I have been teaching an executive course called for four years and the tool that I consider to be most important to good operating model work is something I call a Value Chain Map. For those of you who work on processes, a Value Chain Map is a high-level process map or value stream map: the term value chain coming from the strategy literature. I prefer the term value chain because it reminds me that we are trying to link operations to strategy.
Maximizing the Value of Your Product Backlog (Part One): Gathering the full scope of requirements
The Product Backlog is the heart of defining any Agile solution. The requirements that are identified in the Product Backlog drive the priorities that the Agile development team works on, they establish the scope of the delivered solution, and they ultimately determine the business value that the organization will receive from their Agile investment. The challenge is that most Product Backlogs are based on input from selected stakeholders, rarely representing the full scope of requirements – and constraints – that need to be considered before priorities and business value can be accurately identified.
This is the first of two articles that provide you with techniques for maximizing the value of the requirements in your Product Backlog. This article focuses on ensuring that you have considered the full scope of potential sources for identifying what the solution needs to deliver – and equally what it should notbe delivering.
Mounting Pressure for Better Decisions
We are in a perfect storm for making great decisions and nothing less. There are converging forces that put a premium on better decisions in that organizations are being asked for more in a changing world. At the same time the number of assists that are available to boost better decision making are also emerging quickly. What are these forces and boosts to increase an organization’s ability to make better at the minimum and great decisions at a maximum? The coming decision wars will be at the forefront of success going forward for organizations and individuals.
Forces Affecting Decisions:
Business Contexts Shifting Faster
Robotics is a GO, now what?
The Future Is Now
Many companies are making the decision to step forward and implement various forms of Digital Process Automation, namely some version of Robotics Process Automation (RPA). There is a spectrum of Automation (Exhibit 1), from simple tasks that “bots” can easily handle to Artificial Intelligence. RPA is the next generation of process automation, moving from scripts and macros, to automating repetitive activities. Companies are choosing where to jump in and how to stand up to the new business capability.
Exhibit 1
3 months ago, we all thought Cambridge Analytica was a font!!!
Consumers are waking up to the fact that if they can’t work out what product that a website is selling, then they are probably the product. Or at least, their data is. We’ve all known this, but probably hadn’t realized how much of our data is being harvested, aggregated and then exploited.
Every business is now a digital business and data is the lifeblood. This is a major shift over the last 10 years, but the true impact is really starting to be recognized. This transformation is a as significant as the industrial revolution, and with the same redistribution of wealth.
So, let’s first cover off which industries or areas of business are being impacted by the combined disruptive effect of cloud, social, mobile, big data. That is easy. ALL OF THEM.
The digital business
Once an Architect…
As is the case with many of us in the Business Architecture forums, my career is firmly rooted in computer science and information technology. The first few years of my professional life found me devising algorithms, designing databases and writing code for various organizations around the Washington, D.C. beltway. It was a pleasant and satisfying endeavor, well suited to my quiet disposition. Despite the unavoidable meetings with end users – which meetings never failed to throw a monkey-wrench into my carefully crafted programs – my projects tended to unfold without major heartaches while I dug deeper into James Martin’s Information Engineering, Barry Boehm’s Spiral Model for Software Development, and Barbara von Halle’s writings on data architecture and business rules.
Visual Management in Enterprise Excellence Deployment
A “Next Level Evolution” model for Operational Excellence to integrate with Business Transformation under the broader concept of Enterprise Excellence was discussed in BPMinstitute.org article in May 2017 1. The impact of a standardized Stage-Gate Process for Innovation and New Product introduction was detailed in April 2018. 2
As Part of a Business Transformation and Enterprise Excellence strategy, how can the tools and techniques of Operational Excellence be integrated into Business Strategy?
A foundation package of Operational Excellence tools and techniques that should be fundamental to all Business Strategy and Transformation efforts that are part of an Enterprise Excellence deployment strategy is shown below:
BPM Maturity is Needed for Digital Business Success
BPM Maturity is Needed for Digital Business Success
The importance of a process orientation in driving digital business success has been recognized for some time. In the early days of digital – it was already recognized that leading companies succeed with digital by re-envisioning customer experience, operational processes and business models.
Gartner has also stressed the importance of BPM in digital transformation success and predicted that a deficit of BPM maturity may actually prevent 80 percent of organizations from achieving the desired business outcomes from their digitalbusiness strategies.
The main options for deploying digital are:
a) Find a digital tool and deploy it
Ten Essential Steps to Create an Effective Data Management Plan
During any kind of research project, you’re going to collect data. This data will vary depending on what you’re studying, but you will need to create a data management plan no matter what. This is because it’s vital you explain exactly how you will use data at every point during the data life cycle. Here’s ten rules that will make creating your own plan simple.
Rule 1: Understand the research sponsor requirements
The first thing you must do is find out what is needed from you from your research sponsor. Each sponsor will have slightly different needs. “Even if you’ve worked with a sponsor before, it’s always best to check to ensure they haven’t recently changed their requirements”, – says Amber Coburn, an Operation Manager at Bigassignments .
Rule 2: Identify the data to be collected
Gaining Insights from Your Process Repository
“How can I get the information I need from this ocean of models? “- questioned the VP of Operations after going through the process repository built for his group. The repository had hundreds of models of different types. They were built over months of effort from Subject Matter Experts and Process / Business Architecture practitioners. He wanted to find out
What percentage of activities are automated and manual?
Which teams use a specific application?
How many teams are involved to execute a value stream?
How many people refer to models in the repository to perform their daily duties?
At what rate are different teams building these models? Etc
The information for which the VP of Operations was asking buried was in the repository – many times in multiple models. To answer each of question, the analyst may need to spend a couple of hours to go through multiple models, generate reports, analyze and then consolidate information.