• Vendor X sells its ERP to a company in Healthcare;
• Client wishes to setup its informational environment (data sharing, BI, CPM etc..) right from the start;
• Vendor X pushes the 'standard' solution' they sell;
• Client decides to decouple their informational environment from its source(s) for several reasons (heterogeneous sources, sustainability, compliance, adaptability etc..);
• Vendor X deploys their ERP;
• Client starts to design and build the informational environment;
• Interfaces between ERP of vendor X and the informational environment are developed;
• The ERP of vendor X off does not offer functional interfaces ('X keeps pushing their standard product'), so client needs to connect on the physical level;
• Going-live is near; of both the ERP and the new informational environment

Business Intelligence vendors seem to embrace collaboration (I am still struggling whether this software is any different from the groupware we had in the 90's) . As an example please take a look at SAP streamwork at youtube. I am gonna be blunt here; this type of software is completely useless, unless the organization is willing to fundamentally change its decision making process.

Let me try to make my point here with the help of giants like Galbraith, Daft, Davenport and some..

There are basically two information contingencies; Uncertainty and Equivocality.

• Uncertainty can be defined as the absence of information (e.g. Shannon and weaver) and can be overcome by simply asking the right question. The answer is out there.....
• Equivocality is an ambiguity, the existence of multiple and conflicting interpretations about an organizational situation. Participants are not even sure about the questions that need to be asked, let alone the answers they need. I think this can also be regarded as 'wicked problems'.

Now, for overcoming uncertainty you can suffice with relatively blunt instruments. Reporting and the ever increasing possibilities in analytics really shine in reducing uncertainty.

Now, for overcoming Equivocality the Business Intelligence stuff like reporting and even analytics have diminishing usage. You need more 'richness' in the tooling. And with tooling I don't necessarily mean software. Examples of more rich tooling are group meetings, discussions, planning, creative (group) thinking, etc..Simply put; you need face-to-face contact.
 
Davenport wrote an article about 'Make Better Decisions' in the Harvard Business Review in 2009. He is advocating a more formalized approach towards decision making:

'Smart organizations can help their managers improve decision making in four steps: by identifying and prioritizing the decisions that must be made; examining the factors involved in each; designing roles, processes, systems, and behavior to improve decisions; and institutionalizing the new approach through training, refined data analysis, and outcome assessment.'

Davenport, in my opinion, is aiming towards the equivocality and a more formalized method of coming to an outcome. And frankly, I like it a lot. But organizations need to really be willing to change its decision making process. And this is a major organizational and cultural change in my opinion. If organizations are really committed (Davenport is naming a few of those companies - like Chevron, The Stanley Works) in making this change, collaboration software has the potential to shine in supporting such a decision making process.

I am however afraid that collaboration software from BI vendors will be sold as candy with the promise of better decisions. And that is just bullshit and my prediction is that it will fail big time. 
 

What we all knew was true, but could not get across to management, is now more scientifically proven. The decision process regarding the outsourcing of a DSS is influenced by significantly other characteristics, when compared to OLTP. If you are interested in the details, the theory and the underlying data, please read:

Factors considered when outsourcing an IS system:an empirical examination of the impacts of organizations size, Strategy and the object of a decision (DSS or OLTP).

B.Berg and A.Stylianou in the European Journal of Information systems (2009 18, 235-248)

I still encounter organizations who are stuck in the OLTP world, even when the object of decision regarding outsourcing is completely different on many dimensions. They tend to use the same decision process regarding the outsourcing as they always did...whether they outsource an ERP, a CRM system a data warehouse or a more elaborate BI system.

Lately I come across vendors of OLTP systems that engage highly in tied selling. Now - if there is complete transparency to the customer- this is off course no problem. But, the sad thing is, this transparency is usually extremely bad or even non existent. 

This tied selling combined with (complete) lack of transparency has caused severe damage to the economy as we have seen especially in the financial sector. In Europe the European Commission is highly active in forcing vendors to stop tied selling (for example Internet Explorer and the OS of Microsoft). Vendors receive huge fines if they engage in these practices.

Unfortunately these practices are also quite mainstream in the data exploitation industry.

