Category Archives: cognos

Using structured data analytics to make better business decisions

imageIn the current edition of Analytics, a cross-brand team from IBM (Irv Lustig, Brenda Dietrich, Christer Johnson and Christopher Dziekan) explain IBM’s view of the structured data analytics landscape.

Key to this model are three categories of structured data analysis:

1. Descriptive Analytics: A set of technologies and processes that use data to understand and analyze business performance
2. Predictive Analytics: The extensive use of data and mathematical techniques to uncover explanatory and predictive models of business performance representing the inherit relationship between data inputs and outputs/outcomes.
3. Prescriptive Analytics: A set of mathematical techniques that computationally determine a set of high-value alternative actions or decisions given a complex set of objectives, requirements, and constraints, with the goal of improving business performance.

As the authors explain, this model can help businesses make better decisions, rather than just simply automate standardized processes.

Let’s use the example of a fictional global shoe manufacturer we’ll call ‘Footloose’ to see how each category could be used to increase business performance.

Descriptive analytics

These are your flexible dashboards that let you focus in on key areas of the business. For Footloose, this could be all the standard operations dashboards eg. like the one showing monthly shoe sales by region. Footloose should be able to see how actual sales fared against the forecast. Where there are deviations (say the sales of sandals in Spain has gone through the roof), they can use descriptive analytics to drill-down into the data. They may see that the growth is coming from the Madrid and possibly related to a major marketing push during a hot spell in that region.

IBM Cognos solutions offers this kind of descriptive analytics (including business intelligence) that can be implemented to measure and explore how a company is performing.

Predictive analytics

Here we use data from the past to make predictions about the future. For Footloose, this could include combining seasonal sales variations for a sports shoe with the longer term uptrend they have been seeing for the last few years. Footloose can also use predictive analytics to improve their web presence: they can launch a recommendation engine to suggest what a visitor might want to view next based on what they (and people like them) have looked at in the past (like the book suggestion service Amazon offers).

IBM SPSS offers a set of predictive analytic tools which allow business users to employ predictive insights at the point where decisions are being made.

Prescriptive analytics

How can we achieve the best outcome, whilst addressing any uncertainty in the data? Prescriptive analytics can help us answer this question. Let’s say Footloose has made its prediction about what shoe sales are likely to be over the coming year. Now they just need to figure out how to respond to those predictions. Sales of sandals are expected to remain high in Spain so they need to increase their distribution channel there. How should they achieve this? Increase the fleet of vehicles or buid more (costly) distribution centers.

Footloose can plug the data into an optimization model (costs of building a new plant, buying new trucks, gas) to calculate what would be the most efficient supply chain to deliver the extra required capacity.

IBM ILOG Optimization has technologies specialized for these kind of calculations where there are large data sets with potential uncertainty.

I’ve used this example to present a simplified view of IBM’s approach to structured data analysis and how IBM technologies can be used in tandem to improve business performance. A key advantage of these technologies is that their utility stretches across various industries and applications.

For a fuller explanation of this field, I’d definitely recommend reading the full article in Analytics Magazine

Critical issues in business analytics: James Taylor

Decision management expert and consultant James Taylor was ‘cornered’ recently at the IBM IOD conference and asked to explain the present and future of business analytics. An eloquent speaker and veteran in this field, James does a great job of highlighting the current growth and energy in this space, some of the confusion this has engendered, and the questions you should be asking yourself in determining whether analytics are right for you:

He also highlights three critical issues on which I’ll share my viewpoint:

Where can analytics be employed?

Decisions take place across the organization: from the CEO deciding who to appoint as the new sales director, down to the customer service rep asking if you want to take out a maintenance plan when you buy a new computer. At not all points does it make sense to employ analytics to inform the decision process. If you have highly automated business processes in your organization, then company-wide business analytics may make sense. Alternatively, it may just make sense to use analytics to sharpen up one department such as the marketing operation.

There is a political dimension to this which also has to be considered. It could be that the marketing department has a tight agency relationship who strongly pitch an analytics solution highly tailored for the marketing operation. Whilst this may be able to drive up efficiencies in marketing, it won’t help the support decision process (or possibly cross-sell or up-sell opportunities).

On the other hand, it could be that the IT department, in the interests of cost-cutting, prefer to go with a centralized solution with a narrower maintenance footprint. 

These considerations (which tend to be aggravated in larger organizations) need to be taken into account in addition to the theoretical/modeling questions:

"What are the decisions that drive my business? how do I apply analytics to make a better decision or drive my metrics in the direction I want?"

Figure out how to align Business, IT and Analytics

In the past it was tough enough to engage business and IT departments (which can be heavily siloed and have the kind of relationship you see between Siamese Fighting Fish). But now you’re throwing an analytics team into the tank.

Although I’d suggest that this analytics team can provide the glue that holds together those creative types in marketing and the IT logicians. It’s not unusual to find the analytics practitioners sitting somewhere in a department such as the corporate office. Whilst they may have strong knowledge of the tools, they are also plugged into the business imperative. As long as the importance of their role is realized and they are given due authority, they may well be able to spearhead the implementation of a business analytics solution and its systematic application.

