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You can’t make an omelette without breaking a few eggs, so goes the saying

You can’t successfully become a data led organisation without the right leadership.

A recent study, conducted by Forrester in collaboration with Atos, found that the adoption of data analytics is already at 40% and is set to grow to 90% by 2020, but most organizations continue to struggle when it comes to moving from raw data to insights.

Nowhere is the need for data insights more prevalent than in the financial sector.

The use of low level data in financial services has been known since the dawn of modern practices but the core industry has not been as successful as others when it comes to moving to data centric business models.

There has been a brain-drain of existing and potential talent to FinTech start-ups and other more enticing industries. As reported in 2014 by The Economist, MBA students did not see banking as entrepreneurial and not somewhere they could make an impact. This shift has continued to now as earlier this year the Financial Times reported that Fintech is luring MBA graduates away from the banking and consulting industries because “Salaries are less of a concern to those who aim to be agents of disruption”.

The loss of MBA graduates may seem like a minor thing, but who will lead the change needed to help Financial Services catch-up with other industries? An Executive MBA graduate is twice as likely to work in Technology now as they are in Finance or Accounting.

Though financial services organizations can better use data across their organizations in high RoI areas such as supplier management, product management and robotics, none of these areas were mentioned by respondents in the Forrester report. It is as if Financial Services is still taking the same approach at a time when the talent is busy disrupting the industry in a start-up, or they are busy disrupting other industries. With the convergence of business models and the encroaching threat of large non-traditional financial services providers (Google, Apple, etc.) how should Financial Services move forward?

To be a truly analytics led organization we already know the nine challenges that must be overcome with one of most important aspects being the presence of the right leadership to drive disruption and performance. Data and Analytics driven success begins and ends with analytical leadership. Without strong analytical leadership transformation efforts will not gain the direction and organization-wide support that is required in order for analytics to be put at the heart of the organization; strategic analytics goals must be fully devised, set out and communicated clearly with all relevant stakeholders.

Is the lack of a MBA (or similar) talent pool holding back a new wave of needed disruptive leadership in Financial Services, well it may be.

Somewhat unsurprisingly the median employee age in companies who are deemed as being disruptive is much lower than those in the Financial Industry - Amazon (32), eBay (30), Google (29) and Apple (31) versus Bank of America (32), Prudential (37), Western Union (35) and MetLife (36). For Goldman Sachs, the iconic disrupter in Financial Services, the figure is 29 years of age, the same as Google. So this may show that you can’t teach an old donkey new tricks, but it is the average employee tenure with an employer that really stands out - Amazon (1), eBay (2), Google (1) and Apple (2) versus Bank of America (4), Prudential (4), Western Union (7) and MetLife (5). For Goldman Sachs, the figure is 3 years, outperforming even Google.

It seems then there still is hope for Financial Services, indeed even in the wave of Automation and Robotics that is a key area of focus right now in the industry to lower cost income ratio’s that someone will need to lead these organizations to kick-start their own disruption efforts. I wait with trepidation that this may come too late for an already massively strained industry, but with Gen Y breaking through into leadership roles and soon Gen Z will follow, it’s not a case of ‘if’, but ‘when’ will end-to-end digital transformation come to the industry.

 

 Sources:

  1. Article: https://www.economist.com/news/business/21623673-graduates-worlds-leading-business-schools-investment-banking-out-and-consulting
  2. Article: https://www.ft.com/content/3d3583ea-1e0e-11e7-a454-ab04428977f9
  3. GMAC 2017 Alumni Perspectives Survey Report: https://www.gmac.com/market-intelligence-and-research/research-library/measuring-program-roi/2017-alumni-perspectives-survey-report.aspx
  4. Forrester report: http://go.atos.net/LP=573
  5. Atos whitepaper: https://atos.net/wp-content/uploads/2016/07/atos-consulting-whitepaper-analytics-hr-interactive.pdf
  6. Fortune 500 Employee Tenure report: https://www.payscale.com/data-packages/employee-loyalty/full-list

 

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Comments: (2)

Alexander De Lange
Alexander De Lange - Aurelia Financial Consultants cc - Johannesburg 09 October, 2017, 05:36Be the first to give this comment the thumbs up 0 likes

'The banking industry in (sic) has been dominated by a handful of big global or regional banks for 100s of years' ?? Memory serving, before Big Bang, in the mid-eigthies, there were some large banks, but certainly not global ones. And those were mostly large on a corporate business basis, retail was nice for cheap funding.

I fully agree that the need for data insight is as great in financial services as in any other data-driven industry. But I'm not sure that this approach underlines deficiencies in this regard. Is an MBA really the (only and) Holy Grail as far as data analysis is concerned? Let's also not forget that (a number of) those MBAs forgoing larger salaries for being agents of disruption, affect financial services anyway, through the influence that their disruptive technolgy roles have on the FSI industry.

 

Ketharaman Swaminathan
Ketharaman Swaminathan - GTM360 Marketing Solutions - Pune 09 October, 2017, 15:32Be the first to give this comment the thumbs up 0 likes

In my post Banks Will Know Chipotle Is Going Bankrupt Before Chipotle, I’ve quoted several examples of banks making excellent use of data gathered not only from the earth but also from the sky to make a quick buck. That said, banks may need to be more cautious than other industries in how far they go with data (probably because they handle money, which is different from goods and services). Like in the example quoted in my post, while customers say they want personalized offers and do like the ones they get from Uber et al, they tend to find the ones they get from banks quite creepy.

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Disruption in Retail Banking

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