The Value of Case Management Today

Case management is popular today as many processes are already in place to handle repetitive work leaving most of the remaining work, about 70%, as unstructured or emergent and hard to put into a crisp process even if the process has some adaptability capabilities. The real value of case management is for work that requires collaboration and various types or levels of knowledge. Cases typically run longer than straight through processes because multiple skill-sets and knowledge bases are necessary to call a case complete.  While individual activities can act in parallel, eventually completion requires multiple parties.Typically the kind of cases that are seen in organizations today fall into five key major categories, but there are variants.

Service Request Cases

Investigative Focused Cases

Incident Focused Cases

Decision Intensive Cases

Hybrid Cases

Case Management Encourages Knowledge Collaboration for Goal Attainment

Case management, particularly adaptive case management, enables knowledge worker collaboration to reach evolving goals as a team. This is needed because work, cases in particular, have become more complex and perfect knowledge is not available in one job role or person to handle a case. There are five kinds of collaboration that I have observed in my work life and are enumerated below

Unstructured Communication:

Most collaboration happens in things like social media, email and through texts. While this gets the job done, sometimes, it doesn't get captured for reuse and future leverage. If we are working together to reach today's goals and really don't intend to help others downstream, this is a great approach. However, in the interest of capturing gems of wisdom, there are additional approaches.

Enabled Conferencing:

Quite often one to one communications, captured or not, are not up to the task of solving complex and complicated cases. This often requires "brain storming" in a group fashion to "noodle through" difficult, event patterns, decisions and appropriate actions in a speedy fashion. This may require "in person", audio and video conferencing where content (images, voice, image and video) can be shared in a cooperative understanding session. This helps understanding the semantics, semiotics and dimensions of complex work, agree on actions and glean cooperative commitment to the solution.

Coordinated Activity:

While independent activity such as communication and conferencing can solve complex cases, the process is quite haphazard in attaining goals. If this goals are coordinated and driven to in a milestone fashion with proper recording of activity and history, there can be value carried forward for future cases and patterns of success. This is especially true when the milestones are not carved in stone and they can flex as cases progress. This where adaptive case management leverages a technical assist.

Leveraging Community:

Often organizations are only focused on the resources that they directly control with salary and employment contracts. While there is some sense in this practice, sometimes cases need to tap into worlds that the organizations do not have the knowledge or skill. Even if the organization has all the knowledge and resources, they may not have the bandwidth to handle the work. This where stringers, communities and public cognitive surplus can be leveraged to the advantage of case resolution and positive organizational outcomes. This approach usually interjects a new level of security and responsibility, however.

Better Practice Guidance:

Often knowledge workers are left to their own experience and judgement as to how to approach a case that may be growing in complexity over time. While it is good to have experienced resources, there are assists that work for both the uninitiated, the normal knowledge worker and the expert. Identifying better practice patterns should be the goal of organizations where the work varies greatly and the kind of cases are still emerging. By analyzing better practices and rating results in the light of goal attainment can give your knowledge workers several alternative paths for success. This could be at a large grained level or as fine grained as to identify great collaborative patterns between resources.

Organizations will need to practice all five of these collaboration approaches. The wisest organizations will define when and where each style is used. As work gets more complex and as processes aim for larger "end to end" scopes there will be a mixture of knowledge work and routine process actions, so get ready now for guiding these practices. Processes and cases share great visibility and accountability for the work and all the work participants, case management allows for the dynamic addition of participants and knowledge bases. Case management will also track who is doing what work and track them to milestone events and final completion. Most case management technologies allow for content sharing for collaborations and the transfer of knowledge and data. In addition good case management capabilities include the ability to track conformance and variance to capture better practices, not just rigid best practices.  Often case management styles can be intermixed with crisp processes to create a hybrid.

It's pretty much a given that large scoped, end to end, processes will contain a mixed set of process styles, but it is not clear what style will dominate. Will it be case management as the controlling style or will it be a typical flow. We know that both kinds of processes have a start and a stop, but how they get from one to the other is quite different. The Case approach follows a string of milestone goals, with little concern for the sequence of steps to the reach each milestone. The traditional flow has pre-planned paths and sequence implied in them. So why would one dominate the other?

