A leading business archivist provides insights into the difficulties of selecting, organizing, and preserving corporate records. Dr. Ernst reflects on the future needs and responsibilities of the business archivist in a changing economic and social environment.

Current conditions in the money and credit markets, along with the memory of the “crunch” of late 1966, have caused both the managers of financial institutions and their regulators to reconsider their concepts of “liquidity.” Both Minsky and Ritter have argued forcefully that traditional attention paid to balance sheet proportions should be abandoned in favor of an intertemporal analysis of cash flows [6], [7], and [8]. Ritter states that: “With a multidimensional cash flow forecast extending several years into the future, probability estimates can be made regarding potential liquidity needs over time” [8]. The purpose of this paper is to suggest a forecasting method which explicitly deals with the problem of uncertainty. The method is specifically designed for a mutual savings bank, but it could easily be adapted for a savings and loan association and, with perhaps greater effort, a commercial bank.2 In Section I, components of cash inflows and outflows are examined with the general objective of classification according to: (1) degree of uncertainty and (2) degree of management control. A risk analysis simulation model which permits explicit consideration of uncertainty is presented in Section II. Problems of implementing the model are discussed in Section III, while the implications of the analysis for future research are considered in Section IV.

With the rapid growth in various types of corporate combinations, many opportunities arise in which increased internal efficiency in the allocation of capital budgeting resources may be obtained. Although the resource-transfer methodology proposed in this paper is discussed within the context of a merger/acquisition environment, the operational analysis conveivably could be applied to multiproduct, multifirm, or multinational situations. This study examines an application in which a linear programming model can be used operationally as an analytical planning device (1) to obtain efficient capital budgets for the merged companies, and (2) to quantify the monetary value of potential gains in efficiency produced by a merger. Conceptually, the model assists management in searching for excess capacity in each company, efficiently combines scarce resources, selects an optimal project list for the merged company, and indicates what the composition of the new capital budget should be. In addition, a variable step function provides for multiplicative adjustments in common resource constraints. These adjustments might be positive (negative) if the combination results in a more than proportionate increase (decrease) in the availability of a scarce resource.

Markowitz's [2] portfolio selection model was originally concerned with financial investments, but the model's implications for capital budgeting are now well recognized. Markowitz's basic idea is that the optimal portfolio for an investor is not simply any collection of good securities, but a balanced whole, providing the investor with the best combination of “return” and “risk.” Return and risk are to be measured by the expected value and variance of the probability distribution of portfolio return. Although financial writers have generally accepted Markowitz's measure of return, they have not been completely satisfied with his suggested measure of risk [1]. In fact, Markowitz himself had reservations about choosing variance as a measure of risk.1 Besides variance, he considered five other alternative measures of risk:

(1) The expected value of loss;

(2) The probability of loss;

(3) The expected absolute deviation;

(4) The maximum expected loss; and

(5) The semivariance.