July 9, 2020

A Winning Data Strategy Series Part 1: Off to a Faulty Start

By Anita Raj

A Winning Data Strategy Series

This is the first piece of a 5-part series on plugging the obvious but overlooked gaps in achieving digital success through a refined data strategy.

Everyone is aiming for stellar digital success. A pricey ambition that has led enterprises to onboard top minds as Chief Data Officers, invest whopping amounts in the latest technologies and infrastructure, and proactively collect data from every source possible. Yet, despite all the heavy-duty investments, digital transformation continues to be an elusive unicorn for most even after a decade. A quick human mind-led troubleshooting pins down the wrong reasons as the faulty piece in the success equation here. Lack of skills, absence of enough data, technology that needs an upgrade, so on and so forth. However, oftentimes, if you dig deep enough, you’ll realize the real problem lies in a faulty start – the absence of a refined data strategy.

Let me make this simpler to understand. We’re all aware of how staying fit works, right? It does not take a genius to know that simply buying the best gym equipment or hiring a celebrity fitness expert won’t automatically make you fit. Rather, these are mere facilitators in your fitness journey. What can truly drive your fitness aspiration to success is a clearly defined fitness plan. Do you want to lose weight or gain muscle mass? What kind of workout or routine is feasible for you? What should your diet plan look like? And, if in 2-3 months’ time, something isn’t working, how can you work towards making amends?

Your digital transformation journey is just like your quest to become fit. While it is great to be investing in the latest technologies, hiring an executive-level data expert, and collecting data from all possible sources, the first and most important step to be taken is to build a winning data strategy.

So, what does a winning data strategy look like?

A winning data strategy:

  1. …sits in alignment with your business strategy: Your IT team will facilitate your digital journey. But if it becomes the sole responsibility of the IT team, you will end up losing sight of the bigger picture. Should data improve supply chain efficiency by 20%? Should it reduce customer turnover by 10%? Or, should it enhance accuracy in frontline decision-making by 5%? These are business perspectives of your data strategy, an absence of which can often divert the focus to more technical aspects – Is the data secure? Does the technology fit in with the current organizational setup? Are the systems data compliant? These are important questions to ask, of course, but it can’t be the guiding pillars of your data strategy.

  1. …brings together all stakeholders to work collaboratively: Only the IT team cannot drive a data strategy. Nor can process, IT, and leadership teams working in isolation. A winning data strategy requires a culture shift where different teams within an organization can shoulder their responsibilities in the bigger picture and work in collaboration to drive the collective vision. Say, for instance, a data-driven effort to reduce customer turnover will require the combined efforts of the customer relationship, marketing, sales, and product marketing teams to bring their unique perspectives and knowledge for success.

  1. …follows a roadmap: You can never have a winning data strategy if you can’t track your progress. Where are you headed? What are the milestones to be reached along the way? How and when do you make changes if you go off-track?

Is there a tried-and-tested route map to a winning data strategy?

To the tee, maybe not. There is no one-size-fits-all approach to creating a data strategy. But over the years, experts in the field have suggested guideposts to building and implementing one. I would simply put it as the ‘5 questions to ask while creating your data strategy.’

  1. What’s your business problem? 

This is the starting point. Skip this step and no data strategy will ever take off to its full potential. Ask the simple question, what business problem can data solve for you. Can it enhance your business operations? Customer experience? Or, anything else?

Data strategy cannot be built in isolation. In fact, data is the means to achieve your business priorities. Don’t make the mistake of shaping your business problem around the data you have. Define your business problem first and then move to the next stage, which is, the type, form, and amount of data required to achieve this.

  1. Where can you collect data from?

Once the business problem is defined, it becomes easier to sort out the data that is required to work around this problem. Firstly, do you have all the data that is required? If not, you need to look at how to collect them. Other considerations would include, do you need structured or unstructured data? Only internal data or external data too?

It’s like, don’t simply start cardio because you have a treadmill at home. Draft your business problem and accordingly, use the treadmill if necessary or invest in a few dumbbells and a skipping rope too. Starting where your data is isn’t the best piece of advice.

  1. What are the infrastructure & skills required?

Let your business problem guide your investments in infrastructure and skills. Again, not the other way around. Based on the goal you intend to achieve and the sources of data, choose the right tools to collect, store, analyze, and communicate insights from the data. Once the tools are identified, you will be in a better position to recognize the specific skills required to best use these tools. A thorough understanding of the skill pool within the organization can help you hire competencies that you may not already have.

  1. What are your data governance practices?

One slip and data can go from being an asset to a liability. Protecting your vast pool of data from leakage, attacks, and access by unauthorized people is critical. You must, therefore, actively engage in enhancing the quality, security, and privacy of all data. This will include defining who has access, where is it stored, permissions to gather and use data, and ethical practices in using data.

  1. How to implement and make changes?

This is the time to get on the playing field. At this stage, it is necessary to break down your larger plan into smaller actionable items and have different teams or members take accountability for their respective parts. Planning meetings to track progress and facilitating periodic revisions as deemed necessary by the overall team is crucial to success.

In conclusion…

Everything from data to infrastructure, tools, skills, and manpower are meaningless unless guided by an overall data strategy. And now that we have established the unequivocal power of a data strategy in enabling you to achieve digital success, it is crucial to also look at some of the most common mistakes or assumptions made while developing a data strategy, in the upcoming posts.

By Anita Raj

Anita Raj

Anita is a Germany-based technology evangelist with more than a decade of experience in Cloud, Big Data and AI. Previously, Anita has held product leadership roles in international markets such as UK and Silicon Valley for Fortune 100 companies such as Progress Software, Dell EMC and Infosys. LinkedIn  Twitter @anita4tech
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