Where Case Should Dominate:

Case should be the dominate style, with bits of leveraged planned flows or snippets, when the basic goals around investigation and collaboration to obtain  high quality and consensus outcomes. The further away a process is from best and tightened downed practice, the more case makes sense. Over time certain bits of the interaction can be made into min-flows (snippets), but investigative processes are generally dominated by case.

Where Planned Flows Should Dominate: 

Flows should be the dominate style, with bits of collaboration, when the basic goals are around speed and efficiency. The further away a process is from evolving and emergent behavior, the more planned flows make sense. As things become fuzzier and judgement intense, case and collaboration can be interjected, but value and supply chains are generally dominated by flow.

Net; Net:

A general rule of thumb is that case is great for emergent work and process is great for repeatable work, but both deliver great rates of return while they help case / process participants organize and track their work to completion. I will be covering Smart Process and Case Management Frameworks in future blog posts. My top ten key players in Case Management are Newgen, Pegasystems, IBM, Appian, DST, Lexmark/Kofax, Tibco, OpenText, Micropact and Hyland today. 

Software AG Demonstrates a Digital Business Platform At CeBIT

Software AG believes that the Digital Business Platform (DBP) is the foundation for the digital transformation and that having DBP in many organizations facilitates Industry 4.0. Because a good DBP supports agile, flexible, fast and differentiating processes, systems etc, DBPs are likely to be at the core of most organizations digital efforts and will assist digital transformations in a big way. A DBP supports innovation via your own staff; not an application or stack vendor. This was presented eloquently by CEO Karl-Heinz Streibich and further proven by the financial success of Software AG recently. All the numbers were up nicely.

Eric Duffaut, Chief Customer Officer, proceeded to challenge the crowd of customers prospects and the press to "Disrupt Yourself Before Someone Else Does It" He went on to make the point that co-innovation with customers was the key inventing digital futures within the known and the unknown. Since I also agree that that a DBP is a must, I had no quarrel with Software AG. In fact a great DBP will help the digital transformation with it's ability to quickly try options and alter solutions until they deliver. I saw some initial successes with customers and some very nice demos of what could be done at various stations in the show floor.

The story was told to Angela Merkel, the Chancellor of Germany, and she smartly asked if a DBP would enable German & other European companies to cooperate better and the answer was yes. She also pushed back and asked if she wanted to buy an iron on Google, would a DBP drive her to Bosch (a German provider). The answer was a qualified "yes" if Bosch used the DBP to enhance her customer experience in the past building loyalty.

Going around the Software AG booth stations I found a goodly number of compelling digital examples of digital promise demonstrated visually and in an experiential way. Below was a disruptive approach to creating new replacement teeth using a milling machine, CAD drawings, human mouth scans and process to create a cross organization (Industry 4.0 Solution) for dental patients (This was a proof of concept demo). 

There was a demo of vibration & temperature detection in the transportation industry that might indicate cargo damage. 

There was a retail floor map with cell phones mapped by department and customer type for the pushing of offers. This also was a demo. 

There was a demo of ALPHABET that showed how to manage risk across your digital transformation efforts while linking with architectural impacts.

                            

These were just of a sample few that caught my eye out of a myriad of others. Needless to say, the booth was loaded with people checking things out. 

Net; Net:

Software AG is the first vendor claiming to be a Digital Business Platform. There are other vendors with potential to move in the DBP direction, if they chose to do so. Time will tell if others do and if DBPs can consistently deliver great digital experiences and support solid digital transformation efforts. I'm betting on it and I expect Software AG to deliver some more great stories down the road. 

Kewl Booths at CeBIT

Yesterday I hinted at the scope and scale of CeBIT and it was mind blowing. Today I captured some images of vendor booths that impressed me along the way. Keep in mind, I was pretty focused on my sponsor, Software AG, but I did break way from their location to see some pretty kewl booths. The most expansive booth I saw was IBM, but there were others than impressed at CeBIT.

There were both hardware and software vendors. I saw robotic examples and really compelling displays of digital software in action, embedded in devices or cars. I'm sure I'm just scratching the surface with so many booths, but I am impressed.

