- an enabler for Social
- an enabler for Mobile
- an opportunity to offer services as well as a different way to deliver IT
- enabling new business services and models that would not have existed before
The final bullet is the topic of this blog post. I think that the coming together of trends in consulting innovation along with the opportunities provided by cloud computing can enable a better form of consulting services. Let me explain how.
The use of data analysis to support consulting recommendations is not new. McKinsey is well known for its fact-based consulting methods that draws heavily on data gathering and analysis. Deloitte (where I work) is also a well-known business consulting firm that uses a robust data driven approaches and benchmarking for developing strategic recommendations. However, the achilles heel for such data-driven consulting has always been the difficultly to get a representative data sets for comparison. In the past, we have had to compile data manually from numerous sources. Often the sources would be structured differently and not give the same perspective across companies in a given study. Internal company taxonomies had to be understood and translated so that the data was interpreted accurately. Due to these challenges, it can be very difficult to get large numbers of companies involved in any kind of benchmarking comparison due to the time-consuming and sometime subjective nature of the data gathering and analysis process.
So how does cloud help?
Imagine the 100,000 customers today running in the multi-tenant database architecture of Salesforce.com. While the exact configuration of each customers' application will vary slightly in specific places , the majority of those customers are running a high-level standard model that can be compared. Every opportunity management processes divided into a number of clear stages, data is structured in the same way, accounts are related to opportunities which in turn are related to sales reps. Due to this standard model, we can (or Salesforce.com could) very easily create an analysis across this data set to show key metrics across the sales domain. Important metrics that show insight into the performance of the business such as:
(1) the average time taken for a newly created Sales Qualified Lead to reach a Closed-Won deal (velocity of the pipeline)
(2) the average number of opportunities at each stage of the pipeline (the shape of the pipeline)
(3) the average revenue of an opportunity and value of the pipeline for a given quarter in a specific industry (the size of the pipeline)
With a bit of work from Salesforce.com customers and population of a few additional fields in database, users could help Salesforce.com automatically interpret the data so that more detailed metrics could be gathered, like the number of sales managers vs. sales admin or the velocity of sales through sections of the pipeline. And did I mention you have 100,000 data sets here? This would give you a representative data sample and metrics for almost any industry.
This idea itself isn't new. I chose Salesforce.com as an example because it's the most populous SaaS solution out there. However, the cloud vendor Eloqua has already tackled this market with their Revenue Performance suite that measures marketing process metrics. But it doesn't stop there. As the industry continues to migrate to cloud-based solutions, there will be many organisations running large portions of their business with cloud providers in the future. HR processes might be supported by Workday. Perhaps financials will be run on FinancialForce. Netsuite might take on Order Management and Supply Chain. With all of these cloud solutions, customers will store their data in a similar way in the same cloud database which in turn can churn out a decent set of comparable benchmarks with little effort.
The final link becomes interpreting the metrics and turning the insight into action. The ability to do this and improve business performance will seperate the leaders from the followers and this is where consulting 2.0 comes in. The business consulting field has changed very little since over the last decade with the key progression being "outcome-based consulting"where a consulting firm links its fees to improvement in an agreed metric of business value like cost reduction for example . There is much more innovation to come in the consulting model given the competitiveness of the market - see this post by Daniel Krauss. One way for consulting firms to address this is to move further towards recommendations based upon deep data analysis of the specific client and industry. By partnering with the cloud vendors who can produce the metrics, a consulting company could utilise the data and metrics available in the cloud data sets and provide consulting specialists to interpret these results through statistical analysis and mathematical models. In addition, leveraging the powerful but affordable burst processing power the cloud offers and utilising services like Hadoop, Teradata and Netezza, consultants could utilise the enormous data sets (so called big data) available from the cloud. The specialist skills required to carry out this type of work would be of clear value to a purchasing organisation when embarking on a performance improvement exercise.
To get an idea of the possibilities, just look at what Pete Warden has done scraping 220million Facebook profiles and analysing the data. Building business strategies founded upon the insight provided by this kind of analysis turns consulting advisory work into much more of a science. Furthermore, we can use outcome-based commercial models to link payment for our services back to the metrics we are improving. This all might send shivers down the spine of some consultants but only those that are afraid to be judged on their results. Probably a good thing for the market as a whole.
So there it is... a new (or at least much evolved) business service for the consulting industry enabled by Cloud Computing.
That's why Cloud Computing + Consulting 2.0 = Data Driven Consulting :-)
