You Can’t be a Data-Driven Organization Unless...

If you are a new-generation nomadic traveler, the whole idea of randomly waking up one morning to pick up your backpack and head to an unknown, exciting destination sounds fascinating.

But when businesses start behaving this way, know for sure that they’re readying themselves for massive failure.

If you are unsure of where I’m getting with this, have a look at the data below:

The companies with Chief Data Officers (CDO) have grown from 12% in 2012 to 67.9% in 2019 with over 400 CDOs present across big and small organizations.

Does this mean that organizations have finally nailed the data game?

Sadly, the big revelation by the New Vantage Partners says quite the contradictory.

According to its 2019 Big Data and AI Executive Survey, 69% of the respondents that comprised of C-level business and technology executives report that they have not yet created a data-driven organization.

What was even worse was the downward spiral observed in organizations identifying themselves as being data-driven, from 37.1% in 2017 to 32.4% in 2018 to 31.0% this year.

After a decade of having witnessed the promising side of data and with organizations continuing to accelerate their investments in this field, the ironic revelation by New Vantage Partners urges us to think and think hard about why we are moving towards data regression instead of progression.

The unfortunate truth is, organizations seem to be working more out of fear than conviction.

There is a prevalent need to ride high on the new trend lest you get ousted in the competitive market.

But this blind-sided approach of reaching for a destination without a strategy has reduced businesses into new-generation nomadic travellers, headed towards a fancy destination but with no plans whatsoever.

And if you really want to judge how data-driven your organization is, simply compare yourself to the likes of Uber, Netflix and Amazon. Despite being B2C companies, they set the context right for the rest of the world.

If you really are a successful data-driven company, your journey will ride on data which means even the lack of access to data for an hour can have a crumbling effect on your business. Is that where you are at?

If not, then it is time to re-look at data from a fresh perspective.

Digital transformation, data-driven, AI-first or analytics-driven decision making are all great destinations to be at but the real journey for any organization starts with defining your processes and your data strategy.

To believe that the data you’ve been collecting will serve as the starting point to where you want to be is setting yourself up for failure.

In fact, according to a survey by Forrester, anywhere from 60 to 73 percent of all data within enterprises goes unused for analytics, let alone for driving innovation or creating new data monetization models.

It is high time organizations quit the plumbing approach to data strategy. Utilizing data to fix problems than approaching it in a more holistic and enterprise-wide way is the birthplace of disasters.

The real crux of a successful data-driven journey lies in identifying the business problem first and then working backward.

Here’s what I believe is an easy 5-step approach to building your data strategy.

1.What’s my business objective?

The fundamentally wrong but most common approach to handling data is, ‘Let me start with what I’ve got.’ If you’ve been thinking or doing the same, I challenge you to give it a different perspective. How about defining a business objective first - What is it that you’re trying to solve?

Once you have your overarching objective in place, create smaller objectives or goals that can be achieved in phases leading up to your final business objective.

2. What data do I have to meet this business objective?

Asses the data that you have accessible. Once a business objective is defined, not all data will be relevant data. Screen out your data basis your objective and also check for any dependencies on the external dataset too.

3. Am I on track?

Well-defined KPIs can keep you on track your journey. Choose your key KPIs that define your positive and negative outcomes. And keep a check on the progress you’re making basis these KPIs.

4. What does my outcome look like?

Visualizing your outcome is important. Understanding and analyzing your data to come to key conclusions or decisions is crucial. You cannot just run with what you finally get. Rather, you should be in a position to compare and contrast. To take the results to your management, you need to have a well-charted result in place.

5. What are the scopes for improvement?

There are going to be roadblocks and let’s be honest about it. This could be with the technology, people or process. What a roadmap of this kind can help you achieve is, identify these roadblocks and work out ways and strategies to tackle them.

Over and above having a defined data strategy in place, the success of your journey to becoming a data-driven organization also depends upon the data maturity of your business.

Does this process need a CDO or not continues to be questionable.

While 90% of companies are expected to have a CDO soon, a lack of clarity in the job role along with an inability to demonstrate actual business impact has been crippling the true value a position of this stature can bring about.

The fact is, data is going to proliferate.

The need for data strategy, governance and policies cannot be overlooked.

Over time, an impactful CDO function may be built to enable organizations to take a more strategic and holistic approach to data.

To Conclude..

Ultimately, when it comes to business, heading out on a spontaneous trip with no plans and just a destination in mind is a big no. When it comes to digital transformation, a roadmap a.k.a your data strategy is a must-have and is also the starting point for your path ahead.

In a quest to stay relevant and be on top of the data game, what organizations often miss out on is that the failure of the digital transformation journey is less about the technology and more about people and processes.

Ideally, I would say organizations need to take a healthy pause and assess where they are at and take courageous steps towards building their data strategy and data culture towards becoming a data-driven organization.