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Data as an Asset Blog

Ten Signs Your Data Centric Program Will Fail, Even If You Seem To Be Making Progress

Every CxO knows that their enterprise must be data-driven to be successful in the digital age. There was a time, I remember CxOs used to ask, “why bother about data, when the business is doing just fine on it’s own?”

Well, today is a different world.

Every forward looking leader knows the cost of not investing adequately into data capabilities for their business. In-spite of this realisation, data-centric programs are tough nuts to crack.

Not every business is comfortable with successfully executing their data-centric programs. In this context, by data-centric program I mean all those investment programs that are initiated with an aspiration to gain massive business benefit through better utilisation of enterprise data, in the chosen business model. These could include, but not limited to cloud adoption, data analytics, data governance, master data management and the like.

The only measure for success is a positive impact to the bottom line. And nothing else!

Here are ten signs your data centric program will fail, importantly, even if you seem to be making “good” progress. The only measure for success is a positive impact to the bottom line. And nothing else!

  1. The executive team doesn’t have a clear vision for its entire data portfolio
    • With the best of intentions many executive teams are just not clear about their vision. With the endless possibilities that numerous technologies  and vendors offer today, it takes hyper-focus to zero-in on exactly what’s required to manoeuvre the business, over a fifteen to twenty year time horizon. Even if some of them are clear, their ability to communicate that vision consistently and coherently to mindsets seeded in a legacy culture is a challenge
  2. No one has determined the economic value that the initial use cases can deliver in the first year
    • In most cases business cases are developed “procedurally and abstractly” as opposed to clearly “defining done”. When “done” is defined, it forces accountability and responsibility. And not every one is comfortable in dealing with ambiguity.
    • Also, forcing definite outcomes demonstrating business benefit in the first year helps build sponsor confidence, with out compromising the morale of the delivering teams 
  3. There’s no comprehensive data strategy beyond a few use cases meeting immediate needs and perceptions
    • The language and the everyday tools used in an enterprise reveals the existence of a data strategy or not. It is crucial that a real data strategy exists and that it is measurable. More importantly, the key participants in the organisation should be clear about what the strategy is and what it is not. Often, strategy is assumed to be mere desk-ware. Of course, the data landscape of such organisations will reflect this reality, anyway. 
  4. Data centric roles—present and future—are poorly defined
    • Most mid-level and senior managers, tend to struggle with this shifting demands of new competencies in the workplace. As such, may poor decisions are made in defining roles accurately. Resulting in mis-management of talent.
  5. The enterprise lacks “datapreneurs”
    • Datapreneurs are experts at “Getting to Yes, Now!” with all available technologies and data. When programs fail at an alarming rate in an organisation or even it they are abandoned mid-way, it is certain that the organisations do not have the needed competencies
  6. Data capabilities are isolated from the business, resulting in an ineffective data organization structure
    • When a business model fails to recognise the role of data in creating value, data is under-utilised and not leverage to create business benefit. As a consequence the organisation set up is weakened, resulting in inefficiencies and ineffectiveness
  7. Expensive data-provisioning and uneconomic data integration efforts are initiated without adequate data management and governance foundations
    • Any data program is doomed, if data-nomics is not understood in the digital age
  8. Data platforms aren’t built to purpose
    • When data platforms are not purpose built, it is difficult for enterprises to justify the quantum of capital investment required to build and maintain one, that delivers true economic value to the business
  9. Nobody knows the economic value added by data centric initiatives
    • It is indeed very rare for the leaders in a data centric initiative to actually take the time to pen the true economic value of a data centric initiative. This is probably because historically, value propositions have been typically evaluated by finance functions. Whereas, the demands of today’s technology operating models require cross-functional collaborations, and not every business is able to pull this off, successfully
  10. No one is focused on embracing a data-centric mindset that embraces the ethical, social, and regulatory implications of data initiatives
    • Whilst recognising the critical role that data plays in an enterprise is one thing, realising that data has wider and external consequence in a business model context, is quite another thing. As such, addressing the ethical, social and regulatory implication of data is no more optional in the digital age. However, not every organisation is equipped with the right competencies to address this

For more information on how to organise and enterprise data for creating economic value, get your copy of The Billion Dollar Byte.