Begin with the decision in mind

Why? So you don’t end up drowning in data that will do nothing to drive your business. James points out that you need to understand what is a good and bad decision (for instance be clear on what a positive or negative outcome looks like).

Just like the scientist needs to understand there is inherent bias in the questions she asks, so you should realize that the decisions you choose to focus on can have a profound effect on your business. For instance just applying analytics to short term decision making (such as maximizing quarterly sales) could pull you out of synch with any strategic objectives and hurt you in future years. If you go overboard using predictive analytics to decide what to offer individual customers next on your website based on their past behavior, you may end up looking like a creepy stalker. Keep an eye out for symptoms of unintended consequences!

James is one of the most prominent/prolific bloggers in the decision management space and can be found at JT on EDM and ebizQ.

In the video James references these IBM technologies: Cognos business intelligence, predictive modeling from SPSS, and business rules and optimization solutions from ILOG.

Analytics warning: what you don’t know could be harming your business more than you think

imageA post by Timo Elliot over on the Forbes blogging community posits that we have a tendency to be overoptimistic on our abilities. For instance, 93% of Americans think they have above-average driving skills.

This notion of our egos over-inflating our perceptions of our abilities carries over into the business world: many successful executives have similarly high opinions of their decision making skills and ‘hence under-invest in fact-based systems and processes that could help us correct our misperception’. The systems Timo is talking about here are business analytics and business intelligence systems.

Now if this is the case, there would be space for competitive advantage by those execs who put trust in these systems when it comes to making business decisions. And yes, in fact this is exactly the finding of a recent study conducted by IBM and MIT Sloan Management. Here is the bottom line:

Top performing companies are three times more likely to be leading users of analytics.

So the companies that are using analytics have a tendency to perform well in their segments. Michael S. Hopkins, editor-in-chief, MIT Sloan Management Review goes even further and suggests that these top performing companies are reaching to further their use of analytics:

"Interestingly, the top performers also turn out to be the organizations
most focused on improving their use of analytics and data, despite the
fact that they’re already ahead of the adoption curve."

If you are not in this top-performing coterie, beware. These are the companies that also stand to widen that gap in their performance against that of their non-analytics-based competition.

When it comes to implementation of business analytics, Timo’s post talks about sharing information and decision-making as widely as possible (garnering the ‘wisdom of the crowd’). We are seeing this feature creep into the latest generation of business intelligence tools. For instance, IBM Cognos has added social networking to the latest version of the flagship product. Although, as Timo points out, there needs to be organizational as well as technological change for this to be effective.

The IBM/MIT study offers further advice on rolling out business analytics solutions, such as tackling the biggest obstacles first. For instance, in the online marketing space, you may want to concentrate on implementing analytics on your largest marketing channel, or on the part of your website that receives the most traffic.

You should also determine first what insights you are after, and then figure out which data you need to help you to get to the answers. Again, in the field of marketing (you may have guessed this is my comfort zone), questions could be ‘What pages on the site normally lead to sales?’ or ‘What frequency of email nurturing works best?’. A good vendor should be able to help you frame the questions and get to the meaningful data – don’t be afraid to ask: ‘what should I be measuring’.  

Read the Timo Elliot post

Read the IBM/MIT study

More on IBM Cognos

Cognos 10: what does social networking bring to business intelligence?

In my previous life as a webmaster I was called on to develop monthly web performance reports for consumption by the whole marketing organization. At one time these had been documents that were mailed around, but we decided the best approach was to build a web interface with charts and diagrams that would be updated monthly.

We showed standard metrics. Stuff like this:


Each month I’d send out an email with a link to the latest report with my notes on site performance each month. For instance, I’d point out from looking at the graph on the left that although traffic had dropped this month, this is a seasonal variation. For the graph on the right, I’d say I wasn’t sure why our search traffic had grown: this is something I’d investigate with the various individuals running search campaigns (meaning for 90% of the people on the email distribution, the answer would end up in an Inbox far, far away).  

How much smarter we could have been if we’d have had access to a system like Cognos 10 that marries business intelligence/analytics with social networking capabilities that allow you to add that layer of insight on top of the data.

For instance, here’s a standard chart:


and here’s the same chart with the addition of related Lotus Connections discussions:


Going back to my examples above, if I was showing yearly traffic figures, I can use this discussion area to record what I know about seasonal variations. Now if someone receiving the report didn’t agree with my evaluation, they are free to comment on it. As for the discussion I’d need to have with my search marketing folks about why the search traffic has spiked, I can set this up from the same page:


…with the thread of the discussion unfolding below the graphs and charts to which it relates. Anyone wishing to follow up on the status of the question can go to that page and scan the thread to see the outcome.

I should point out that the Cognos folks have taken this a step further: integrating activities as well as discussions. The data is now more ‘actionable’. Let’s say you are looking at global sales data and you notice a slump in a certain geographic region. You can use the new functionality to setup an Activity to address this, with a number of associated tasks assigned to different sales people or teams. Over time you can evaluate their actions against the performance data all from within the same interface.

