Bad Meat

We bought some bad meat the other day. We returned the meat to the butcher and the manager promptly, and without hesitation, replaced it and doubled our original order at no charge to us. This is one of the reasons we go back to the same butcher, time and time again. We’ve moved recently and this butcher is no longer in our neighborhood yet we still travel quite some way to get to his shop. We go there because he provides good quality at fair prices and excellent service. We will always shop there as long as he maintains the current levels of quality, price and service.

What does this have to do with business intelligence? Service is one of the components in a customer satisfaction scorecard. Keeping track of how customers perceive your organization is important particularly when something goes wrong. Notice how I’m not berating the butcher for providing us with a faulty product. First of all the butcher has historically helped us with selections and good service during our visits. Secondly, sometimes a product breaks or malfunctions or in this case, tastes bad. If a business handles a problem quickly and responsibly, the problem will go away quickly and the customer will know that if an issue does arise that he can expect a quick and fair resolution.

What else can the shop owner learn from the bad meat? Why was it bad in the first place which looks at quality control metrics. Perhaps it was the wrong meat for the job? This was actually the issue for us. The meat wasn’t bad really but it wasn’t the right cut for our intended use. This leads to employee training. Did the person at the counter understand the customer and the intended use of the product? Will employees be trained to ask more specific questions as to what the customer wants? Will employees be trained to handle these types of customer returns?

Or will the entire incident be forgotten?

It’s up to each business to decide whether they want to learn from the daily transactions that make up a business day. Do you want loyal customers? If so then you need to continually train employees, manage product quality and understand your customer. All of these factors will lead to a healthy bottom line.

Analysis Services Presentation

I will be presenting a session on Analysis Services for SQL Server 2005 on December 7 at Microsoft Canada.

Here’s what I’ll be talking about:

Analysis Services in SQL Server 2005 benefits from rich data model support, an enhanced development environment and strong management tools. We’ll begin our session by working with a cube, with emphasis on dimensions and attribute hierarchies. We’ll then discuss the Unified Dimensional Model, data source views and the rich meta data that is used to develop multidimensional models. We’ll also look at some of the built in modeling support provided via business intelligence wizards. Finally we’ll discuss some of the new management capabilities available within SQL Server Management Studio. The user will leave the session with an introduction to the components that make up SQL Server Analysis Services 2005.

You can register here. I’d love to see you.

GM – What Were You Thinking?

General Motors announced yesterday that they are laying off 30,000 employees as part of a measure to curtail costs due to GM’s abysmal sales record. GM is hurting. Hurting bad. They lost billions of dollars last year. The company might not even be salvageable.

Dealerships have to be hurting as well. Some Buick dealerships were reporting sales of only four units per month. Basic economics says if your prices are already rock bottom and you are selling only four units per month then something has to break.

Why is this happening all of a sudden? Why does GM have to shut down so much in one gargantuan swoop? Don’t they measure things? Didn’t they realize a long time ago that cars simply weren’t selling?

Sales is the most basic and yet most important of all the metrics! It’s the king – ruler of all metrics – the penultimate – the metric that all others aspire to be. What did we sell this quarter compared to last quarter? What are our strongest product lines? What were the weakest lines? What kinds of products are people buying? Are we cross selling services or other products? Do we have any dogs (no point in making them if we’re not selling them)? Who are our strongest partners? What parts of the country are selling the best? Who’s buying our products? I could go on and on and on.

GM might have known something was up when they started to introduce employee pricing. Sales were slow so they had to do something. That employee discount was a dumb idea right from the outset. How are you going to recover from cheap prices? It’s easy to lower prices – everybody likes that. But once you lower them, it’s very hard to raise them back up again. Competing on price is one of the least effective ways of making a sale or even staying in business. You might gain some short term market share but if I purchased a GM vehicle on an employee discount, you can bet I would expect that discount forever.

