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Business Model Transformation | @CloudExpo #BigData #DigitalTransformation
Across a number of industries, we are seeing business models under attack
By: William Schmarzo
Feb. 19, 2017 12:00 PM
Business Model Transformation and What it Means to the Data Industry
I recently read an MIT Sloan Management Review article by Clayton Christensen’s recent book titled “The Hard Truth About Business Model Innovations.” While the article is full of great observations about business model transformation, the most important motivation for business model transformation is found at the end:
“..our understanding of the business model journey allows us to see that, over the long term, the greatest innovation risk a company can take is to decide not to create new businesses that decouple the company’s future from that of its current business units.”
We use the Big Data Business Model Maturity Index as a vehicle for engaging with our clients about how they can leverage data and analytics to transform their business models (see Figure 1).
Figure 1: Big Data Business Model Maturity Index
In light of the Big Data Business Model Maturity Index, the article really got me thinking about how the entire data technology industry is posed for a business model transformation. Let me explain.
Across a number of industries, we are seeing business models under attack. It may have started with the digital media industries (advertising, entertainment) but it has quickly spread into physical product and service industries such as retail, telecommunications, financial services, healthcare, education, travel, hospitality, transportation, distribution and manufacturing. Organizations within these industries are leveraging data and analytics to disrupt existing business models (and disintermediate customer relationships) as the boundaries that separate industries evaporate (see Figure 2).
Figure 2: Big Data Driving Business Model Disruption
I believe that same business model disruption (and subsequent customer disintermediation) is going to happen to the technology industry that spawned all of this transformation, and no technology industry has the opportunity to be a business model disrupter more than the data technology industry – the industry that gathers, stores, secures, provisions and analyzes the growing wealth of transactional, social, mobile, wearables, embedded, machine generated and publicly available data.
So I searched for a proxy that might provide some insights into the business model transformation of the data industry, which took me to the bottled water industry transformation.
Bottled Water Business Model Transformation
In 1977, Perrier launched a successful advertising campaign in the United States, launching the popularity for bottled water. Bottled water is currently the second largest beverage category by volume in the United States, behind carbonated soft drinks (CSDs). The Beverage Marketing Corporation (BMC) predicts that bottled water will surpass CSDs to become the number one beverage in America by early 2017 (see Figure 3).
Figure 3: Increasing Demand for Bottled Water (per Person consumption)
Despite having one of the best municipal tap water systems in the world, American consumers flocked to commercial bottled water for four key reasons:
A couple of key lessons that we can take away from the bottled water business model transformation:
Future of the Data Industry
Organizations have traditionally treated data as a legal or compliance requirement, supporting limited management reporting requirements. Consequently organizations have treated data as a cost to be minimized. The financial valuation of data technology companies has been based upon those perceptions and relationships. The below chart from Gartner summarizes the business model transformation challenge (see Figure 4):
Data technology companies tend to sell to the part of the organization where data is a cost to be minimized and the sales processes focuses on negotiating with Procurement on price, margin, terms and conditions, instead of engaging with the part of the organization where data is a corporate asset to be exploited for business value, and discussions focus on time-to-value and de-risking projects.
It would seem that anything that the data technology companies could do to increase the perceived and actual value of data to its customers and the market could dramatically increase their financial valuation. This includes leveraging data to deliver business outcomes such as:
This would require a business transformation for technology companies in order to focus more on delivering business outcomes and less on selling technology piece parts with “some assembly required.”
Data Industry Call to Action
There is much that we can learn from other organizations that have transformational business models. Companies such as Netflix, Amazon, Uber and GE have created business models by focusing on the Customer Journey; by meeting customers “where they are and taking them where they need to be” and focusing on delivering business outcomes (or decisions in data science vernacular), not just technology piece parts.
But this needs to be done at scale; something a data technology company is uniquely qualified for, with the ability to create pre-engineered solutions and “collaborative value creation” platforms that couple hardware, software, and consulting to support the customer journey.
Data technology companies can be the pioneers in transforming their business models; however, they will not drive business model transformation by selling data as a commodity like tap water. Instead, data technology companies can exploit product development, sales, marketing and consulting to focus on delivering customer business outcomes at scale; helping customers to leverage and monetize their data assets to optimize key business processes, reduce security and compliance risks, uncover new monetization opportunities and drive a more compelling customer engagement.
 Here is some background reading for more details on this topic:
Plus, I am currently working on a research paper with the University of San Francisco titled “Applying Economic Concepts To Big Data To Determine The Financial Value Of The Organization’s Data And Analytics, And Understanding The Ramifications On The Organizations’ Financial Statements And IT Operations And Business Strategies” where we will put forth a framework and supporting processes to help organizations to determine (estimate) the economic value from their data.
The post Business Model Transformation and What it Means to the Data Industry appeared first on InFocus Blog | Dell EMC Services.
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