                      Representation of Dynamic Big Data in SAPs Booth (double click)

Cool Robot Delicately Handling a Fragile Package 

                                         Software AG's Emulation of Industry 4.0 (double click)

Jim's Electric Dream Car 

The IoT Booth Sponsored by Intel and HP 

Motion Detecting Football (Soccer) Game at Software AG's Booth

IBM's MEGA Booth with a Racing Boat and Flight Simulator 

First Day at CeBit

Can you imagine 280000+ people in one place over a weeks time? This is CeBIT which is an acronym for the German translated into "Centre of Office Automation and Information Technology and Telecommunication" in English. There are over 6000+ vendors spread over many acres and 30+ good size buildings. Now you can appreciate the size and scope of CeBIT as it is the largest technology expo and conference in the world. I was a bit overwhelmed at the space, but this is just preparation day here in Hanover Germany and there will be more updates to follow. 

I was invited by Software AG to be on a panel in their booth on Tuesday. I was quite impressed with their booth as it was a work of art with a circular trail of demos surrounding the core art piece pictured below. 




Since Software AG is the first vendor that markets and sells a complete Digital Business Platform (DBP), it seems appropriate that I be there at the unveiling. While there are a number of other vendors with individual competing point technologies, Software AG has thoughtfully woven together their DBP offering with it's full organization behind it. This is a start of an expected trend of vendor provided DBPs for clients to do digital business without getting to hung up in individual technologies. You will see more from me on DBPs on this blog site and stay tuned for more on CeBIT. Also you will see a new book from me on Digital Transformation in the coming months that needs a DBP http://mkpress.com/DT/

Another impressive booth from German Telecom (Deutche Telekom).

What is Industry 4.0?

I received a question this morning on what was the difference between the IoT, the Industrial Internet and Industry 4.0. At first glance it seems that the differences are subtle, but it goes much deeper than one would believe. Besides the emphasis on manufacturing and production, Industry 4.0 has significant additions to the way it interacts and behaves that can spread out of pure engineering and manufacturing arenas. Let's dive into the differences 

The Internet of Things:

The (IoT) is the network of physical objects—devices, vehicles, buildings and other items embedded with electronics, software, sensors, and network connectivity—that enables these objects to collect and exchange data. Notice the emphasis on data and not on the processing or context. While certainly processing can be added inside the devices through embedded chips, the contexts are more about but not exclusively machine to machine (M2M). We see this played out in our cars with machine advisory or auto actions. There is more collaboration to leverage here, so enter the industrial internet.  

The Industrial Internet:

The Industrial Internet is a term coined by GE and refers to the integration of complex physical machinery with networked sensors and software. While complexity is one of the keys, the addition of software, particularly process software, adds tremendous leverage for desirable outcomes. The control points are now distributed and machines, software and humans can control their own contexts and can swarm to a solution.

Industry 4.0:

WIKI Definition: Industry 4.0 facilitates the vision and execution of a "Smart Factory". Within the modular structured Smart Factories of Industry 4.0, cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Over the Internet of Things, cyber-physical systems communicate and cooperate with each other and with humans in real time, and via the Internet of Services, both internal and cross-organizational services are offered and utilized by participants of the value chain.

Industry 4.0 is even a broader approach as it considers man-machine interaction in a value or supply chain context. It is ideal for a Digital Business Platform that supports better customer service  leveraging independent agents, cognitive knowledge agents (Cogs) or swarming agents. In industry 4.0 the contexts are larger, coordinated and goal/constraint directed which allows for more efficiency without sub-optimization. 

Net; Net:

There is a big difference with Industry 4.0 and the simple internet of things, but the combination of the IoT and decentralized control (swarming agents) plus new collaborations among machines, software, Cogs and humans will deliver new digital businesses that benefit many. 

How's Your Digital Maturity?

We are far beyond asking, if you are going digital. The questions are how far and how fast?  It's imperative to know where you are and where you want to be and the intermediate steps to take on this long and adaptive digital journey. Below is a simple and quick way to determine just how far you have progressed and what steps might be ahead of you as the digital journey continues forward. There are also some rough guidelines for you to determine your position within the model and I will be detailing each of the levels over time.

