Business Intelligence: Sometimes a problematic term

I often find myself in between the world of military language and the completely different language used in the information technology domain. Naturally it didn’t take long before I understood that term mapping or translation was the only way around it and that I often can act like a bridge in discussions. Understanding that when one side says one thing it needs to be translated or explained to make sense in the other domain.

Being an intelligence officer the term Business Intelligence is of course extremely problematic. The CIA has a good article that dives into the importance of defining intelligence but also some of the problems. In short I think the definition used in the Department of Defense (DoD) Dictionary of Miltary and Associated Terms can illustrate the core components:

The product resulting from the collection, processing, integration, evaluation, analysis, and interpretation of available information concerning foreign nations, hostile or potentially hostile forces or elements, or areas of actual or potential operations. The term is also applied to the activity which results in the product and to the organizations engaged in such activity (p.234).

The important thing is that in order to be intelligence (in my area of work) it both has to gone through some sort of processing and analysis AND only cover things foreign – that is information of a certain category.

When I first encountered the term business intelligence at the University of Lund in southern Sweden it then represented activities done in a commercial corporation to analyse the market and competitor. It almost sounded like a way to take the methods and procedures from military intelligence and just apply it in a corporate environment. Still, it was not at all focused on structured data gathering and statistics/data mining.

So when speaking about Business Intelligence (BI) in a military of governmental context it can often cause some confusion. From an IT-perspective it involves a set of technical products doing Extract-Transform-Load, Data Warehousing as well as the products in the front-end used by analysts to query and visualise the data. Here comes the first issue of a more philophical issue when seeing this in the light of the definition of intelligence above. As long as the main output is to gather data and visualising it using Enterprise Reporting or Dashboards directly to the end user it ends up in a grey area whether or not I would consider that something that is processed. In that use case Business Intelligence sometimes claims to be more (in terms of analytical ambitions) than a person with an Intelligence-background would expect.

Ok, so just displaying some data is not the same thing as doing indepth analysis of the data and use statistical and data mining technology to find patterns, correlations and trends. One of the major players in the market, SAS Institute, has seen exactly that and has tried to market what they can offer as something more than ”just” Business Intelligence by renaming it to Business Analytics. That means that the idea is to achieve ”proactive, predictive, and fact-based decision-making” where the important word is predictive I believe. That means that Business Analytics claims to not just visualise historic data but also claim to make predictions into the future.

An article from BeyeNETWORK also highlights the problematic nature of the term business intelligene because it is often so connected with data warehousing technology and more importantly that only part of an organisation’s information is structured data stored in a data warehouse. Coming from the ECM-domain I completely agree but it says something about the problems of thinking that BI covers both all data we need to do something with but also that BI is all we need to support decision-makers. The article also discusses what analysis and analytics really mean. Looking at Wikipedia it says this about data analysis:

Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making.

The question is then what the difference is between analysis and analytics. The word business is in these terms also and that is because a common application of business intelligence is around an ability to measure the performance through an organisation through processess that are being automated and therefore to a larger degree measurable. The BeyeNETWORK article suggests the following definition of business analytics:

“Business analysis is the process of analyzing trusted data with the goal of highlighting useful information, supporting decision making, suggesting solutions to business problems, and improving business processes. A business intelligence environment helps organizations and business users move from manual to automated business analysis. Important results from business analysis include historical, current and predictive metrics, and indicators of business performance. These results are often called analytics.”

Looking at what the suite of products that is covered under the BI-umbrella that approach downplays that these tools and methods have applications beyond process optimization. In law enforcement, intelligence, pharmaceutical and other applications there is huge potential to use these technologies to not only understand and optimize the internal processes but more importantly the world around them that they are trying to understand. Seeing patterns and trends in crime rates over time and geography, using data mining and statistics to improve understanding of a conflict area or understanding the results of years of scientific experiments. Sure there are toolsets that is marketed more along words like statistics for use in economics and political science but those applications can really use the capabilities of the BI-platform rather than something run on an individual researchers notebook.

In this article from Forbes it seems that IBM is also using business analytics instead of business intelligence to move from more simple dashboard visualizations towards predictive analytics. This can of course be related to the IBM acquisition of SPPS which is focused on that area of work.

From the book written by Davenport and Harris, 2007

However, the notion of neither Business Intelligence nor Business Analytics says anything about what kind of data that is actually being displayed or analyzed. From a military intelligence perspective it means that BI/BA-tools/methods are just one out of many analytical methods employed on data describing ”things foreign”.

