By: Sachin Kamath, Principal Director – Data Engineering, LTIMindtree

Data strategy is an essential component in the new world, and every organization has either created or refreshed or wants to create one. This is a humble attempt at compiling a list of considerations before one embarks on a Data Strategy exercise. How deep you go into these considerations or how well your strategy brings these into real-world discussions can highlight the difference between success and failure to implement your strategy.

Business problems solved – This is the single most important factor. If your data strategy is not solving any business problems or uplifting your business, then you are wasting your time. And it’s not just the promise of solving problems. You need to:

• Define KRAs and KPIs that can tangibly articulate the business benefit that will be delivered on implementing the strategy.
• There must be a clear lineage that will allow senior management to envision how every component of your strategy will contribute towards achieving the KRs/KPIs defined.
• There must be a provision to measure and track the impact at an enterprise level.

Of course, there will be some non-tangible wins that happen along the way, but these should be considered as a bonus rather than the main outcome. Keeping the business involved and a major participant in all discussions leading up to the strategy is a must. A common challenge with Data Strategy is that it’s perceived to be an IT prerogative, and businesses cannot really spend too much time on this. If this challenge can be overcome, you can be sure that you are solving the right things.

Know your data – Do you really know the data that you already have? How is it being used? What else can you do with it? Once you have answers to these and other related questions, then you might want to look at what other data you need. Where to source it? And all the “Art of possible” questions. Some of you will resonate with such responses as ‘Hey! We already have this’ or ‘we already do this’ when external consultants present the data strategy. This is not anyone’s fault most times. Enhanced business value cannot be measured unless we know where we started, where we are, and where we want to go. You need to carve out a way to baseline and then build on it.

Organizations need to define a “Common Data Language” so that everyone understands and means the same thing. This language needs to be defined for each organization and not just assumed that implementing a Data Governance tool will do the job. Tools will help you communicate and enforce better. This is the game-changing piece for any strategy to be successful in today’s world. It must bring together Business and Technology to speak the same language when it comes to data. Easier said than done.:)

Do you really need it? – One of the killers of a good strategy is the overwhelming need to propose the best-in-class, latest, and greatest ideas/platform. Most times, this gets the team into analysis paralysis, especially with so many options now being available for tooling, modeling, choosing patterns, frameworks, and the list goes on. Also, the costs burgeon, funding becomes an issue, and unless you have done an awesome job of articulating the business benefits and return on investment, your strategy won’t get the funding it requires. It’s good to be a minimalist here and focus on the least you can do; it will get the most for your business.

For example, do you need an enterprise-wide, real-time data ingestion platform if you still haven’t been able to define a significant number of use cases that will change your business when data becomes available in an instant? In most cases, when you dig deeper, you will realize the uplift provided between deriving the insights based on real-time vs. day-old data is not really a game changer. You can always have fast follower phases and build upon your minimalistic vision. Remember, once you have proven your strategy is redefining business, then funding will never be an issue.

Data culture – organization change management – “Culture eats strategy for Breakfast” – said Peter Drucker. This does not take away in any sense  the importance of a strategy, but rather emphasizes the critical need for an empowering support system for the strategy to be successfully implemented. An organization that wants to be data-driven, must think “Data First” and imbibe “Data by Design” thinking into its people strategy, business strategy, product strategy, decision making, sales, operations, and every walk of its business  at every level.

You can only do this if your entire organization is living and breathing these paradigms and not just a slice of your organization (typically the CDO). The power of decision science and advanced analytics is no longer just a business intelligence exercise. Organizations that can understand and adopt this power in every segment and decision making (in an acceptable, ethical, and auditable manner) will be the ones who  will truly be using data and technology to redefine their business and disrupt the market. Data Literacy -Awareness, acceptance, and training at every level will ensure greater success.

Keep the developer community in mind – This is the most overlooked part of the game. Seldom does decision -making consider the ease of adoption, maintenance, support system etc. that is required for the engineering teams to adopt, accept, and deliver the strategy. While there is nothing that a good engineering team won’t be able to do with some training, the “voice of this team” can add valuable insights to the ‘how, what, why’ of your strategy. Making them a part of the overall exercise upfront, factoring in how this impacts them and incorporating interventions can significantly increase adoption. Once the engineering teams have bought into the strategy and are empowered to deliver on it, you can  rest assured about  the technical implementation of the strategy.

Bringing this all together in a large enterprise is not easy, but it is  extremely important if your strategy must move beyond the presentation and mindshare stage. How well you connect your data to your business will define how relevant you will be in the new world.