Stryker

In the world of business,it has almost become cliché to talk about having to balance ‘people, process, and technology.’ Data thought leaders would argue one should not forget about the data too!

Data has long been an afterthought; nevertheless, putting the spotlight on data’s importance has amplified in recent years. For instance, a simple google search brings up various trendy metaphors on the topic, such as ‘data is the new bacon,’ ‘…the new oil,’ ‘…the new gold,’ ‘…the new plastics,’ ‘…the new oxygen,’ ‘…the lifeblood of modern organizations,’ ‘data is an asset! Notwithstanding the level to which you may or may not agree with any of these, it is this author’s view that a focus on thoughtfully and intentionally managing our data is instrumental to the health and resiliency of our organizations in today’s fast-paced and highly competitive business environment.

And so, with so much talk about data and analytics, rather than elaborate about why there will never be a better time to take this on, let us presume everyone is onboard with this notion and either starting or well on their journey to successfully implementing a meaningful data strategy. ’Successfully implementing’ being the operative words, and drawing from a 27+ year career focusing deeply on the data space, here are my top 3 watch out for you to consider on your journey:

Data strategy is not about the data;it is about the business

It is about tapping into the data’s potential to inform and optimize business operations, improve stakeholder experiences to grow the business, proactively mitigate risk and safeguard the business.

 It is about tapping into the data’s potential to inform and optimize business operations, improve stakeholder experiences to grow the business, proactively mitigate risk and safeguard the business 

Clearly a tall order, this is the reason a comprehensive data strategy aiming to ‘manage data as an asset’ includes complimentary pillars like data governance and stewardship, data& information architecture, master data management, data quality, data science and analytics, information governance, data privacy, information security, relevant technology tools and platforms. With all this to consider, it is easy to make it about the tools and the data itself, disconnecting it from what ought to be its north star: data strategy ought to enable the business to reach its strategic objectives. Therefore, its priorities must coordinate with and support the prioritized business goals. At the same time, the business strategy ought to recognize data’s hugely impactful role in cross-functional business operations, strategic goals, and aspirations. Therefore,also actively be informed by this as it is being defined or refined.

One might say these are tables takes. Agreed, and yet we have seen it play out over and again: organizations tend to overlook and either underestimate the importance of data and information management or regrettably equate data strategy to bringing shiny new technology in-house. If technology were that silver bullet, we would have figured it all out by now!

It is not an IT-only undertaking

Unfortunately, many organizations fall into this trap, possibly because, as discussed in first heading, technology is seen as the solution to all and so often equated to data strategy. Being successful in implementing a thoughtful business data strategy absolutely takes a close ‘contractual partnership’ between functional and technical resources representing business and IT. Erroneous notions like ‘IT owns the data’ or ‘the business doesn’t get it’ signifies opportunities to raise awareness and home in both: effectively solving for it demands a lot more than IT skills, as well as what is really the root cause behind key relevant issues (for instance, why does unreliable, incomplete, or hard to locate data exist in the first place, subsequently causing various business processes to break or delay?) Business resources have distinct and critical accountability in resolving and managing these types of scenarios. So does IT. Short-lived or subpar attempts at this from across various industry verticals have taught us that business cannot do it alone successfully; IT cannot do it alone successfully, either.

It is easy to undervalue the criticality of people, culture, and organizational change management

Successfully implementing a data strategy involves (among other) getting people across functions, divisions, departments, and/or geographies to work together to define and then, in practice, start ‘speaking the same language.’ Think enterprise master data. For instance, does everyone understand and use constructs like product hierarchy, customer, supplier, global analytic KPIs, and even sales, all the same? Very few organizations have reached the level of maturity where this is true. To get there, it requires that folks replace old habits,typically in support of their silo, with new habits that consider cross-functional impacts. It requires carrying out day-to-day business in a culture of empathy, collaboration, transparency, communication, curiosity, listening, and learning from each other, oftentimes aligning on a path that benefits the enterprise and not one department over another. Intention, diligence, and measurable goals specific to driving and sustaining this organizational change are instrumental to successfully implementing a data strategy.

These 3 traps are quite common and agnostic of any industry. If I had to put it in a few words, I would say:

• drive with business value-relentlessly and consistently

• work together with the clarity of roles and expectations– it is a close partnership

• change is hard, do not forget to keep bringing the people along–data, system, and process silos all point back to people!

This list is not all-inclusive. There are many more industry lessons, critically important and relevant to successfully implementing a meaningful data strategy.