The TOFU (Top of Funnel Users) Approach to Business Intelligence

Posted on by Teddy Nee

The TOFU (Top of Funnel Users) Approach to Business Intelligence

An interesting article in Forbes.com entitled, “Why Top Of The Funnel BI Will Drive The Next Wave Of Adoption”, written by Dan Woods, sparked some great conversations about bottom of the funnel users (20-30% wanting specific business information), and Top of Funnel Users (or TOFU) that want to interact with information in a personalized way and express their interests. I was fortunate to have Matt Milella, Director of Product Development for Oracle Business Intelligence Mobile Apps, and Jacques Vigeant, Product Strategy Director for Oracle Business Intelligence & Enterprise Performance Management, join me for a podcast to discuss their opinions about “The TOFU approach to business intelligence (BI)”.

Jacques explained that the article is basically about how BI has historically focused on what we refer to as the ‘business analyst’ or the ‘power user’. That’s the person in a company that has the unenviable task of analyzing data, finding trends, and synthesizing data into dashboards that he/she then shares with management. The common thinking, in BI companies, is that roughly 20% of the users prepare data that the ‘rest of us’ consume. There are many practical and technical reasons why BI started using this model 30 years ago, but the world of technology has come a long way since then. Today, the average user can do much more with much less help from IT.

Do you think that this article is interesting? Do you have any opinions? Thank you for reading. If you have any questions, send us a messageor leave a comment below.

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80 per cent of supply chain managers don’t believe their supply chain enables business strategy

Posted on by Teddy Nee

80 per cent of supply chain managers don’t believe their supply chain enables business strategy

Some eight out of 10 supply chain managers do not see their supply chain as an “enabler of business strategies” within their organisation, according to a survey.

The poll, conducted by Hitachi Consulting, also found 55 per cent do not regard their business’s supply chain as a “fundamental source of business value and competitive advantage” and 29 per cent see it as “purely an operational function”.

Cathy Johnson, vice president at Hitachi Consulting, said: “These figures are far from reassuring. For the most part, it seems that senior executives understand the strategic importance of the supply chain, yet the managers who deal with the supply chain on a day-to-day basis do not.

“A supply chain that doesn’t support the overarching business strategy, and which doesn’t deliver competitive edge – and which isn’t going to deliver a material change in performance over the next five years – is clearly not a desirable asset.”

The survey, involving 100 supply chain managers and directors from nine European countries, revealed almost half did not believe their organisation’s supply chain would deliver increased profitability over the next five years, just a third believed it would deliver an improved customer experience over the same period, and half did not think it would deliver a “reduced working capital requirement”.

What is your opinion? Write it below in the comment or contact us for discussion.

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Five Data Mining Techniques That Help Create Business Value

Posted on by Teddy Nee

Five Data Mining Techniques That Help Create Business Value

The term data mining first appeared in the 1990s while before that, statisticians used the terms “Data Fishing” or “Data Dredging” to refer to analysing data without an a-priori hypothesis. The most important objective of any data mining process is to find useful information that is easily understood in large data sets. There are a few important classes of tasks that are involved with data mining:

Anomaly or Outlier detection

Association rule learning

Clustering analysis

Classification analysis

Regression analysis

Data mining can help organisations and scientists to find and select the most important and relevant information. This information can be used to create models that can help make predictions how people or systems will behave so you can anticipate on it. The more data you have the better the models will become that you can create using the data mining techniques, resulting in more business value for your organisation.

If you have any opinion about how data mining help to create business value, post it in the comment box. And contact us for discussion.