Presentations by Alec Sharp

The Lost Art of Conceptual Modeling – Where Did It All Go Wrong?

The high value of getting into the conceptual modeling space is being stressed these days, yet there is a startling lack of agreement on what a conceptual mode really is. At one recent conference, the vendor of a leading data modeling tool offered the bizarre suggestion that it's a logical model printed without attributes or keys. At the same conference, a data modeling guru offered a definition so close to physical database design as to be unintelligible to business professionals. This presentation offers clear definitions and examples, guidelines, and practical techniques for conceptual modeling. Much of it is based on the speaker's experience taking existing physical and logical models up to the conceptual level so "mere mortals" could comprehend them, and their business impacts. Highlights include:

  • Definitions and examples for contextual, conceptual, logical, and physical modeling
  • How conceptual modeling arises in other areas such as process modeling and use cases
  • The growing value of conceptual thinking in the business world
  • Why conceptual modeling is vital to your continued employment
  • The role of data modeling tools in all this confusion
  • Why packaged solutions and legacy system "revitalization" make conceptual modeling more important than ever, and how you can apply it
  • A process for "getting conceptual"

 

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The Human Side of Data Modeling –Improving Communication With Subject Matter Experts

Above all, data models should be viewed as a communication vehicle among different stakeholders, including decision-makers, content experts, business analysts, and designers. Unfortunately, the communication often gets lost, either in the clouds, in the weeds, or somewhere off to the side. Whether the modeler has drifted too quickly into abstraction and generalization, or has taken the “deep dive for detail,” the result is the same – confused, frustrated, or detached subject matter experts. And the result of this is inaccurate or incomplete models! Experience shows that it doesn't have to be this way - simple techniques, consistently and regularly applied, will go a long way to ensuring involvement, buy-in, and communication. Drawing on over 25 years of successful data modeling experience, this presentation will discuss the core “human side” behaviors – accessibility, direction, simplicity, consistency, visibility, relevance, plurality, patience, humility, tangible involvement, and empathy. These will be illustrated through a variety of topics and examples:

  • "Role induction" for clients, and why you can skip the "tutorial" on data modeling
  • Getting started – choosing between top-down, bottom-up, or sideways-in approaches
  • Presenting vs. modeling – considerations for the emerging world of "systems archaeology"
  • Appealing to all learning styles – visual, auditory, and kinesthetic
  • Conventions for comprehension – guidelines for data model graphics
  • "Scripts" for growing the model – the value of consistency
  • Using other techniques – workflow modeling, use cases, and service specifications

 

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From Process Model to IT Requirements – Crossing the Chasm

One lesson that's been learned over the past decade, especially from huge ERP implementations that went sideways, is that large information systems projects carried out without regard to business processes often fail. Unfortunately, although it's a great start, having a well-considered and widely-supported process design doesn't guarantee success either. As in any type of project, the issue is how best to discover, document, and verify functional requirements. Simple, list-based approaches (loved by management because of the illusion of traceability) are loathed by developers because they provide no context. On the other hand are rigorous, complex techniques that are indecipherable to most users and analysts, and thus also produce undependable results. What to do? This presentation will describe methods that have worked well for all parties in large, process-oriented undertakings. Some of the questions that will be answered include:

  • What are functional requirements? – a simple framework that includes business processes
  • Technique overload - usage-centered design, use cases, scenarios, agile methods, service or component specifications, contracts, etc. Are any or all of them useful and necessary?
  • When should I stop modeling process flow and shift to other forms to capture requirements?
  • How can I avoid the “deep dive for detail,” and take a controlled descent instead?
  • Don't agile methods mean I can forget about all this overhead and just get on with the job?

 

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Getting Traction for "Process" – What the Experts Forget

Are your efforts to get a more “process oriented” approach adopted at your organization falling short? If so, you’re not alone! Many BPM conference participants have reported that their attempts have been met with indifference, misunderstanding, skepticism, and even outright hostility. The reasons for these reactions are surprisingly common, and include not addressing the unpleasant outcomes of previous “process” initiatives, assuming that everyone knows what a business process is, using language and methods that are unsuitable for mere mortals, and the ever-popular failure to acknowledge that “we’re working hard and meeting our targets!” This presentation will cover proven techniques, backed up by real-life examples, for getting and maintaining the support and participation of managers, subject matter experts, and process participants. Key issues:

  • What people are thinking when you say “process” – avoiding the backlash from misapplied BPR and Six Sigma initiatives
  • From mechanistic to humanistic – taking the sting out of process work and making it blame-free
  • Choosing the right mapping technique for the audience, and controlling detail
  • Applying the new mantras of “conceptual thinking” and “simplicity” to the world of business processes
  • Commonly misunderstood terms, and a glossary (with examples) to clarify them

 

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Getting Traction for Data Modeling – Winning Over the Masses

Data models are powerful tools, useful for much more than what they are often (unfortunately) seen as – another term for database design. Rather, data models should be seen as a communication vehicle among different stakeholders, including decision-makers, content experts, business analysts, and designers. This often isn’t the case, and data modeling is treated as an irrelevant or after-the-fact exercise. It doesn’t have to be this way! Simple techniques, consistently and regularly applied, will go a long way to getting traction for the idea that data modeling is a vital business tool. Drawing on almost 30 years of successful experience, this presentation will discuss five (or maybe ten) core techniques for helping people appreciate, use, and possibly even want to build data models. Topics include:

  • Stop talking about data! What Alan Kay said about DAMA.
  • Don’t start by teaching data modeling – there’s a better way to get started
  • Show them what they’ve already got (and why they don’t like it)
  • Getting conceptual and even contextual
  • Solving management, analysis, and development issues
  • Making it repeatable – methods, patterns, procedures
  • Being style conscious – appealing to visuals, auditories, and kinesthetics

 

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Process Orientation for Data Management Professionals: Using “Process” to Gain Support

Organizations everywhere are once again looking at their business processes - undertaking Business Process Redesign, adopting Six Sigma methods, or getting into Business Process Management. This is great news for data management professionals with skills in the business process arena. That’s because our goal may be improved data and information, but experience has shown that focusing on business processes is a great way to get the attention and support of the enterprise. This session introduces techniques for working on process-oriented projects, and is packed with practical frameworks and tips to get you off to a successful start. It touches on all phases of a project, including introducing business process concepts, discovering processes, scoping and assessing the target process, modeling the as-is process, and designing the to-be process. Throughout, we’ll illustrate the interaction between process and data perspectives. Specifics include

  • The lessons of history - the rise and fall and rise again of process re-engineering
  • What people think a process is, what a business process really is, and how to discover them
  • Why some of our beloved data management approaches and frameworks can work against process orientation
  • How to make processes visible and the need for improvement compelling yet blame-free
  • Proven presentation techniques for getting management attention
  • Why process modeling begins before you begin process modeling
  • How process modeling is different than data modeling, and the methods that work

 

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