts the same work to a new toolset, and

When IT creates the reports, the report developers are a step removed from the day-to-day input of the folks who need the data.  The developers won't have that hands-on feel for what's really needed and even for what the basic business terms mean.

I recently spoke with managers in two Fortune 1000 companies (Automotive and quick service restaurant) who have both come up with the same answer to this problem.  And, both have user communities that are gobbling up their BI capabilities.  The approach is this: Develop a BI subject matter expert (SME) in each user department.  This SME will create the templates and reports for their peers in the department.  Rather than assigning this role to a random person in the department, this person must already show a proclivity for working with data.  This is usually the guy in the department who everyone already turns to when they need to do something complex in Excel.  

Situations will vary but being the BI SME is usually not a full time role.  These folks have other day-to-day jobs to do.  But, because they are a part of the department every day, they're in the perfect position to understand what their coworkers are saying & what they need.

Having a BI SME also saves you from wasting money training folks who aren't going to get anything out of it.  Train the SME on the complexities of the tools.  Train the rest of the department on the few steps necessary to open & use the analyses he creates.

So, when preparing to roll out your BI or analytics system, don't expect users to just pick it up.  Build the right organization, use the right tools and, if the need for data is really there, the system will get used.

Would love to hear your thoughts!

[dataspace]

The Myth of Self Service BI

Most business intelligence efforts start with a statement like the following, "Let's build a BI system so our employees can get whatever data they need, when they need it."  While well intentioned, statements like these are misguided.

The truth:

If folks do their jobs today without using a shiny, new BI tool, why are they going to put extra effort into learning your snappy new tool?

Most folks don't get a big thrill out of accessing data - BI is like a dishwasher, a tool for getting a job done.  Do you want to go to classes and learn a panoply of new things just to use your dishwasher?

Most folks' data needs are limited to a relatively narrow range of topics (e.g. sales folks typically don't need to access HR data).

Even with data warehouses and strong metadata, BI tool vendors have not yet produced a tool that gives anyone simple access to every piece of data in an organization.

The implications:

A few folks do have the need, desire & technical skills to get and analyze their own data.  These folks are called data analysts.

While it's not sexy in terms of BI (is anything sexy in terms of BI?), the vast majority of folks have structured jobs that require access to a limited range of data and they usually need it in some set format (e.g. this week's accounts receivable aging report).  Assume that these folks need BI tools that provide predefined reports into which they can enter a few parameters - tools like WebFocus, Crystal Reports, and SQL Server Reporting Services.  Also assume that these folks will NOT create these reports on their own - you will need technical experts to create and maintain these reports.

You are far more likely to see wide usage of your BI systems if your business processes are designed to be data driven.  Business process design, along with a culture change towards being data-focused is a prerequisite to widespread BI adoption.  It is also hard, time consuming work.

Widespread BI adoption isn't always the correct measure of success.  A $2 million BI system that serves just one user could be a major success if that one person makes or feeds input into multi-million dollar decisions. 

So, if you want a clear path to ROI, rather than starting out to build a BI system, start out to change your organization.  Then, figure out how and where BI is necessary to enable that change.

[dataspace]

Appfluent for Monitoring BI & DW Usage

What parts of your data warehouse are really important and which are never touched?  A few weeks ago I and some colleagues here at Dataspace saw a brief demo of Appfluent.  Affluent is a tool that monitors and reports on the use of database objects and, in some cases, BI tools.  It can answer important questions such as:

Which tables are being used and which aren't?

Which queries are run most often?

Which queries gobble up the most resources?

etc.

Armed with information like this you can do things like:

Eliminate unused tables

Develop strategies to improve the performance of troublesome queries

Determine if your warehouse is really being used at all

In the end, monitoring like this can help you improve and, perhaps, lower the cost of your data warehouse.  You might want to give it a try.