Setting a price for a product or service is clearly important and non trivial. The company may want to maximize profits or market share. But selling on price alone is one dimensional and likely does not address the real concerns of why cars aren’t selling. Did GM look at demographics? What about features like gas mileage, warranties or customization? Scorecarding of buyer behaviors could be used to ascertain likes and dislikes. This information could then be sent out to production so changes can take p[lace quickly. Selling more of what people don’t really want will just create a lot of cheap used GM cars in a few years time.

I wonder if GM’s suppliers were measuring orders for parts and services? Such a big customer can make or break a supplier. If GM continued to produce cars regardless of sales, then there’s a really big problem with the way they manufacture vehicles.

How can GM recover? Let me ponder on that and talk about it another day.

SQL Server 2005 Product Launch

SQL Server 2005 and Visual Studio 2005 launched on November 8 here in Toronto. A lot of people showed up for the event – I’m guessing about 3,000. The day long session was comprised of a SQL Server track and a Visual Studio track but began with a lackluster opening keynote by the president of Microsoft Canada, David Hemler and Craig Symonds, VP of the Developer Tools Division at Microsoft, Redmond.

The keynote was not what I would call inspiring. I guess I’ve been to so many of these that perhaps I’ve become immune to the usual message that this release of (insert product name here) is the greatest ever. Faster than a speeding bullet, able to leap tall buildings in a single bound, allows you to turn back time, cholesterol free and calorie reduced. I’m not sure why they even talked about BizTalk 2006 since this product is not even shipping and won’t be until 2006.

Ok, I’m getting a bit sarcastic since I really like both SQL Server 2005 and Visual Studio 2005, particularly since we use them to build and support our services. They provide us with a rich, deep toolset that allows us to tailor cost effective business intelligence services for our clients. That said, the demos that were presented at the keynote were mundane at best and did not showcase the products at all. The keynote is meant to be a short overview and the details should be presented in break outs but I wanted at least some wow factor. It should be easy because the new releases offer so much for the developer.

I had some involvement with the SQL Server 2005 sessions. I was part of a small group of individuals asked to contribute feedback and suggest content for the sessions. We talked about presentation, content of course, and what was important to show given the limited time available. In fact that was a big part of our discussions – what to exclude. There is so much material to talk about that when we received the early drafts of the sessions we thought each topic consisted of several days of presentation! Bias alert on! I think Barnaby and Damir did a great job of presenting so much material in just three short sessions. Bias alert off!

I was also in the Ask the Experts Cabana, answering questions on SQL Server 2005. I got some standard questions like how much faster is the new release. This is a “it depends” type of answer as to what the database operations are. You have to make sure that we are comparing apples to apples. For example, some operations in SSIS (the ETL tool that ships with SQL Server 2005) are extremely fast. That said, it would be difficult to compare to the SQL 2000 version directly since many operations can be combined into a SQL 2005 package that simply were not possible in the prior release. In a SQL database you are rarely performing just one operation so comparisons without detailed specifics are not simple. Overall the new release is a lot faster but a factor of x times faster simply can’t be supplied.

I have to address one semi sarcastic comment I made earlier about SQL Server 2005 turning back time. This was not all that facetious. The MDX query language for Analysis Services allows us to go into the database history to retrieve anything we want for a given time. This means that numbers can be compared over time, related to events that may have affected the outcome those numbers. This also means that forecast models can be created based on history and tested and then used moving forward. Data mining algorithms can also be used to help users with future events. I’ll talk about forecasting another day.

I was also asked about technology investing and whether Cognos is a good stock to buy. Some folks in the equities world see this release of SQL Server 2005 as digging into Cognos’ share of the business intelligence market. You could ask the same about database vendor Oracle. Both companies got to be where they are in the market place because they make good products. New product releases do not instantly change the face of the market.

I think businesses don’t necessarily want more software. They want more answers. They want something that will make them money, be more competitive or create market share. When innovative companies take these new software tools and provide a cost effective service, then yes, I think competitors share prices will be affected. But it won't happen overnight. Of course, if I could foresee the future with 100% accuracy then I’m not sure I would be telling you or anyone else what I would be investing in.