In my experience I have seen that misunderstandings can come from the other end as well. Consider a military intelligence branch using…here it comes BI-software…to analyse incoming reports. From an outsider’s perspective it can of course seem like what makes their activity into (military) intelligence is that they use some form of BI-tools and then present graphs, charts and statistical results to the end user. Resulting from that I have heard over and over again that people believe that we should also ”conduct intelligence” in for instance our own logistics systems to uncover trends, patterns and correlations. That is wrong because an intelligence specialists are both skilled in analytics methods (in this case BI) and the area or subject they are studying. However, since these tools are called Business Intelligence the risk for confusion is high of course just because of the Intelligence word in there. What that person means is of course that it seems like BI/BA-tools can be useful in analysing logistics data as well as data of ”things foreign”. A person doing analysis of logistics should of course be a logistics expert rather than an expert in insurgency activities in failed states.

So lets say that what we currently know as the BI-market evolves even more and really assumes a claim to be predictive. A logical argument on the executive level to argue that the investment must provide something more than just self-serve dashboards. From a military intelligence perspective that becomes problematic since all those activities does not need to be predictive. In fact it can be very dangerous if someone is let to believe that everything can be predictive in contemporary complex and dynamic conflict environment. The smart intelligence officer rather need to understand when to use predictive BI/BA and when she or he definitely should not.

So Business Intelligence is a problematic term because:

  • It is a very wide term for both a set of software products and a set of methods
  • It is closely related to data warehousing technology
  • It includes the term intelligence which suggests doing something more than just showing data
  • Military Intelligence only covers ”things foreign”.
  • The move towards expecting prediction (by renaming it to Business Analytics) is logical but dangerous in a military domain.
  • BI still can be a term for open source analysis of competitors in commercial companies.

I am not an native English speaker but I do argue that we must be careful to use such as strong word as intelligence when it is really justifiable. Of course it is still late for that, but still worth reflecting on.

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Can BPM meet Enterprise 2.0 over Adaptive Case Management?

The project that I am running at JCDEC involves a lot of internal ”marketing” targeting both at end users and people in charge of our IT-projects. Lately I have found myself explaning the difference between Workflow processes using Documentum Process Engine and Taskspace and what EMC’s new clients Centerstage Pro and Media Workspace. My best argument so far has been that BPM/Workflow is well suited for formal repeatable process in the HQ while Enterprise 2.0 clients takes care of ad-hoc and informal processess. Keith Swensson explains the Taylorism-based Scientific Management-concept as the foundation of Business Process Management in this blogpost in a good way. He continues to provide a bridge over to ad-hoc work that nowadays is done by what is called Knowledge Worker. Documentum Centerstage is a tool that is intended for the Knowledge Worker which also can be seen as the Enterprise 2.0 way of working.

However, Keith continues to steer us over to a concept called Adaptive Case Management which is supposed to address those more agile and dynamic ways of working as a contrast to slow-changing well-defined business processess that is deployed in traditional BPM-systems. To my understanding this focuses a lot on the fact that the user itself (instead of a Process designer) needs to be able to control templates, process steps and various other things in order to be able to support more dynamic work such as criminal investigations or medical care.

However, Adaptive Case Management is also a concept (I understand) in the book called ”Mastering the Unpredictable”. The idea is to focus on the unpredictable nature of some work situations but also reflect a bit over to what degree things are unpredictable or not. In this presentation by Jacob Ulkeson the argument is that the main bulk of work is unpredictable and therefore also means that Process Modeling using traditional BPM most likely won’t work.

Some people have opinions that there is no need to redefine BPM and that all these three letter acronyms does not contribute much to the understanding of the problem and the solutions. I think I disagree and the reason for that is that there are no silver bullet products that covers everything that you need. Most organisations start somewhere and rolls out systems based on their most pressing needs. I believe that these systems have some similarities in what they are good and bad at. Having bought an ECM, BI, CRM or ERP-system usually says something about what business problems have been addressed. As SOA-architectures matures and the ambition to reduce stove-pipes increases it actually means that the complementary character of these systems matter. It also matters which of these vendors you choose because the consolidation efforts into a few larger vendors means choosing from different approaches.

To me all of this means an opportunity to leverage the strong points of different kind of platforms. Complex sure but if you have the business requirements it is probably better than building it from scratch. So I think when companies quickly rolls out Enterprise 2.0 platforms from smaller startup vendors they soon discover that they risk creating yet another stove-pipe but in this case consisting of social information. Putting E 2.0 capabilties on top of an ECM-platform than makes a lot of sense in order to be able to integrate social features with existing enterprise information. The same most likely goes for BI, CRM etc.

