Partial least squares (PLS) is sometimes used as an alternative to covariance-based structural equation modeling (SEM). This paper briefly reviews currently available SEM techniques, and provides a critique of the perceived advantages of PLS over covariance-based SEM as commonly cited by PLS users. Specific attention is drawn to the primary disadvantage of PLS, namely the lack of consistency of its parameter estimates. The instrumental variables (IV) /two stage least squares (2SLS) method of estimation is then described and presented as a potential alternative to PLS that might yield its perceived advantages without succumbing to its primary disadvantage. Preliminary simulation results show that: PLS parameter estimates exhibit substantial bias when the number of items is moderate; SEM-based methods yield lower bias; and IV/2SLS estimates may indeed provide a viable ordinary least squares (OLS)-based alternative to PLS.