Why Digital Transformations In Governments, Need This New Competency

According to an IDC Insight, by 2020, as Artificial Intelligence is more widely adopted in back-office systems and citizen self-services, 15% of national government workers will shift their job roles to more complex, idiosyncratic tasks, problems, and interactions.

While governments throughout the world work to digitally transform, in order to provide better quality services to citizens, while improving the efficiency, effectiveness and delivery of government programs and services.

The primary challenge lies not in the availability of technology but rather in the lack of effectiveness by government organisations at scaling their digital business.

Gartner’s digital business survey was conducted from September through December 2017 among 372 digital decision makers in six countries (U.S., Canada, U.K., Australia, India and Singapore) and across six industries (financial services, government, manufacturing, retail, healthcare and education). It included 60 government respondents. To be included in the survey, all organizations had to have a minimum annual revenue of $250 million.

The survey results indicate a lack of effectiveness by government organizations at scaling their digital business and two possible internal barriers are envisaged, according to a senior analyst at Gartner. They were:

  1. Misalignment between digital strategy and business priorities, and
  2. A lack of urgency and readiness for change

While there is no question that our world will be paying a very high price for this, how can leaders in government organisations, start to eliminate these two barriers?

…we are all blessed with the ability to adapt, through learning.

Fortunately, we are all blessed with the ability to adapt through learning. The only challenge is to accelerate this learning.  To this end, in my book The Billion Dollar Byte, I introduce a new competency termed “datapreneurship”.

People with the datapreneurship competency know exactly how technology transforms businesses and they are naturally driven to get purposeful outcomes.

When governments invest in their datapreneurs, they have a better chance of successfully achieving their digital transformation ambitions. Without datapreneurs, governments are certain to grope around in dark ages.

Non-Techie: Are You Prepared For This One Skill Of The Future?

Regardless of your industry and profession, the reality is that technological advancements are creating tectonic shifts in our world and importantly, the the world of work and careers as we have known them both.

If you have started your careers in the nineties or earlier, coming to terms with these changes, is perhaps even more difficult.  This is often stressful, and manifests as job changes, career changes etc.

The good news is that there is a solution for this. And the solution is an ancient one.

Keep Learning.

But, what should you invest in?

The World Economic Forum’s Future of Jobs Report 2018, has identified top 10 emerging roles by 2022. This is a very useful piece of information for anyone, who is invested in nurturing their career roadmaps.

Here are the top 10 emerging roles which are expected to be a part of the jobs landscape in 2022:

  1. Data Analysts and Scientists
  2. AI and Machine Learning Specialists
  3. General and Operations Managers
  4. Software and Applications Developers and Analysts
  5. Sales and Marketing Professionals
  6. Big Data Specialists
  7. Digital Transformation Specialists
  8. New Technology Specialists
  9. Organisational Development Specialists
  10. Information Technology Services

On the other hand, here are the declining jobs in the 2022 landscape:

  1. Data Entry Clerks
  2. Accounting, Bookkeeping and Payroll Clerks
  3. Administrative and Executive Secretaries
  4. Assembly and Factory Workers
  5. Client Information and Customer Service Workers
  6. Business Services and Administration Managers
  7. Accountants and Auditors
  8. Material-Recording and Stock-Keeping Clerks
  9. General and Operations Managers
  10. Postal Service Clerks

While most of this is understandable, what stands out to me is the role of “General and Operations Managers”.

A decade ago, I was running a business in the hospitality industry, in India. It was manpower intensive. Needless to say, the role of the “General and Operations Manager” was the most critical. At that time, our business had hired some of the best talent in the country. Candidates were from elite Indian Institutes including a few who had excellent military experience. They were hired and paid to make decisions.

However, this day and age the role of the “General and Operations Manager” is a lot different. They are still expected to make decisions, no doubt about this. But, this time around, they are expected to be make decisions using technology and data.

The most competent ones are those whose, ability to act on data is high. The not so competent ones are those whose inability to act on data is high.

Where do you stand on your ability to act on data? This is one skill you should invest in, for sure.

To know more about how you can use data to create economic value and propel your career to new heights, get a copy of 2017 American Book Fest finalist The Billion Dollar Byte.