Data Analytics in Enterprise Architecture

In the prezi “Relating TOGAF ADM to other IT related Methods” I highlighted the relation between TOGAF and other IT Standards (COBIT, ITIL, PRINCE2 and CMMI). Unfortunately current software tools supporting these standards are not seamlessly integrated. Information locked in one tool is not easily accessible to the other tools. Hence data cannot be analysed appropriately despite the correlation and synergy of the data stored in the various tools.

With the acquisition of Alfabet by Software AG and Troux by Planview as well as the current offerings of other independent software tool manufacturers to support Enterprise Architecture, one can hope to see improvements towards integral tools supporting the various IT standards mentioned above.

As this tool integration process matures, the values of Enterprise Analytics can be leverage to collected integral, correlated data facilitating the development of an advanced CIO Dashboard. Leveraging Enterprise Data Analytics at the core of IT (in the architecture of any enterprise) will change the game of Business/IT alignment.

While IT has been providing enterprise data analytics to other departments such as marketing, customer and partner relations management, IT has not been at the forefront of using Enterprise Data Analytics in driving the business of IT within and/or across enterprises and industries. This should be at the core of any implementation of the IT4IT™ Standard  towards realising the Vision of Boundaryless Information Flow™.

Another challenge in the uptake of modelling in the era of IoTx

The development of modelling standards has reached a maturity level where Model Driven Development – MDD can drive productivity in the entire System Development Life Cycle – SDLC, but the uptake of these standards in industrial production has been lagging despite the current wave of developing Internet of Things – IoTx.

The evolution of IoTx is and will drive industrial development for at least the next twenty years. And the value of modelling in the era of IoTx has been emphasised in the many reports on “Industrie 4.0” (Cyber-Physical Systems). The lagging in the uptake of modelling in the integral development of products and systems is in my humble opinion due to overcoming the challenge of promoting knowledge on modelling amongst managers and directors (decision makers).

In the light of quarterly thinking (short term evaluations) investments in long term value generators such as taking up modelling standards are generally postponed or cancelled in organisations managed and directed by decision makers lacking adequate knowledge on modelling. The consequence is a crawling pace in unleashing the values of modelling in an era of highly computerised production of cyber-physical systems.

In this IoTx era, standardisation across the entire production chain is the catalyst to speed up production. If a bead on the chain is not in alignment with the standards used, a bottleneck impacting production time is created. Projecting this understanding to the introduction of state of the art modelling standards into established business as usual processes, it becomes obvious that decision makers must be involved in the management and direction of this feat. But what do you expect, when directors and managers are not knowledgeable in modelling and lack the will to focus resources on developing that knowledge.

After a demonstration of some use case scenarios of IoTx, a director asked a question shedding light into this challenge. The question was: “How long does it take to model such a use case, can it be done using MS Office tools?” In a side conversation another question was frequently asked: “How can I leverage IoTx in my organisation, I cannot get a sponsor without showing the ROI?

To the first question, my response was: The speed of modelling depends on the proficiency in the modelling language, as well as knowledge of the modelling tools and the (system) context being modelled. In elaborating on the response, it became evident that the current versions of MS Office tools are not appropriate in unleashing the value of modelling in the era of IoTx.

To the second question, my response was: A collaborative effort will be required to develop a common understanding of the respective organisational context, before an adequate value proposition can be tailored. The key question is: When is who going to commit human and financial resources to address this challenge?