When it comes to BPM the potential lies in extending formal processess with social and informal aspects. However, it is likely that the E 2.0-style capabilities make new ways of working evolve and emerge. Sooner or later they need to be formalised maybe into a project or a community of interest. Being able to leverage the capabilties of the BPM-platform in terms of monitoring and some kind of best practice in form of templates is not far-fetched. To some degree I believe that Adaptive Case Management-solutions sometimes should be used instead of just a shared Centerstage Space because you need this added formal aspects but still want to retain some flexibility. Knowledge Worker-style work can then be done on top of a BPM-infrastructure while at the same time utilising the ECM-infrastructure for all content objects involved in the process. Having a system like Documentum that is good at content-centric human workflow processes makes a lot of sense.

So is the Documentum xCP a way to adress this middle-ground between Process Modeling-based processes and Knowledge Worker-style support in CenterStage? The mantra is ”configure instead of coding” which implies a much more dynamic process. I have not played around with xCP yet – we have so far only deployed processes developed from scratch instead of trying out the case management templates that comes with the download.

Not all companies want to do this but I think some will soon see the merits of integrating ECM, BI, E.2.0 and BPM/ACM-solutions using SOA. The hard part I belive is to find software and business methods support for the agile and dynamic change management of these systems. The key to achieve this is to be able to support various degrees of ad-hoc work where on one the user does everything herself and on the other way a more traditional developer coding modules. Being able to more dynamically change/model/remodel not only processess but also the data model for content types in Documentum is a vital capability to be able to respond to business needs in a way that maintains trust in the system. This is not a task by IT but something done by some kind of Information and Knowledge Management (IKM) specialist. They can get some proper means of doing their work using this SOA-based integration of different sets of products.

So employ E 2.0-style features in Task Management clients and make sure that E 2.0 style clients include tasks from BPM/ACM in their activity streams or unified inboxes. Make sure that all of this is stored in an ECM-platform with full auditing capabilities which needs to be off-loaded to a data warehouse so it can be dynamically analysed using interactive data visualisation, statistics and data mining. I hope we can show a solutions for that in our lab soon.

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Dave Kellogg on Palantir

I recently began reading the blog written by Dave Kellogg who is the CEO of Mark Logic, a company devoted to XML-based content management. I think I came to notice them when I discovered what cool technology EMC got when it bought X-hive which has now become Documentum xDb/XML Store. Mark Logic and X-hive was of course competitors in the XML Database market. In a recent blog post he reflects on the Palantir product after attending their Government Conference.

The main scope of his blog post is around different business models for a startup and that is not my expertise and I don’t have any particular opinion around that although I tend to agree and it was interesting to read his reflections of how other companies such as Oracle (yet another competitor to Mark Logic and xDb) have approached this.

Instead my thinking is based around his analysis of the product that Palantir offers and how that technology relates to other technology. I think most people (including Kellogg) mainly view Palantir as a visualisation tool because you see all these nice graphs, bars, timelines and maps displaying information. What they tend to forget is that there is huge difference between a tool that ONLY do visualisation and one that actually let you modify the data (actually modifying contextual data around them such as metadata and relations) within those perspectives. There are many different tools around Social Network Analysis for instance. However, many of them assumes that you already have databases full of data just waiting to be visualised and explored. Nothing new here. This is also what many people use Business Intelligence toolkits for. Accessing data in warehouses that is already their, although the effort of getting there from transactions oriented systems (like in retail) is not small in any way. However, the analyst using these visualisation-heavy toolkits access data read-only and only adds analysis of data already structured.

Here is why Palantir is different. It provides access to raw data such as police reports, military reports, open source data. Most of it in unstructured or semi-structured form. When it comes into the system it is not viewable in all these fancy visualisation windows Palantir has. Instead, the whole system rests on a collaborative process where people perform basic analysis which includes manual annotations of words in reports. This digital marker pen allows users to create database objects or connect to existing ones. Sure this is supported by automatic features such as entity extraction but if you care about data quality you do not dare to put them in automatic mode. After all this is done you can start exploring the annotated data and linkages between objects.

However, I do agree with Dave Kellogg that if people think BI is hard, this is harder. The main reason is that you have to have a method or process to do this kind of work. There are no free lunches – no point of dreaming about full automation here. And people need training and mindset to be able to work efficiently. Having played around with TIBCO Spotfire lately I feel that there is a choice between integrated solutions like Palantir which has features from many software areas (BI, GIS, ECM, Search etc) or using dedicated toolkits with your own integration. Powerful BI with data mining is best done in BI-systems whereas they probably never will provide the integration between features that vendors like Palantir offers. An open architecture based on SOA can probably make integration in many ways easier.

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