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and legacy infrastructure and data have accrued We have already reported how some large organizations have identi ed this as a signi cant problem as operations budgets consume resources for maintenance that could otherwise be used for performance improvement through advancing technology Breaking this cycle is a huge target for government performance improvement, but it comes at the expense of reducing expenditures to some systems integrators that pro t from inef ciency Here is an interesting observation When the GEIA electronics industry association conducts their annual review of government expenditures, they identify operations and maintenance budget items as the onerous enemy because increases in operations and maintenance (O&M) come at the expense of investment in new electronic technologies Product sales suffer when service labor sales increase On the other hand, when aerospace defense contractors who are in the systems integration business meet, they see operations and maintenance increases as a positive development because it means more contracting for professional services Smart data strategy is an objective means of identifying opportunities for performance improvement and therefore should be conducted by third-party objective professionals This also means that objectivity must be preserved for internal and external analyst and auditor participants It is too costly to maintain interfaces to a host of legacy systems inside the organization and among enterprise constituents A legacy systemisacomputersystem orapplicationprogramthatcontinuesto be used because the user does not want to replace or redesign it Legacy systems performance is often de cient, slower performing and more costly to maintain Often, their use is so high and critical they cannot be taken of ine Redesign is often costly due to their being large and complex and often documentation needed to understand the code and how the system works is de cient For these reasons, there needs to be a way to exchange datawith and otherwise transact with these systems while injecting a degree of agility, adaptability, and exibility Smart data is the technological means for achieving this It is also too costly and impractical to change to one perfect solution Smart data is the means to overcome legacy system barriers It requires stopping investments in maintenance and diverting resources toward new solutions Often, the data needed is found in fragmented and noncon gured states and therefore is incomplete and unreliable This circumstance can be eliminated by beginning with knowing what decisions the enterprise needs to support and providing con gured data for reporting, decision making, sense making, and predicting Incoming data takes extraordinary effort to translate into usable format and syntax for internal systems Smart data strategy places the burden of deviation on the source of the deviation That is, smart data strategy provides a universal basis for data.

then the total base pay would be $3,000,000, which would yield a benefits percentage of 14 percent This percentage could then be tracked over time to spot changes, or compared to industry standards to see if a company s benefit costs vary from the norm

(1235)

226 where Cl (t) =

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This is one of the most closely watched of all performance measures It is based on the assumption that employees are at the core of a company s profitability, and so, high degrees of efficiency in this area are bound to result in strong profitability It is also a standard benchmark in many industries To calculate this measurement, divide revenue for a full year by the total number of full-time equivalents (FTEs) in the company An FTE is the combination of staffing that equals a 40-hour week For example, two half-time employees would be counted as one FTE The formula is: Annualized revenue Total full-time equivalents A variation on this ratio is to only divide annual revenues by those FTEs who can be categorized as direct labor This measures the productivity of those personnel who are directly connected to the manufacture of a company s products or services This measure should be used with care, since it is not always easy to determine which employees can be categorized as direct labor and which ones fall into the overhead category instead The formula is: Annualized revenue Total direct labor full-time equivalents For example, the operations manager of the Twirling Washing Machine Company wants to determine the sales per person for his company, both for all staff and just the direct labor personnel The company has annual revenues of $4,200,000 Its headcount is: Department Direct labor department Direct labor part-time staff Production supervisors Material handling department Sales, general & administrative Administrative part-time staff Engineering department Headcount 22 6 2 4 10 2 8

nm T lk (t) lk (t)

.

(1236)

Payroll Measurements and Internal Reports / 81

1 with lk (t) N (0, i l (t) Ci (t)) and nm is the mutation strength For large values of nm , the mutation strength is small, because a large sample, 1 , 2 , , nm , provides a closer approximation to the original distribution than a smaller sample Ostermeier and Hansen suggested that nm = nx

Previous sections have already discussed a number of di erent self-adaptation and mutation strategies for ES This section describes a few ES implementations that di er somewhat from the generic ES algorithm summarized in Algorithm 121

.

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