IBM and Accenture Shift the Way They Go to Market. Should Others Follow?

Labels that can take on lives of their own fascinate the technology industry. Big data represents a label with hype that far exceeds its utility. Technology enables big data to store exponentially increasing information in structured and unstructured file formats. Cloud drives down the price points for the bare-metal compute and store required to warehouse data. However, it has yet to be seen how cloud and big data can be turned into business outcomes effectively.

Cloud’s ability to lift cost constraints tied to IT hardware represents a fundamental shift in IT, upending our industry’s conventional wisdom, hammering traditional go-to-market operating models and shifting and evaporating profit pools in ways that pressure the IT industry as never before.

It is cheap to capture transactional data streams (big data), push new systems of engagement and store unstructured data from social media streams (more big data) – so what?

Data Everywhere and No Time to Think

As the hype around big data increases rapidly, businesses are left to discern how to deliver more value based on having access to an exploding body of digitized record keeping of personal and commercial activities.

Mining actionable business value depends on what smart decision makers apply against big data. The melding of the systems of transaction, or the legacy back-office record keeping, with the systems of interaction, or the increased development and innovation around digital marketing channels, requires more than just information collection and storage. It requires a strategic re-evaluation of the commercial entity’s value proposition and access to the technologies and employee skills of “data science” that are in very short supply in the market today.

This re-evaluation and need for new skills represent a huge commercial opportunity for strategy-led consulting firms such as Accenture, Deloitte and IBM on the macro level and a very lucrative career opportunity for individuals possessing the requisite skills and natural inquisitiveness to consider the different possibilities for analytical scenario planning available to even the smallest of commercial enterprises. Bringing business value – be it from a brilliant data scientist with the scale, scope and reach of IBM or from a brilliant data scientist effecting huge changes at a small company – to disparate data will increasingly separate winners from losers.

Organizational Proof Points

The smartest IT vendors have started shifting the way they organize their IP assets and the way they go to market. Consider the following:

1. IBM intends to marry strategy consulting with digital and analytics. Strategy buoys services profit margins and digital extends it to the collection points, be it end-customer actions or machine-generated data capture netted out by the shiny term the “Internet of Things (IoT).” IBM will further the relevance to customers by organizing around vertical industries to extend the business value of its underlying technology offers.
2. Microsoft has the de facto industry standard for business communication in Office. It moves this to the cloud in Office365 and has the ability to extend the Office bundle with application-specific components around niche extensions for the specialized knowledge worker. Early extensions will be in broad-based horizontal applications such as Dynamic CRM, while TBR expects to see additional permutations tied to vertical industries such as healthcare, financial services, and science, technology, engineering and math (STEM) workers in industries such as oil and gas.
3. Accenture is betting on four growth platforms — strategy, digital, technology and operations — and relying on its ability to bring scale to its clients as a differentiator between itself and competitors. Scale, however, depends on technology partners and rapid go-to-market innovations. Accenture has a proven track record but must continue to execute successfully in what is a brutally competitive market.

Shifting lenses from vendors, one has to consider end-customer IT undergoes just as rapid a transformation that pivots on capex and opex cost considerations. Traditional IT devoted the majority of its energy to procuring, managing and maintaining on-premises infrastructure and providing the rationing point for competing line-of-business requests for the compute power. IT rose to prominence when large enterprise automation was a greenfield opportunity in the 1980s and 1990s and sank in stature once commercial business fully automated.

After discussions with large enterprise decision markers, TBR believes there are several end-customer evolution points transpiring:

1. IT as a P&L selling to lines of business: IT departments take on the hybrid cloud orchestration role of integrating on-premises and cloud application streams. On one side, they manage the infrastructure integration and capacity management planning functions, and on the other the self-service simplicity demanded of LOBs along with the metered billing required to drive the opex financial analysis down to the department level. This rapid deployment allows departments to “fail fast” in their development activities and promotional marketing campaigns.
2. Establishing parallel IT departments: Commercial enterprises split the IT function along similar lines. Legacy IT sits with the chief financial officer for the capex considerations of cost management and cost takeout. On the other side sits those internal IT skills sets required to work with LOBs in a “Bring Your Own Chief Information Officer” fashion to determine how best to harness cloud-enabled compute to quicken time to intelligence for the various business units.

