Author Archives: @donaldmac

Static BI Adoption and a Proposed Solution

Cindi Howson of BI Scorecard has just published her annual “Successful BI Survey”* and the results are sadly all too familiar.

Once again BI adoption is pretty much static at 22% (a little down on last year’s 24%, but probably statistically flat)

As I have written about time and time again in this blog, my strong feeling is that the reason for this flat-lining of BI adoption is that we have saturated the “analyst” BI market and we are going about “end-user” BI in the wrong way (hint: force-feeding analyst BI to end-users has failed in the past and is not going to succeed in the future).

Over the past 10-15 years, the BI market has sold over and over to people who want to do their own analysis (think end-user query, ad-hoc BI, self-service reporting, data discovery, …) in essence each wave made it easier for the same people (analysts) to get better access to information.

Don’t get me wrong, analysts (and all  forms of analyst BI) have a key role to play in the BI strategy of any organization, but they make up less than half the picture (actually less than 25% of the picture given Cindi’s survey).

To get beyond 25% adoption, we need to consider the end-user who does not think in terms of analysis or data discovery, but just wants relevant information to drive their everyday activities.

The good news is that I can see momentum building towards a new, complementary approach.

Eric Vallo summed it up for me a few days ago on his blog. After pointing out that

“~80% of users … just want to be told what data to use to make a decision and … to go on their merry way”

he says that:

“The really innovative BI vendors are going to deliver tools that … make it RIDICULOUSLY EASY to proliferate BI to the masses so that it integrates into their day-to-day routines so that they don’t even know they are using BI”.

This is exactly what we are trying to do at Antivia. DecisionPoint empowers one set of people (BI professionals and analysts) to quickly and easily deliver ridiculously easy to use BI content to the wider end-user community, which in turn gives them information in the flow of their everyday business (as Timo Elliott is bored of me saying, just like the BBC weather site).

Another encouraging trend for us is that a number of our recent customers have bought DecisionPoint to “complement their Tableau implementation”. Tableau is the undisputed king (or queen) of Data Discovery, but these happy Tableau customers want something to work alongside their existing investment to distribute information more widely to the non-analyst community.

There is also cause for optimism in Cindi’s survey results. The number one BI priority for her respondents was “dashboards”, and interactive dashboard applications are the best way to deliver end-user BI. In addition, Cindi’s survey recorded a marked improvement in the adoption of Mobile BI (up to 48%). I bet a pound to a penny that this is because on mobile, most business users want their BI packaged in the style of a no-training required iPad app, which represents a move away from yet more “Data Discovery”.

To those who object to this because they feel that end-users should be building their own BI, I would say three things:

1)      Think of your sales team, do you want them building BI and “discovering” new things in the data or do you want them selling based on information which they can access  as easily as a weather forecast  (e.g. what to sell, where, to whom)

2)      Self-service BI should be like self-service food. Think about it, you are never shown into the kitchen in a self-service restaurant.

3)      There is a new wave of BI on the horizon, driven by the expectations set by consumer access to information through web sites, mobile apps – no need for analysis just quick, packaged access to information

Analyst BI in general and Data Discovery in particular are important but they are not enough, they need to be complemented by an alternative data delivery mechanism which is as easy to use as consumer information sources, available on desktop and mobile devices and quick and easy to build on top of existing corporate data stores. Something like DecisionPoint, why not request a test-drive to see for yourself?


*See here for Cindi’s summary of the survey or here to purchase the in-depth report.

Why have SAP gone Lumira mad ?

Is it just me or do SAP talk more about Lumira than all their other BI products put together ?

If I am right, then it is a little odd because when I have talked to people at SAP the strong message I get is that Lumira is a tool targeted at analysts, and analysts, I would argue, are a small minority of the potential BI users in an organization.

Despite some of the more outlandish claims in the market, we are NOT “all analysts these days”. The vast majority of us have jobs to do which involve running part of a business, and although we need data and information to do this, this does not make us analysts or suitable users for an analyst tool.

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The two key types of BI usage

Today, Timo Elliott at SAP tweeted that for BI:

“nobody seems to agree with me, but it’s not about the type of user, it’s about tasks”.

Timo I do agree, and yes it all comes back to the BBC weather site again :-)

Although you can sub-divide a thousand different ways, the most important distinction (if you want to deliver successful BI) is between “analyst BI” and “end-user BI”.

I know that sounds like types of user but actually it is not, it is about modes of usage and one user can use both of these at different times.

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A Visionary Example of the Future of End-user BI

My ex-colleague from BusinessObjects, Bill Schmarzo (that is his picture to the left), has just posted a blog entry (here) which should be compulsory reading for anyone in BI and especially for those who are working with BI and “big data”.

Let me explain why …

The opportunities opened up by “big data” are very significant and no-one should be ignoring them. Unfortunately, if you follow the hype in the market today at best you will only realize a small percentage of the value and at worst you will swamp your organization with inappropriate, time-consuming access to data they don’t actually need. Continue reading

“The war on self-service BI”

Mark Cooper (that’s his avatar on the left) posted a great article on the SAP Community Network (SCN) earlier in the week.

The title “the war on self-service” immediately drew me in as I have long advocated that self-service BI (in all its forms) is probably the biggest inhibitor to the wider adoption of BI in our organizations.

I was not disappointed. Mark summarizes the problem beautifully:

“The most commonly attempted [self-service] scenario in BI projects is … the one that I commonly see fail because the project tries to reduce reliance on IT and enable the business to do their own reporting”

Bingo! In a sentence, this is the reason we have had with too much BI shelfware and too little BI adoption for the last 15-20 years.

To explain, there are two issues: Continue reading

Something a little different – The Fuze

As a software company there is no more important skill to us than computer programming and at Antivia we are very fortunate to have a fantastic team of developers creating our products.

However, as others have observed over the last couple of years, as a society we are not doing as much as we should or could to encourage the next generation of programmers. In fact, you could argue that we have gone backwards on this over the last 30 years.

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Limits on mobile SAP Dashboard data volumes and how to avoid them

Would you like great performance, off-line capability and 50 times more data in your mobile SAP Dashboards ?

Last week Sarah Gou from the SAP Dashboards product team posted an article on mobile best practices for SAP Dashboards. It is a good read with a number of pieces of excellent advice for deploying successful mobile dashboards. Continue reading

Interactive Dashboards – where the BI puck is headed!

I am beginning to hope that Howard Aiken was right when he said :-

“Don’t worry about people stealing your ideas. If your ideas are any good, you’ll have to ram them down people’s throats.”

For a long time now (pretty much any of my other posts in this blog cover the idea in one way or another) I have been advocating the idea that ad-hoc / self-service is not the panacea for Business Intelligence which it is widely perceived. More recently this has evolved into the more constructive idea that interactive dashboards are the only form of BI needed for end-users.  Continue reading

Next-generation BI learning from the NBA HANA system

There was much discussion of advanced/predictive analytics and agile visualization in the tweet stream from the SAP Analytics briefing which Steve Lucas gave to analysts in New York last night (mainly via John Appleby, @applebyj) however, for me the biggest insight came from what the NBA are doing with HANA.

The underlying technical stuff was impressive, as John tweeted:

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Understanding BI Users

This post is an extract from our recent eBook “Why self-service BI fails and how dashboards provide the answer”.

To better understand the types of BI user within our organization we can classify them along 2 dimensions:


1. Activity Performed

This first dimension considers the type of activity being performed.  At one end are people performing the type of deep analysis supported by data discovery tools and the other extreme are those who prefer the simplicity of the ‘just click’ interface of a dashboard. Continue reading