Plotting Your Data Strategy

by Oct 1, 2018

How to get started

In my last post, “21 Ques­tions You Should Be Asking of Your Data Strat­egy,” I inten­tion­ally seeded a sense of urgency…and it worked! Since then, I’ve received numer­ous inquiries about how to get started devel­op­ing an orga­ni­za­tion-wide data strat­egy, so here’s the skinny…

Devel­op­ing a compre­hen­sive Data Strat­egy is rela­tively new to busi­ness, yet it’s become table stakes for compet­ing in today’s compet­i­tive market­place. Inter­est­ingly, recent survey results published in the Harvard Busi­ness Review demon­strate that large enter­prises who don’t have a strat­egy in place are increas­ingly worried. Disrup­tions from star­tups that have nurtured data-driven cultures from their begin­ning and inno­v­a­tive stal­warts who are rewrit­ing culture are leading the way. Whether your enter­prise is estab­lished or burgeon­ing, large or small, there has never been a better time to ensure that you’re program­mat­i­cally working to harness the power of your data.

Step One: Determine Who Owns Your Data Strategy

Several common chal­lenges must be navi­gated in order to build a durable data strat­egy that will accom­plish your desired busi­ness outcomes. Chiefly, differ­ent roles within any company have differ­ent perspec­tives and decid­edly differ­ent needs. Those clever creatives in your Market­ing depart­ment already have a plethora of tools and systems in place. Your Finance wizards and your agile Sales Force both hammer spread­sheets and likely have home­grown systems to manage all their moving parts. HR, too, and merchan­dis­ing use special­ized tools tucked into the corners of your tech­nol­ogy stack. And then there’s your Analyt­ics and Insights teams that come with their own means and measures for plying their craft. Pretty much every tech­nol­ogy in your stack and every indi­vid­ual in your orga­ni­za­tion has their very own methods for accom­plish­ing their aims. And (almost) every­one also has their own data silo. While each tech­nol­ogy is capable of collect­ing data aligned to their vision of the world, it takes effort and plan­ning to pull together all those vistas to see the whole ecosys­tem.   

And someone needs to see your whole world.

So, find that hero. And support them with a consis­tent and unified view of data. While this doesn’t neces­sar­ily need to be a fully feder­ated data lake, the perspec­tive into aggre­gated data must take into consid­er­a­tion a modern multi­plat­form data archi­tec­ture. This setup must enable your Chief Data Officer (or what­ever title you bequeath) to manage data, govern it, and make it acces­si­ble for myriad forms of analy­sis and utiliza­tion. Lots has been written about the role of the CDO, here and here…so I won’t write the job descrip­tion. I’ll just leave it at this: owner­ship and account­abil­ity over data are crit­i­cal, so make sure someone is securely holding the bag.

Step Two: Assess Your Data Strategy Readiness

Readi­ness is a funny thing. Are you ever fully ready to plunge into the deep end? As the apho­rism goes, Perfect is the enemy of good. This is true in data strat­egy as well. However, it is impor­tant to under­stand where your strengths are and what needs improve­ment. Take stock of your data and under­stand what you have and how you can use it. This is partic­u­larly impor­tant today because of GDPR and upcom­ing CCPA regu­la­tions that will impede you from using data any old way you choose. So under­stand what’s avail­able in customer data, across your propri­etary systems, and what you can access from 3rd parties. Your data strat­egy must encom­pass all sources of data with clear cut poli­cies about how you can use it.

Of course, using data assumes that it’s acces­si­ble. Having a compre­hen­sive data strat­egy means that data is avail­able to users across your busi­ness. Gone are the days of hoard­ing data and only provid­ing access to a precious few, satis­fy­ing the rest with Excel reports or (please no) PDF print­outs. Lever­age the power of your people and elevate data liter­acy to assure that your data will be used consci­en­tiously.

This is yet another reason that data archi­tec­ture is so very impor­tant. By linking require­ments to solu­tion docu­men­ta­tion to outputs, you have a better chance of main­tain­ing data integrity. And most BI aggre­ga­tion tech­nolo­gies will offer gover­nance proto­cols that help you manage and certify datasets, so that they are used for their intended purposes.

Being ready also means using your data with purpose. To do this effec­tively, prior­i­tize time for data quality and liter­acy, because you will want to auto­mate things. Automat­ing data is a ninja-level stan­dard for acti­vat­ing your data. But it doesn’t have to be compli­cated. Simply using alerts, trig­gers, and rules-based events can be the first stage in automa­tion. Then, you can get fancy and start build­ing models and employ­ing machine learn­ing and arti­fi­cial intel­li­gence. As you delve into ques­tions about your data strat­egy readi­ness, assure that you know exactly what data you have, how it’s held together, and what oppor­tu­ni­ties and risks you face when it comes to automa­tion.

Step Three: Build an Executable Data Strategy

You’ve prob­a­bly heard of (or expe­ri­enced) consult­ing firms offer­ing huge, mono­lithic Data Strat­egy roll­outs that span years and require massive enter­prise heavy lifting. But here at Search Discovery, that’s not us. We build bite-sized strate­gies that get you off the blocks running. Each compo­nent of our data strate­gies deliv­ers results and adheres to a plan to help you achieve busi­ness impact. Executable data strate­gies are depen­dent upon a data and analyt­ics ecosys­tem (we can help with that too), which provides the infra­struc­ture, the people, and the processes to move at an agile pace. By start­ing with executabil­ity, we are able to iden­tify what is impor­tant to you and then build 3–6 month strate­gies that “ladder up” to a north star strat­egy that we collec­tively define.  

What Getting Started Looks Like:

The data strat­egy projects we’re deliv­er­ing, whether the client is a non-profit corpo­ra­tion, large regional health­care orga­ni­za­tion, or multi­na­tional Fortune Global 500 company, all have a similar work­flow process. We begin by under­stand­ing what the orga­ni­za­tion is working towards. Since our strate­gies are all bespoke, they’re built upon a solid under­stand­ing of each clients’ goals and objec­tives. These are specific to the group/department/business unit that brings us in. But they also consider the larger corpo­rate culture, IT infra­struc­ture, and resources. We align the strat­egy to this context and proceed to define specific purpose for their data.

Once that phase is complete, we work to develop desired outcomes that are key compo­nents of the strat­egy. These outcomes are the results that have a measur­able impact on the busi­ness. We work tire­lessly to deliver. Yet, doing so typi­cally requires devel­op­ing foun­da­tional elements like data gover­nance prac­tices, measure­ment frame­works, stan­dard oper­at­ing proce­dures, and acti­va­tion proto­cols. We strive for align­ment. So, through­out our engage­ments, commu­ni­ca­tion is key.

Finally, we advise, support, or deliver on the actual imple­men­ta­tion of the strate­gic plan. This may include passing off a detailed plan for execu­tion that you, the client, will own, or some­thing that we support through train­ing and road­shows across busi­ness units to drive adop­tion. In many cases, we’re deploy­ing tech­nol­ogy or config­ur­ing appli­ca­tions. But in all cases, we’re setting the busi­ness up for success as defined by the executable data strat­egy that we’ve created. Change manage­ment almost always plays a role in the adop­tion and imple­men­ta­tion of our projects, and it’s some­thing that we love to do for you OR to coach you to take on inde­pen­dently. But the bottom line is that we set you up to succeed. Our strate­gies are stress tested and proven on the basis of what works for your orga­ni­za­tion.

Need help build­ing out your data strat­egy? Drop me a line at I’d love to chat and help you get started.

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