Commercial enterprise will need strategic business advice on how to organize to best leverage the new business value within reach given the vastly different economics of compute and store. The advice will couple organization and change management with IT services built around harnessing big data to make big decisions based on business intelligence. Business intelligence enabled by analytics and by a strategic understanding of the possible creates a virtuous cycle in which more analytics applied smartly breeds demand for additional business intelligence.

Regional Implications

In Latin America the IT industry suffers from serious skills gaps. Some gaps exist simply because of the continued invention and creation of new ways to capture data as well as the technical methods necessary to stitch the assets together in ways that generate tangible business results. Beyond the region, some skills gaps revolve around technological integration; some revolve around business-specific model testing that must flow from the human brain and be translated through analytics into the binary code to direct compute to explore the combinations at rates far faster than the human brain can accommodate. In meetings with IT professionals in Guatemala in October, TBR was impressed with the technical knowledge and entrepreneurial verve – but everyone, including IT folks in Latin America, needs to adapt to an increasingly steep learning curve around analytics, business intelligence and the application of big data to business models.

For Latin America, this suggests the following:

• Skills: Strategic investments in education will buoy economic activity by bringing high-value jobs to the region. Knowledge work will require less capital investment to be possible but require additional and stronger STEM skills coupled with adaptability. The high-value technical skill today will be an automated piece of software tomorrow; therefore, today’s specialist will have to adapt their intellectual contribution to the industry at faster rates to stay relevant. Centers of excellence will have to shift and adapt continually, potentially making captive centers a model for midterm growth (as outlined in TBR’s reporting on Guatemala- and Costa Rica-based IT services vendors in October).
• Partnerships in all forms: Some argue Michael Porter’s Theory of the Five Forces has been rendered anachronistic to today’s economy. The speed of innovation, accelerated by analytics, means firms have to look more for complementary assets. The adage of “Make, Buy or Ally” for IP innovation has been reversed, with alliances first, acquisition second and in-house development third. Small regional services firms can arise and ally with critical knowledge firms as captive centers. Startups with a high-value, niche focuses can arise and be rapidly absorbed by larger IT firms. Governments likewise have to establish cooperative legislations to facilitate the free flow of ideas across sovereign borders to continue to make their locations attractive for strategic hiring investments. And governments must partner with IT firms to ensure investments in developing the business- and tech-centric English language skills of employees continue to be a top priority. TBR’s interactions with government-backed trade and economic promotion officials from across the region provided substantial encouragement that governments understand the stakes and support the IT industry.

The industry cannot change the underlying economic shifts impacting the business. However, smart companies can monitor and track disruptors while working to assemble commercial offerings, which resonate with commercial enterprises’ consumer IT capabilities. Key elements TBR is watching include:

1. Skill sets: The skills IT professionals need will shift rapidly to software functions as the industry increasingly abstracts its intellectual property from the firmware into software. How to monitor a virtualized or cloud environment requires vastly different skills than how to diagnose and physically swap out pieces of infrastructure. Companies must invest heavily in recruitment and training practices to identify the specialty skills needed and the behavioral traits that allow an individual to thrive in the increasingly demanding rate of change washing over our industry.
2. Solution sets: IT will increasingly be consumed on a try-and-buy basis of various integrated components rather than as a broad suite of “shelfware” sold on a transactional basis. Companies will have to listen intently to customers, develop adaptable solutions from disparate components and be able to provide timely service and support to accelerate the knowledge transfer to their end customers.
3. Automation level sets: Analytics allows for more rapid automation of complex tasks. Automation strips the labor component from services; therefore, the market landscape will have competitive differentiation level set to zero more rapidly on each innovation wave.