Yep - bringing up an oldie, but still o so true.

Financial assets: A single Euro can only be spend once.....

Human captial: They can just walk out of the door and leave or be hunted by your competitor

Not so with your data; It is uniquely yours, closely connected to your business language, full of nuance, in the proper context and the ability to procreate new data. Every organization can use it's data differently to create it's own niche. When data is used by anyone in your organization, it will not be consumed and it will not expire (a patent will). There is simply no other asset that anyone can think one that owns these capabilities.

To make the case even stronger; the movement of data in your organization is your lifeblood. Any company will simply seize to exist if this data is of bad quality. Orders will not get through, customers credit information can not be seen and invoices can not be send.

Another fascinating attribute of data is that it defines the other assets; financial data, property data, employee data. Badly managed data will jeopardize the management of the other assets big time. So, it's kind of a 'super', ultimate asset.

Nicholas Carr wrote in 2003 in the Harvard Business Review 'IT doesn't matter'. Systems, infrastructure, services, hardware, software, ERP...whatever...they will and probably are already commodities. They are not a differentiating factor in competitive advantage, sustainability or reliability.  Data is however always unique, competitors can not get hold of it (well....unless you got a security problem) and if they got it, it will probably be hard to use, since data is often very closely linked to the organizational lingua franca.

Data must be nurtured, managed aggressively and - most of all- must be enabled to be exploited to the max in order to get a good return.It is by far the ultimate proprietary asset.

I believe that in business nowadays huge amounts of money are spend on very sophisticated technology, financial controls and process management  (the process taliban). The marginal returns from ever increasing investments into these developments will be small. Investments in data are quite the opposite. The opportunities are limitless. And, more importantly, any investment you make is proprietary to your organization. This is the true definition of competitive advantage. 

This posted is inspired and sometimes quoted by T.Redman and his book 'Data Driven'

July 2007 I had a first aquantaince with Dan Linstedt - via LinkedIn.
I worked for a large government organisation as the architect for Data
Warehousing and Business Intelligence. I seriously considered Data
Vault as the standard methodology for the Enterprise Data Warehouse. I
worked for over 2 years for this govenment organisation and my choice
for the Data Vault is still a very good one.

November 2007 I got
Dan Linstedt to the Netherlands and got the first 27 peeps trained and
certified of that same government organisation. I had dozens of
discussions with architects, management, developers, etc...but in the
end the consensus on choosing Data Vault was huge.

Since november
2007 Data Vault sky rocketed in the Netherlands. Together with the
Genesee Academy and DNV I think we certified over 200 people and I dare
to say that most new EDW projects nowadays in the Netherlands have
chosen Data Vault as the prime methodology.

Before I get
criticised for sanctifying one methodology despite the various (non)
functional requirements; I do believe that ANY architecture needs to be
in line with the business-, application- and technical architecture. So
choosing one methodology on forehand is just plain wrong. There has to
be sound justification and alignment for any choice in your
architecture. Whether it's a tool, a methodology or whatever.

Since
2 years we (Genesee Academy, me, DNV) certified over 200 people - most
of them extremely seasoned and respected experts in our field. On
average these consultants are very critical on any new 'trick in the
book'. I dare to say that most of the experts that were certified were
convinced that Data Vault has got extreme value and potential. The
proof of the pudding is in the eating; Data Vault got many
implementations in the Netherlands the last two years and it's growing
fast.

I am confident that Data Vault in the years to come will hit Europe as hard as it has hit the Netherlands.

But
I wonder......I and am still baffled by it. The attention for Data
Vault in the United States is extremely limited, why is that? Even a
respected institute as TWDI is not paying much attention. Why? Experts
in the field do not mention Data Vault what so ever. I just don't get
it. Can anybody enlighten me?

For those of you not familiar with Data Vault --> read my articles.

In the 'Neverland' of decision support, Business Intelligence has completely taken over all attractions.

