Several months ago, I got an urgent request from OMG – the organization responsible for BPMN and other BPM standards – to give a short blurb I had written a permanent URL on my website.  The blurb was a promotional piece for my BPMessentials training called “Three Levels of Process Modeling with BPMN.” OMG proudly proclaims that BPMN assumes no particular methodology, but the notion of using it at three specific “levels” was just something I made up when I launched my BPMN course, to describe its value to different audiences.  Now OMG needed it as a “reference” for their OCEB certifi

Experience has shown that major change initiatives undertaken by government agencies seldom succeed according to plan. Too often, expectations are frustrated, budgets are over-run, schedules are exceeded, and/or programs are abandoned. Why is this story written so often, after the fact, about so many government programs? From years of working with federal agencies on some of their toughest challenges, I have found that leaders tend to underestimate the difficulty of the journeys they embark upon, at almost every stage of their more complex transformation initiatives.

Nobody really cares about standards… until suddenly they do. When a standard reaches some threshold of adoption, a tipping point is reached. Then, if you’re not on the standard you’re proprietary. Legacy. A dinosaur. Not where you want to be.

So, you’ve read all the right books on lean, agile, and process improvement. You’ve drunk enough of the “quality” cool aid to believe that if everyone else “got it” things in your department or firm would be so much better; you can actually imagine how things could be faster, better and cheaper. If only others could see, taste and implement that same vision.

Data quality is to the information society what quality of materials and products are to the production society. The quality of data in a business is a deciding competitive parameter, and this recognition is currently spreading among businesses throughout the world.

The technological development has generally, along with the development of ERP systems such as SAP, made it possible for businesses to produce, modify and disseminate enormous amounts of data. These data often form the basis for decision making, financial reporting and controlling liquidity, products, clients and suppliers.