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AS was shown to prematurely stagnate for complex problems Here, stagnation means that all ants follow exactly the same path, and premature stagnation occurs when ants explore little and too rapidly exploit the highest pheromone concentrations St tzle u and Hoos have introduced the max-min ant system (MMAS) to address the premature stagnation problem of AS [815, 816] The main di erence between MMAS and AS is that pheromone intensities are restricted within given intervals Additional di erences are that only the best ant may reinforce pheromones, initial pheromones are set to the max allowed value, and a pheromone smoothing mechanism is used The pheromone global update is similar to that of ACS, in equation (1719), where ij (t) is calculated on the basis either of the global-best path or of the iterationbest path The rst version of MMAS focused on the iteration-best path, where x(t) represents the best path found during the current iteration [815] Later versions also included the global-best path, x(t), using di erent strategies [816]: Using only the global-best path to determine ij (t), in which case x(t) is the best overall path found from the rst iteration Using only the global best path may concentrate the search too quickly around the global best solution, thus limiting exploration This problem is reduced if the iteration-best path is used, since best paths may di er considerably from one iteration to the next, thereby allowing more exploration Use mixed strategies, where both the iteration-best and the global-best paths are used to update pheromone concentrations As default, the iteration-best path is used to favor exploration with the global-best path used periodically Alternatively, the frequency at which the global-best path is used to update pheromones is increased over time At the point of stagnation, all pheromone concentrations, ij , are reinitialized to the maximum allowed value, after which only the iteration-best path is used for a limited number of iterations The -branching factor, with = 005, is used to determine the point of stagnation Gambardella and Dorigo de ned the mean -branching factor as an indication of the dimension of the search space [300] Over time the mean -branching factor decreases to a small value at point of stagnation The i -branching factor is de ned as the number of links leaving node i with ij -values greater than i + i,min ; i = i,max i,min , where i,min = min{ ij }.

focused on improving enterprise data is of equally high importance and aligned with enterprise performance optimization Generally, smart data is the product of engineering such that it presents itself to the right users at the right place and time in support of planning, problem solving, decision making, sense making, and predicting At one time, Fannie Mae embraced these truths and was successful In the near term, Fannie Mae ignored these core concepts of smart data as well as the methodology and algorithms that support the intended uses of smart data As a result, Fannie Mae has strayed from the smart data path and has become a liability as a government bailout Fannie Mae forgot that smart data is interoperable and supports quali ed users with diverse needs in an ubiquitous environment It refused to follow a paradigm that produced advanced data engineering technologies, including modeling and metadata management, and smart application of open standards that account for credentialing and privileging as a dimension of security In a nutshell, this is why Fannie Mae nds itself in nancial woes today The following case was conducted in 1999 and shows Fannie Mae adopting many smart data concepts Compare this environment with the one that Fannie Mae nds itself oundering in, a decade later, by ignoring the smart data paradigm Much like Where s Waldo, can you point out the numerous smart data concepts that Fannie Mae ignored in the following case, Managing Radical Transformation at Fannie Mae: A Holistic Paradigm [22] In this case, from 1999, we noted that change management is a critical issue in the current fast-paced business environment Organizations are being bombarded with global business change, innovations in communications, and rapidly evolving information systems capabilities Since there exists a paucity of rigorous and relevant literature on change management, we chose to embark on an in-depth case study to explore how one organization manages radical change We developed a set of theoretical propositions to guide the effort and act as a theoretical lens Our speci c research question is: How does an organization successfully manage projects that call for dramatic change to the way one normally conducts business The case study allowed us to test the propositions in the business arena with one organization It is hoped that this approach will offer insights and mechanisms to help other organizations effectively deal with change When we embarked on this study, we wanted to explore how organizations successfully manage dramatic change We began by consulting the literature on transformation, BPR, and sociotechnical management The literature helped us articulate ve propositions relating to successful change management We conducted an in-depth case study of one organization (Fannie Mae) involved in radical transformation to see how it coped We found that each of the ve propositions paralleled the case study in some way The case study provided a rich set of data that allowed us to delve deeper than the literature We were able to show that these propositions are in fact applied in at least one case We were also able to show that holistic management can increase information sharing and knowledge creation Fannie Mae approaches training and development in a holistic manner Top management is active and committed.

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(1722) (1723)

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i,max = max{ ij }

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