Back to the product launch! So while I thought the keynote lacked pizzazz, it was still a great event and a lot of people went home with an introduction to some really great new tools.

What's In A Name?

People have been a bit confused by the term “cube” when it comes to a multidimensional data set. A “cube” allows you to ask questions with multiple dimensions associated with the query. It would go something like “I want to see sales and costs for Arizona, by city, by quarter, by product category, by high profit customers.” Do you notice how there are lots of “by this, by this, by that” type qualifiers? A cube implies three dimensions. There were more than three criteria when retrieving the sales information but we still call the structure a cube. Cubes are highly optimized for these types of queries. Other database structures like the ones you likely use everyday are not optimized for these types of queries. In fact cubes can hold many dimensions with detailed granularity, if that’s what’s required.

So don’t let this “Cube” term mislead you. If it does, perhaps you can think of it as a multidimensional cube or MD Cube.

...Can I Just Install It?

Today’s post picks up where we left off yesterday.

We met to discuss what was needed but the meeting did not go well. The call center people wanted access to the data – all of it. Their database was quite large and although the client had excellent infrastructure, it was simply impossible to allow the call center managers to access every last piece of information as part of an analysis environment. I wanted to know what they needed to see so the proper cubes could be built or at least a starting point created. No matter how I asked the question, I got the same reply – “We need to see all the data”.

I was frustrated as you can well imagine. I wanted to help the client and they needed assistance but we weren’t getting anywhere. So then I stated the following, “Imagine that you have the entire database at your fingertips. Responses to any questions you might have are instantaneous. What are the first twenty questions you are going to ask?”

The room was silent. There were no replies. No one knew what they were going to ask. No one knew the benefits they would receive by implementing this new solution. No one could tell me the relationships they needed to see.

It can be difficult to quantify return on investment for business intelligence. We’ll address that in another blog. However some guidelines do apply as to what you want it for in the first place. A BI solution whether it contains key performance indicators or data mining or analytics can’t succeed unless you have at least some idea of what you expect to achieve by implementing any or all of these components.

• How will the solution improve internal processes?
• How will customer service be improved?
• How will employees benefit from monitoring performance?
• Can the company expect increased revenues, reduced costs or improved cash flow from the business intelligence implementation?
• Are there hidden relationships within the data that might exist that will help with any of the prior points?

By using these five guidelines, you can create your own ideas of areas within your organization that could benefit from a business intelligence solution. You can't just add a Business Intelligence solution. It doesn’t make any sense from a practical or technical perspective. A solution must have guidance from the consumers of the information combined with direction from the implementers.

Business Intelligence – Can I just install it?

Do people really think that they can simply add a Business Intelligence score carding tool to their environment and that business will benefit from it?

Let me tell you a story about an experience I had at a major account. I had been working on an analysis application dealing with financial forecasting. We were able to predict future receivables extending forward three years using an Analysis Services cube I built. One of the benefits of cubes is that query times are very short. This means that algorithms can be built and tested against the cube for things like forecasting. We created several forecasting models and then went into history and forecasted into the present to test the validity of the algorithms. We finally arrived at a good model that made sense and the end result was that the client could forecast receivables with greater accuracy than before. They eventually factored their receivables and were able to lower the interest rate due to the forecasting model, saving them a great deal of money.

The same client had a very large call center and wanted the call center information tied to financial information. This was a great analytics application. There were all kinds of metrics we could build and report on and much to be gained in the way of customer service improvements, employee training benefits, business process improvements and so on.

This story will be continued in my next post…

Initial Post

Welcome to our business intelligence blog.

This will be a place where we can discuss many things relating to BI. We'll talk about what we're up to of course but we'll also try to relate stories about what we see as opportunties and issues pertaining to BI. We'll talk about technology and the latest and greatest tool sets. We'll discuss challenges that businesses face when dealing with BI. And we'll talk about using BI in the workplace and how it helps businesses deal with everyday issues.

Please feel free to add your comments. We'd love to hear from you.