AVNET Marshall developed a business model that inspired the company to be an agile customer-focused organization. Agility in business is the ability to continue to grow and prosper in rapidly changing environment. This aspect requires the ability to deliver high quality, high performance and customer configured products and services. A customer-focused organization is one that has the ability to keep customers loyal, anticipate future needs, respond to customer concerns and provide top-quality customer service.
Figure 1: AVNET Marshall Model (Modified)
The model (Figure 1) was developed as a clear, simple and powerful tool to focus employees and information technology on serving customers. This month we are going to deconstruct this model and apply it to our world of meta data. Let me pause for a moment for an editorial comment. After you read this, I want you to ask yourself if this framework provides any insight into your project (meta data or otherwise). I have been doing enterprise meta data since 1999 and not a week goes by that some vendor, consultant or newly appointed meta data expert doesn't approach us with some new idea, product, service or framework. Most of which is simply refactored ideas of old (one of the sins of being in IT for 21 years). This model is different. I printed a copy of the model and simply stared at it for a couple of weeks. This model, in its elegance and simplicity, reminded me how little we know about information systems (IS). I literally changed every slide deck I own to reflect the realizations that these three dimensions provided. If you are not impressed with this model after reading this article then I have failed to communicate its potential. Creative modifications have been made to the model in order to apply our experience.
Most technology projects, especially in the world of knowledge management, focus only on the minimum amount of requirements. We tend to focus on the basic infrastructure, base budget and having the information accessible, which is only the beginning. In the model, this point of origin is the apex point where the three dimensions come together.
The perfect dimension describes the ability of the organization to deliver its products and services to the end customer. Beginning with a solid product line, hardware, communications and other elements of an infrastructure are a positive first step. In the world of meta data, this includes repository applications, portal services, architecture standards and many more. However, when your meta data information is exposed to the technology and business communities, quality becomes and major concern. Meta data quality may be the most important aspect of the product and service delivery. How could the project be perfect if the data has questions? In the end, success and failure within a meta data project depends on its ability to control the quality of the information they process. Front-end edits, content aging, data quality audits and a solid stewardship program are essential. Customers not only want quality information, they want information delivered in an understandable way. Much of the research in the Human-Computer Interaction (HCI) field focuses on this problem. Is there a problem with the usability of our applications? Unfortunately, the answer is yes. The current suite of applications is built more for the sake of technology than delivering a usable product. Check out the marketing materials, where exactly is the statement that our product is usable and built upon common Web-based design frameworks. Don't waste too much time, I am sure it hidden somewhere between the self-acclaim that we support OMG, CWM, RAS, DC, XML or what ever the latest and greatest technology buzzword. What the vendor community needs to do is to stop making incremental adjustments in strategy and completely redefine, no transform, the market into true asset management. If they don't then someone else will, very soon.
Since we define meta data as information collected on the entire collection of assets then we must realize that most customers don't care about the entire collection. Just as when we walk into Wal-Mart - there are some sections of the store that no man has ever emerged from. Men tend to avoid these areas of the store even when they present the shortest path to the automotive or sports department. Customized views of meta data are important both internal to the repository and across the repository collection. Finally, we should be able to anticipate the needs of the user community. Perhaps this means building a repository before there is solid demand (i.e., Web services) or adding a drop-box facility to the subscription services module. Working side-by-side with IT users, meta data-focused employees will begin to see service opportunities long before others. The perfect path is eternal, there are always forces that attack your quality, customer experiences change in the usability expectations and progression in asset management will change many of the other dimensions.
Simply put, customers want the lowest cost and the highest value. Most project organizations will start with looking at budget and shared costs. This is only the beginning and organizations should add metrics on usage and content as soon as possible. Content is the inventory of assets in the collection and usage is metrics around how the information is being used. Content drives usage, the more information you make available then the more people will use the repository collection. Ironically, the opposite is also true. The more people use the collection, the more they will want additional assets. Organizations that implement meta data must always include these first couple of aspects. The next step is much more difficult, calculating return on investment (ROI) for the meta data project. ROI is not easy, and there are a multitude of frameworks that can apply. ROI based on reuse is just one example that we use in order to calculate ROI. Other models such as balanced scorecard or usage-based ROI offer other valuable insights. There is no real silver bullet here; ROI is a challenge and if it was easy then we could move it back up the chain. Finally, charging back for value-add services is critical. Projects and organizations want to get IT products and services for free. Free doesn't mean that there is no cost, but the customer doesn't care based on the value add.
The "now" dimension focuses on your ability to bring meta data into the current workflow, to manage and process customer's requests. The starting position is that information can be collected and posted online. Clearly, moving toward a standard process is a requirement for being a customer-focused organization. Streamlining the process and making it repeatable will enable the support organization to handle more service requests. We like to describe the process as a pipe. If we can streamline the process, we can enlarge the pipe and be able to process more customers at the same time. Ideally, we can reduce our service level agreements and average turnaround time to get to an ideal delivery time. Finally, we want to reach a level where the customer's time to market to deliver their products and services is reduced by our efforts.
Have you noticed something interesting as we approach the Free-Perfect-Now (FPN) stage? The products and services of the meta data group disappear and all of the focus moves to the customer; we become a commodity. While the term commodity has been villainized recently, the reality is that being a commodity means that the components are firing on all cylinders. How long will you stay in the FPN stage? Not very long, the expectations of the customer continually increase which, in turn, requires that you change as well. I encourage you to review this model within your own environment and see how you can change your group from a technology-focused organization to a customer-focused one. Your long-term survival will depend on it.
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