Initiating:

The first level concentrates on learning what digital means to your organization initially and how you might expect it to match your organizations needs for better customer relationships, real time business operations improvements or new products and services. Typically organizations select a small number of digital technology combinations that offer promise and experiment with them in a "sandbox like" environment where failure can happen without consequences.

Opportunistic: 

Once enough experimentation and early "in organization" innovation has taken place, there will be a new confidence in the ability to deliver results with the new skills, guidelines, methods, tools and technologies to look for opportunities to deliver benefits. It is important to link the strengths of the new digital prowess with proper business needs that will deliver real benefits. This will give a wider sense of confidence when benefit delivery happens in a regular fashion. In fact it is at this level that plans for incremental transformation should be drafted, if they haven't already.

Managed:

At this level, there are several successes. Each one should be measured for results and looked at for lessons learned. Out of these experiences, your organization can identify both better and best practices for future digital efforts. This is where better transformation plans can be created or tuned to make sure business results can be optimized from digital efforts. There will be an expansion of skills and competencies during this level. This is essential before spreading digital far and wide.

Habitual:

Now is the time for accelerated results with larger scopes of impact and inclusion. This is where rapid growth and expansion of digital features can take root. This is where digital is at the viral stage and the biggest problem will be to set priorities as to where the digital resources will be leveraged. In addition there will be a need for mass adaption and skills transfer. This is the level where you look to get better in anticipation of the next level.

Leveraged:

This is where you use digital as a weapon and aggressively attack your digital transformation efforts. Your organization will be looking to outflank the competition, start new services, deliver new products and maybe even change or create a new business model.

Net; Net:

Keep in mind there may be several threads of digital efforts running in concurrently that could leverage this maturity model, but the real benefit of the model is to measure a wide scope inside your organization. Remember that digital speeds things up considerably and some efforts will leap through the levels quickly on smaller scopes, but there have been efforts to deliver new business opportunities leaping up through the levels.

Cognitive Computing For All?

There seems to be great promise for cognitive computing, but what is it and how can it help individuals and business in ways that contribute to a thriving world? I'm going to cheat a bit and use a definition I found on the web that is a good enough starting point:

Cognitive computing is the simulation of human thought processes in a computerized model. Cognitive computing involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works.

I would like to add value by showing where cognitive computing adds to or extends the human experience. I believe that it can augment human thinking and actions safely, but once cognitive becomes autonomous (acting on it's own), then special care should be taken to put in safety policies, rules and constraints (boundaries). 

Assuming that all forms of big data(data, events, voice and video) can be consumed and organized for cognitive agents (Cogs), cognitive can bring about great benefits for organizations going digital. I've identified five major areas of cognitive contribution that seem to be contributing today. I will gather case studies over time to publish to show traction. The five areas of contribution are as follows:

Help Decide:

Cognitive is great for highlighting great alternatives for humans by consuming large amounts of sensory data and showing the way forward. This is great for augmenting knowledge workers in areas where they do not posses the domain knowledge or can sort through the amount of information in a timely manner. 

Make a Simple Decision:

Not only can cognitive augment knowledge and show alternatives for simple decisions, it can make a decision for humans and explain why it did so. In fact it can explain why other alternatives aren't as good as the one selected by a cog or a group of collaborating cogs. 

Make a Interconnected Decision:

Cognitive is really great at making a decision where there are a number of related decisions driven by shifting goals, priorities and weighting. This is a more difficult task for humans under fire and cognitive shines in this arena of thinking and making decisions. Cognitive can do this while providing the kind of transparency that shows trace ability and supports audit ability. 

Advise on an Action:

Cognitive can also suggest actions for humans to authorize and explain why and support various "what if" approaches. This can help build the confidence of the person authorizing actions. 

Decide and Take Action:

Cognitive not only can decide, it can act. This is where all the scary stories start emerging, but proper boundaries and rules will create the proper controls. This is especially necessary when multiple autonomous cogs are acting in concert in areas not encountered or anticipated. We have seen lots of success with robotics / IoT and I expect to see much more in the white collar arenas as well. 

Net; Net:

When it comes to taking in large volumes of data, information and sensory inputs in near real  time and answer questions, explain the best alternative and explain why other alternatives aren't as good, it's hard to ignore cognitive computing.