Additional Considerations

Several disciplines emerging from other fields of IT, are starting to integrate with the BPM approach for mutual reinforcement. All of these disciplines either serve as input for the processes, or handle the output of a process, or are leveraged as activities with a process. For example, a social media event can trigger a process or business intelligence can leverage the information provided by process instances for different purposes, even starting new processes based on these results.

4.1.4.1 Social BPM

Social BPM presents itself in two distinct flavors. On the one hand, it uses Web 2.0 and Enterprise 2.0 style collaboration portals where participants can share and influence process design and certain decision making activities during process execution. This flavor has been renamed by Gartner in 2015 to Design-By-Doing. On the other hand, we also speak of Social BPM when we allude to leveraging the organization’s outward social media resources into internal business processes.

Nathaniel Palmer explains in “Passports to Success in BPM” that for Social Media, being one of Gartner’s Nexus of Forces, to influence and drive your process optimization effort, you need to embrace the two factors governing over it, namely trust and reputation. On Social Media you select your network not on experience or firsthand knowledge, but rather on these principles. Much as the grain trade in ancient Rome, when information on a product can’t travel faster than the actual product, trust becomes key in managing such flows. This leads to him determining three forms of social interaction:

 Social Modeling: let the process modeling and discovery in your organization be led by social media conventions

 Social Collaboration: using internal social networks to create virtual teams around activities and efforts

 Social Chatter: the Big Data of capturing social events and processing them to use as input for business determinations, and goal driven activities

4.1.4.2 Business Analytics

The process monitoring ensures that the organization has a trove of useful data on which to work in order to get further benefit from BPM. This data can be wielded in several distinct ways, the most common of which is business intelligence (BI), namely obtaining process-centric information for decision-making and planning of strategies and commercial and marketing actions. Performing detailed analytics on the information (both quantitative and qualitative) registered by the process instances, renders insight into a range of possible areas of interest, such as customer profiles, transaction trends, favorability of points of sales, etc.

An elaborated example of this is customer data and how it is positioned with respects to the ecosystem in which the organization operates. For example, this data can be used to predict and eventualities. Such customer data comes in four distinct flavors:

 Descriptive information: this includes the customer’s demographics, such as his name, address, gender, marital status, estimated household income…

 Behavioral information: this includes transaction information such as order information, payment history, and shipping addresses

 Interaction Information: this details when, where, and with whom interaction took place, what was communicated and what was the outcome.

 Attitudinal Information: this includes information on the opinions, preferences, perceptions, moods… that can be found internally in survey notes, email comments and open-ended inquiries typed into your website, or social media.

Illustration 4.1.13 – 360° Customer View (IBM)

Gartner stipulates that there are five technologies that currently prevail in the IT Operations Analytics market:

 Complex operations event processing: The application of expert system-like rules and filters to streaming operations data.

 Statistical pattern discovery and modeling: The automated construction of probability distributions that best-fit either streaming or persisted numerical operations data and the drawing of statistical and logical inferences from the probability distributions.

 Topology discovery and modeling: The automated discovery, presentation and smart scrutiny of complex logical system topologies, as well as the use of topological representations to illuminate numerical and textual operations data.

 Polystructured text search and text-based inference: The automated discovery of patterns, including key word identification, in polystructured text files (typically log files), as well as the search of and reasoning about lexical and semantic content based on those files

 High-dimension database modeling and analysis: The application of cube slicing and other multidimensional structural searching techniques to high-dimensional, structured operations data.

These technologies can then be leveraged into an efficient implementation of the discipline of Intelligent Business Operations (IBO). Gartner defines IBO as a style of work in which real-time analytic and decision management technologies (such as a Business Process Monitor) are integrated into the transaction-executing and bookkeeping operational activities that run the business. The basic idea is that BI and PM initiatives that support strategic decisions are two or more steps removed from business operations, and thus these analytics become a complementary source of input for these decisions. Organizations adopting a BPM Approach are very well positioned to analyze where real-time analytics and decision management can improve their business. But as with BPM, the impact of integrating real-time analytics into business operations and processes becomes instantly visible, as it changes the way people do their jobs. It grants a strong visibility into how a company is run, and what is happening in its external environments.

If we apply the principles of the OODA loop (Observe/Orient/Decide/Act) as popularized by John Boyd, the technologies listed above, can be mapped to each of the steps of the loop, as shown in the illustration below. After observing the data, an orientation phase based on that data should lead into deciding which actions to take in the current improvement or innovation track.

Illustration 4.1.14 – OODA Loop Applied to Intelligent Business Operations

4.1.4.3 Business Process Outsourcing

Business Process Outsourcing (BPO) is an approach where a selective number of processes are outsourced to a third party. The nature or depth of this partnership should be clearly defined as part of the process governance.

Depending on the strategic import, complexity, change frequency and process interdependence, the tightness of the partnership and in consequence the level of communication between the partners increases. We divide these partnerships into three intimacy levels:

 Contractual Partners: The partnership is guided by contractual arrangements and SLA’s resulting in minimum contact between the partners.

 Cooperative Partners: To successfully deal with process changes the level of communication is regulated and frequent

 Partners in Success: The two companies are utterly dependent on each other for success, resulting in a close cooperation and extensive communication.

Once the level of intimacy has been established, the need arises to assign assets of either partner on a per process basis. These assets are the adoption of the way of working, whose people will execute or manage the process, whose physical assets to use, and whose technology tools, use of partnerships for acquisition, etc.

It is of paramount importance that in BPO, regardless of the intimacy level, the companies set an escape hatch in case the relationship doesn’t deliver on its needs. A solid BPO approach set exit clauses in the contractual agreements, as well as stipulates a backup plan. At the very least, loss of information should be made impossible.