Following on from my post Big Processes 5, in this post I will discuss the fourth and final type of Big Process - Remembering.
Remembering processes help organizations improve their operations.
Although most people know Santayana’s saying, “Those who cannot remember the past are condemned to repeat it”, few organizations live by this rule. Some organizations claim to have reached level 5 of the Capability Maturity Model:
“Optimizing - process management includes deliberate process optimization/improvement.”
http://en.wikipedia.org/wiki/Capability_Maturity_Model
However, few organizations apply this optimizing activity to knowledge work processes in any kind of structured manner. Typically, their “level 5″ describes how they approach routine, semi-automated processes, using techniques such as Lean and Six Sigma to reduce time and cost. It is now becoming recognized more and more widely that an equally great - some would say far greater - advantage can be gained from improving the way in which your most expensive staff collaborate to make and implement the decisions that determine how your organization operates.
Organizational memory must be extended beyond the factory floor and transaction processing, into the domain of Big Processes, and use of that memory made into a core part of business operations. Maintaining and leveraging memory is itself the final kind of Big Process.
Further, it cannot be too long before the same restrictions now placed on financial management - legal and statutory requirements for auditing, and implementation of security measures to prevent fraud - extend into knowledge work. To make this a reality, a sine qua non is the implementation of organization-wide Remembering processes for knowledge work.
Of course, it is almost impossible to record and analyze full details of how knowledge workers go about their business - to capture every text message, transcribe every phone call and fax, record every meeting, and so on, then place all this in context. To even attempt to do so would mean extending existing, and already cumbersome, Customer Relationship System (CRM) tools to breaking point and beyond. However, using a HIMS it is a simple matter to document the outcome of such business activities.
A HumanEdj Plan, for example, typically includes data fields that record key decisions made, along with any supporting contextual information. The work of the Plan is progressed by collaborating to update these fields, so their maintenance becomes a core part of the knowledge work itself, rather than an inconvenient extra task necessary after the day’s work is finished (as can be the case with CRM). As with ECM in the case study above, knowledge capture becomes a seamless and automatic part of daily activity.
Pilot studies are currently underway for the use of HumanEdj in healthcare. For example, consider the common case of a patient whose problem requires GP visits, specialist advice from multiple sources, and ancillary tests such as X-rays or MRI scans. This process, which may be urgent, is frequently held up not by lack of resources, but by the time required to arrange appointments, prepare and circulate test results, discuss findings among the various practitioners, and so on. It is the gaps between work that cause delays, and thus the consequent impact on patient well-being as well as extra cost.
However, it is a very simple matter to use a HIMS to streamline healthcare processes. HumanEdj Plans, for example, are created from Templates, which can be as minimal as desired - since each Plan is simple to extend during usage, without need for technical expertise. As the patient progresses through their treatment, they extend their own Plan to add the new clinicians who will treat them. Effectively, they manage the treatment themselves. A HIMS makes it possible to take the responsibility for progressing each case away from over-burdened healthcare professionals who are dealing with hundreds of cases each week, and to place it in the hands of the rightful “Plan owner”: the patient, who is not only highly motivated to conclude the case successfully but has enough time to do so.
Further, since Plans are automatically recorded in a repository, the clinicians involved and their managers are now able to examine past cases in order to learn from them. This is done by building higher-level Plans whose purpose is to improve operational work. Such a higher-level Plan may be used by the manager of a group of clinicians, who has access by default to the Plans that they have used. Alternatively, the higher-level improvement Plan may be more wide-ranging, and apply business intelligence techniques to Plans from across the organization. Plans can be inspected individually by using custom views to highlight points of interest - for example, all HumanEdj Plans are stored in a range of standard formats including the Web developer’s notation of choice, JSON. Alternatively, summary data can be harvested from a number of Plans and charts or reports created using tools ranging from Excel to specialist analytical applications.
Simply by doing their patient treatment via Plans, each healthcare organization involved gains the ability to look back at their work, with full context, and make informed decisions about how to improve their operations in future.
Finally, the complex, cross-boundary processes of healthcare typically require support from external systems for diagnosis, prescription, image analysis, and so on. Here a Task in HumanEdj may well be implemented via invocation of a Task in an ACM system - an expert system based on rules. By implementing the Big Process in a HIMS, the smaller-scale ACM process comes into its own, as a valuable aid to complex decision-making. As in the other examples above, placing HIMS at the top of the stack allows seamless integration of other high-value software tools.
[HumanEdj is available free]
Keith Harrison-Broninski is a researcher, writer, keynote speaker, software architect and consultant working at the forefront of the IT and business worlds.