Dear Mathias,

As you have indicated, Data has been anointed as the Oil of the new millennium. Modern strategists have elevated Data to the status of 4th factor of production after land, labor and capital. Given the volume, velocity and variety of data, knowledge extraction from new-age data has a complexity, which one would not have associated with data processing a decade back.

Before mapping data to business and planning BPM, one needs to organize data along a few vectors. The vectors are:

1. Location-aware data

2. Person-aware data   &

3. Context-aware data

Then for each of these streams, one has to look at what are the key factors and sub-factors that drive data collection, processing and storage. Some of the factors are:

1. Cost [Storage Cost, OPEX Cost, TCO, resource cost etc]

2. Technology [Are you going to use cloud for data storage]

3. Speed of processing [Data throughput Management]

4. Value adds from additionally processed data [like Visuality of data]

Mapping these vectors together would be useful in understanding the complete nuances of modern data and its involved processing.

Dear Mathias,

As you have indicated, Data has been anointed as the Oil of the new millennium. Modern strategists have elevated Data to the status of 4th factor of production after land, labor and capital. Given the volume, velocity and variety of data, knowledge extraction from new-age data has a complexity, which one would not have associated with data processing a decade back.

Before mapping data to business and planning BPM, one needs to organize data along a few vectors. The vectors are:

1. Location-aware data

2. Person-aware data   &

3. Context-aware data

Then for each of these streams, one has to look at what are the key factors and sub-factors that drive data collection, processing and storage. Some of the factors are:

1. Cost [Storage Cost, OPEX Cost, TCO, resource cost etc]

2. Technology [Are you going to use cloud for data storage]

3. Speed of processing [Data throughput Management]

4. Value adds from additionally processed data [like Visuality of data]

Mapping these vectors together would be useful in understanding the complete nuances of modern data and its involved processing.

Dear Matthias,

my answer might be too simple:

Information is used to make decisions in processes. Therefore Big Data can

supply relevant additional Information in the decision steps of Business processes.

There are two typical directions that I look for when trying to support decision steps in processes:  

- relevant internal information ("hidden" in internal Information Systems that are not enough integrated, yet); e.g. genetic footprint of a Patient or parts of it through which

I can get additional information what normally happens to this type of patients 

- relevant external Information; (externally availlable information that broadens my decisions information base) e.g. external statistics about mortality rate.

Best regards,

Thomas 

Hi Mathias:

One may view any Process as being made up of an Input (to the Process), the Process itself, followed by an Output (from the Process) -- i.e., using the familiar IPO terminology. The same applies to a chain of processes where the output of a Process feeds into another Process as its input. Analyzing Big Data is in itself a Process (with its own Input(s) and Output(s)). The BPM charter, therefore, must encompass the management of any such Big Data Analytics (BDA) process an organization undertakes along with managing other processes in the process chain that includes BDA. Further, these organizations have been managing, each in its own way, Small Data Analytics/Medium Data Analytics, so to speak, before embarking on BDA. The needed adjustments are already being made successfully by some firms in some contexts (e.g., Lenovo with real-time Social Media Analytics). The question then is whether what management a firm like Lenovo is able to successfully pull off, necessary and possible for other organizations operating in other environments. We can quickly see that the answer is probably "no." All BDA, for example, is not necessarily Streaming Data BDA. Thus, one would have to look for nuanced answers applicable to different contexts -- there probably is no general way of organizing the connection of moving analytics to action. The Data Sources involved, the Data Volume involved, the Data Velocity involved, the Data Variety involved, the Data Veracity involved, and the Data Analytics involved, would vary from one context to another.  I think, therefore, that your question would be better approached from multiple real or hypothesized perspectives/contexts.

Dear @Mathias, I am attaching a link that is related to your thread! "The big data trend opens up BPM to new data sources and opportunities to analyze processes more deeply and simulate potential improvements. But doing so successfully takes planning and cooperation among decision-makers in IT and business. It also requires collaboration with subject domain experts, from user-experience designers to technology vendors assisting implementations."

http://data-informed.com/what-big-data-means-to-bpm-more-event-sensors-process-simulations/

Ljubomir:

Thanks for the attached article .....

Thanks! Great input.

Does anybody have examples how Big Data improved operational business processes?

Hi see my article about Social Physics, a book by Alex Pentland.I do believe that big data and social physics will change in a deep way theories and methodology of BPM.

Mathias, where I feel we have an opportunity for big data integration with Business Processes is in expanding our boundaries or areas of influence to help with additional changes and/or modifications to our processes by inputting new data from new sources.  Just having big data doesn’t guarantee this will happen unless you open up the discovery features of your processes to adapt to big data.  I feel that when we get natural language algorithms to the point of helping us find patterns within our data that fit our process needs we won’t be able to utilize fully the big data features that are being touted.  The marriage of these capabilities will change everything we do today and will foster self-organization to new levels.  The next phase will be trust between the data and the processes owners.  This trust issue already exists with big data now, but it will get much more serious play as we go forward.  Therefore, there are many avenues to further this discussion including Information Assurance.  I know this is opening up another can of worms, but as you think through the processes involved, it leads you to the many facets that well be needed to be resolved.  Good luck.

I tend to organize BIG data geographically, and then you would see patterns emerged from BIG data; see the following examples:

Jiang B. (2015a), Head/tail breaks for visualization of city structure and dynamics, Cities, 43, 69-77; Preprint: http://arxiv.org/ftp/arxiv/papers/1501/1501.03046.pdf

Jiang B. and Miao Y. (2014, accepted), The evolution of natural cities from the perspective of location-based social media, The Professional Geographer, xx(xx), xx-xx, DOI: 10.1080/00330124.2014.968886,  Preprint: http://arxiv.org/abs/1401.6756