Thursday, August 26, 2010

Critical Success Factors of CRM Technological Initiatives

Devising a CRM business strategy is unrealistic without a proper understanding of the benefits and opportunities of enabling technology and vice versa. In a recent survey Gartner group reports that CRM project have the highest failure rates in implementation but have the highest potential in terms of return on investment rates.

I want to talk about a study done by Peter Lin and Anne-Marie Corteau & myself which I find very relevant to find what are the critical success factors that are significant of CRM Technology initiatives. The study surprisingly revealed what should be apparently significant CRM impact for an organization is not that significant as perceived by many. The direct CRM impact as perceived by many are operational and strategic benefits arising out of CRM technological initiatives. Operational perceived benefits such as front-office efficiency and productivity in sales, marketing and customer support and service functional units to shorten sales cycle, marketing cycle, and customer support due to better employee productivity. Furthermore improved operational productivity means decrease in costs. On the other hand the perceived strategic benefits would be defined as the the tactical, opportunistic and competitive advantage a CRM implementation can bring in terms of churning of information into useful strategic knowledge base.

The authors put around 1000 questionnaires out to senior management and middle level managers across various industries. They used Iacovu et. al' research model (1995) with various constructs and frameworks that they borrowed to make the testing of 6 hypothesis involving 5 key critical success factors. CRM impact was the dependent variable and the 5 CSF's and their relational to CRM Imapct are depicted in the following figures:


The hypothesis were to calucate the significance (postiviely or -vely linked) of each factor contributing the CRM impact of technology on overall organizational effectiveness. Internal and external focus of the CRM impact were summed to see the overall effectiveness.



Of the 1000 questionnaires an intial 14.3% response rate gave us about 103 organizations that adopted some sort of CRM implememntation, 44 were non-adopters, 28 chose to concentrate only sales force automation and 31 preferred on the Enterrpise marketing application.  Without going into the details of all hypothesis, constructs, instrument and methodology used here is the brief summarization:

A component based software package developed by Chin and Fee (1995) was used to assess the measurment model and the structural model with confirmatory factor analysis technique. The PLS (partial least squares) statistical method was used for the analysis of latent vairable structural models involing multiple constructs with multiple indicators. PLS is a second generation multivariate statistical technique that allows the test of pschometric properties of scales us to measure different variables. With the structural equation modeling technique, the construct reliablity is mot most commonly calculated using rho (ρ) coefficient, a coefficient of reliabiltiy that measures how well a set of items measures a single latent construct.  The results were surprising H1 was not supported as there was a -ve and non-signification relationship between operational perceived benefits and cRM impact (path coefficient =-0.123, p>0.05), H2 is not supported as the strategice benefits perceived and CRM impact though positive was not yet significant as (path coefficient  = 0.065, p>0.05), H3 is supported since the relationship between top management endorsing and supporting CRM impact resulted positive and significant (path coefficient 0.255, p<0.05. H4 is not supported since the link between technological readiness and CRM impact is positive but yet nonsignificatn (path coefficent = 0.062, P>0.05). H5 is supported since the relationship between technological readiness and knowledge management capabitilities is positive and significant (path coefficient = 0.0631, p<0.001). H6 is also supported since the relationship between knowledge management capabilities and CRM impact is positive and significant (path coefficent = 0.486, p<0.01).  The proposed research model appeared to provide good power to explain 43.0% of the variance in CRM impact.

Interestingly the organizations surveyed were from a diverse spectrum (pharmacy, healthcare, technology, etc), and it was surprising to see that what perceived to be prime motivators for spending in CRM implementation did not turn out to have significant CRM impact whereas CSF's turned out to be technology readingess, knowledge management and top-tier support.

I wonder what would happen if each industry were to be studied separately in its own space. Would it reveal a different statistical result on the effectiness of organizations that spend tons of money in CRM technology implementations. The questions are open for research...

Sam Kurien

References:
Chin, W.W & Fee, T. (1995). PLS Graph Software v 2910208

Iacovou, C., Benbasat, I., & Dexter, A.S (1995) Electronic data interchange and small organizations: Adoption and impact of technology. MIS Quarterly, 19 (4), 465-485

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