Let's name a few; BI, Neuro BI, Ambient BI, Sentient BI, Process driven BI, process Intelligence, Pervasive BI, BI 2.0, BI as a Service, BI for SOA, SOA for BI, Mobile BI, google BI, Personal BI, BI-Tools-where-you-do-not-need-a-DWH-and-ETL-Buy-it-now, Mashups-the-new-BI-Desktop (oh my god), BI-in-the-box,Business Analytics,BI-in-the-cloud (love this one!), BI-virtualization, Agile-BI,Operational-BI,Decision Intelligence, Decision Management, Even driven analytics, Complex Event Processing, BAM, Collabarative Decision Making......

Do not get me wrong; I certainly do not dismiss them all.....just most of them :)

Most of these 'attractions' are highly sponsored, look super-dooper on the outside and if you won't sit in them you will loose out big time (so they say). However, when you finally decide to ride them you feel that they are not that stable, not really safe and there is hardly any enjoyment when you exit them (but you can tell you neighbour you dared to ride it!). To put it in other words, not really grounded in theory and the relevance for practice is extermely hard to find.

There are however some attractions in this Decision Support 'Neverland' that are very much dusty, spiderwebs all over the place, but the attraction is still extremely solid and if we would overhaul it with new architectural insights and technology, it could be a smash-hit. These attractions are named DSS, EIS, ESS.... 

I feel that we - as an industry - failed miserably in continuing on the path that was made for us by people like John Dearden, John Rockart, David Delong, Ralph Sprague, Hugh Watson, Steven Alter, Daft and Lengel, Peter Keen, Michael Scott Morton, Herbert Simon, Henry Mintzberg and many more.

Dan Power is one of those brave souls who is standing with the ticketbox - selling tickets for his 'attraction'. I recommend people to read his last written article as well as the blog post written by Wouter van Aerle.

Finally, I wanna contribute to the Decision Support 'Neverland': BI goes Retro

In 1986 Daft and Lengel published an article in Management Science:

ORGANIZATIONAL INFORMATION REQUIREMENTS, MEDIA RICHNESS AND STRUCTURAL DESIGN.

A very interesting article that combines the processing of information by decision makers, the use of structural mechanisms and organizational design. The latter one - organizational design - I will not discuss thoroughly in this blog. Just remember that the choice of structural mechanism to overcome uncertainty/equivocality will impact the organizational design.

It is only by means of good and respectfull discussion that knowledge
and insight will evolve. This post should be regarded as such.

This post is a second reaction to the first article in a series of three
which were written by a highly respectfull thoughtleader in the field
and publisher on the B-Eye-Network; Rick van der Lans. The papers are
titled 'The Flaws of the Classic Data Warehouse Architecture'.

This blog post is a reaction to the first part. It deals with the flaws of the classic data warehouse architecture (CDWA).

Rick signals five flaws which will lead in article two and three to a new architecture. This post is addressing the second flaw.

- My reaction to flaw #1 can be read here
- My reaction to flaw #2 can be read here

Flaw 3 according to Rick
Rick signals the need to do analytics on external data and on datastores that are unstructured. I quote Rick: 'Most vendors and analysts propose to handle these two forms of data as follows: if you want to analyze external or unstructured data, copy it into the CDW to make it availablefor analytics and reporting'. Ricks is wondering why? Unstructured data can be 'handled' on the source and external data can be done by mashup tools.

My reaction to flaw 3
Where are these vendors and analysts that propose to copy unstructured data into the CDW? I do not know them....really I don't. And if they exist - I agree with Rick; don't do it. Especially for the unstructured data I think other architectural choices are more optimal at the moment. But where is the flaw in the CDWA architecture? The CDWA was not meant for unstructured data and still is not. I still do not see the flaw...

But for the external data, I really believe in the years to come that there is still a solid business case of getting this data into your data warehouse. Sure enough - especially for more situational BI - mashups offer very fast time to market for new informational products. Although I believe the securtity issue is not to be underestimated as well as the need to perform analytics on the combinations of internal and - multiple sources of - external data.  

Mashups also need solid architectures.......

So:
- I challenge the notion that the vendors and analysts in data warehousing massively propose to put unstructured data in the DWH. The CDWA was not meant for that purpose. Not a flaw.
- There are solid business cases for getting your external data into your DWH. The CDWA is still a valid approach. Not a flaw.
- Mashups - as is new (BI) technology in general - surely offer new features and promising functionality.