And while we’re talking about the sales team, another new feature in Cognos 10 makes it easier to access reports while on the go, directly from your smart phone:


One feature I’d love to see in future releases of Cognos is the ability to tie conversations/activities to given points on a graph, as opposed to just having these attached to the page of a report. As an example, the popular SoundCloud music hosting service has gained a lot of traction by allowing music enthusiasts to comment on a particular point in a music track:


(each blue bar represents a separate comment)

Maybe something for a future release?

Delaney Turner has a post with more information on Cognos 10, including a link to an excellent interactive demo.

Also check out the Cognos product pages.

IBM’s marketing automation solutions: a primer

Christopher Hosford over at BtoB Magazine ran an interesting piece on IBM’s foray into the field of marketing automation focusing on the recent spate of acquisitions here at IBM. I thought it would be worth expounding on how each of these acquisitions fits into the notion of a holistic marketing automation solution – using an example that hopefully most of us can relate to: internet retail.


Internet retailers use web analytics to explore which parts of their site are most effective, which channels are driving most visitors and what are the common paths taken by visitors who buy. Conversely, analytics can also highlight problem areas such as product lines that receive heavy traffic but little conversion to sale, expensive marketing channels that provide little revenue-generating traffic and navigational bottlenecks. You can take this further using a solution such as Intelligent Offer, which exposes the analytics to the visitor: much like the recommendation engine used by Amazon bookstore on their individual listing pages to say ‘if you like this book, you may be interested in these books too’.


An internet retailer that exploits different marketing channels, eg. email, web, social networks, can use Unica’s Interactive Marketing solution to track responses across the different channels and use this data on past behavior to tailor future messaging. It also allows you to uncover those prospects that have been most responsive and are more likely to cross over and become customers.


Netezza can help the internet retailer wherever there are large sets of structured or unstructured business data. For instance you can use Netezza for bid price optimization of search marketing campaigns where you might have 100s or 1000s of keywords covering product inventory, coupled with multiple text ads and landing pages, leading to millions of permutations. Predictive analytics can help you determine what is the optimal paid search campaign structure.

Sterling Commerce

When it comes to order processing, Sterling Commerce can help internet retailers ensure consistency across different channels (eg. keep consistency across different web sites with different experiences). As one example, the system can help dealing with coupons and the correct application of discount codes across all channels.

I should point out that these are only individual examples. Each of these acquisitions have plenty of other offerings, many of which touch on different components of marketing automation.

I’d be remiss not to mention Cognos, SPSS and ILOG, all of whom offer business analytics offerings that can be customized in a marketing automation context.

IBM’s Business Analytics solutions are set to mature as these acquisitions are woven further into the fabric of each other and the expansive IBM quilt of offerings. Early indications are positive however, as IBM’s Business Analytics revenue has grown 12% over the last year to a net income of $3.6 billion. This would suggest we’re in for some interesting times ahead!

BtoB Magazine article on IBM’s marketing automation solutions

In the news: advanced business intelligence from Cognos 10


The big news today from the IBM IOD Global Conference and Business Analytics forum is the unveiling of Cognos 10.

The most common feature brought up on news sites and blogs is the ability Cognos 10 opens up to access business intelligence on a mobile device: be it a Blackberry, iPad or iPhone. Bloomberg picks up on a case study from the car rental industry:

"Hertz Global Holdings Inc., the largest car-rental company, will gather survey data from customers via text messages, and use IBM’s software to analyze responses. Employees can then receive real-time information on potential problems, such as wait times at car-rental locations, and adjust accordingly. Office Depot Inc. also is using the software to gather, analyze and report store-performance data."

Meanwhile, Dr Dobbs focuses on the move away from charts and graphs to "broader analysis tools supported by built-in images and user help videos". They also highlight advances in predictive analytics and ‘what if’ scenario evaluations.

Over on PC World, there is coverage of the tie-up with other parts of the IBM portfolio. Linkage with Lotus Connections, IBM’s social networking platform, will "allow users to engage in conversations about business information and get more value out of the software". Cognos 10 also includes a statistics engine from the SPSS suite.

ITBusinessEdge points out the importance of business intelligence in the current economic climate: "business executives are looking for simplified access to more relevant information they can trust".

More information on Cognos 10
More information on the IBM Business Analytics Forum

IBM Business Analytics Software protecting children in care in Nevada

imageAs the Business Analytics Forum gets underway in Las Vegas, eWEEK feature an article on how IBM’s analytic software is helping Clark County Family Services Department in Nevada improve the delivery of social services. Prior to using IBM analytics, spreadsheets were used to monitor care workers and the level of service provided. Due to population increase and the need to conform to state legislation and policies, the department needed a solution that would make reporting easier, help the department comply with new regulations, and measure business performance.

According to Eboni Washington, a IT supervisor in the Family Services Department,
“Before this we had a lot of children not being seen each month. And now we have an automated system, rather than some workers keeping a hand count of who they have seen and what they have done each month.”

For more information, read the full article in eWEEK.