Dr. Martens Drives Knowledge Transparency and Transformation with Atlan

Legendary Client Model Improves Knowledge Discoverability, Influence Evaluation, and Enterprise Collaboration on Knowledge

At a Look

  • Dr. Martens, an iconic world footwear model with a six-decade heritage, evaluated the information catalog house as a way to drive self-service atop their rapidly modernizing knowledge stack.
  • Selecting Atlan, their knowledge crew rapidly applied a self-service catalog to supply context round their most crucial knowledge belongings.
  • Atlan’s implementation has accelerated time-to-insight for Dr. Martens’ inner knowledge shoppers, and is decreasing time spent on impression evaluation from 4 to 6 weeks, to beneath half-hour for knowledge practitioners.

Dr. Martens is an iconic British model based in 1960 in Northamptonshire. Produced initially for staff searching for powerful, sturdy boots, the model was rapidly adopted by various youth subcultures and related musical actions. Dr. Martens has since transcended its working-class roots whereas nonetheless celebrating its proud heritage and, six many years later, “Docs” or “DM’s” are worn by individuals world wide who use them as an emblem of empowerment and their very own particular person perspective. The Firm is a constituent of the FTSE 250 index.

Of late, Dr. Martens has been steadily rising and evolving its enterprise, with 52% of their gross sales direct-to-consumer in FY’23. Essential to this development, previous, current, and future, is a visionary knowledge crew that provides fashionable expertise and insights to their enterprise colleagues tasked with making one of the best selections attainable.

Amongst these knowledge visionaries is Karthik Ramani, International Head of Knowledge Structure for Dr. Martens.

“I began off from a person’s perspective in a Enterprise Intelligence position, then Knowledge Warehousing, then Knowledge Engineering earlier than stepping into Knowledge Structure. I’ve had visibility into the end-to-end of information, and I’m obsessed with guiding individuals to get essentially the most worth out of information, processes, individuals, and frameworks,” Karthik shared.

And answerable for guaranteeing Dr. Martens’ knowledge is ruled, accessible, and contextualized is Lawrence Giordano, Knowledge Governance & Technique.

“I discovered myself in Knowledge Governance as a result of I’m obsessed with it. I’m right here to show that it’s not purple tape, and it’s not about stopping individuals from doing stuff,” Lawrence shared. “We are able to supply curated knowledge units whereas additionally taking care of our knowledge the proper manner. Knowledge Governance truly permits different capabilities to do their jobs higher.

Delivering Sustainable and Worthwhile Progress

Guiding and prioritizing Dr. Martens’ enterprise and expertise selections is the DOCS technique, representing 4 pillars of Direct-to-consumer First, Organizational and Operational Excellence, Client Connection, and Assist Model Growth with B2B.

Current examples of execution on this technique embody opening new retail shops in current and new markets with omnichannel experiences, supported by expertise modernization and provide chain enhancements.

“Most initiatives at Dr. Martens will affiliate themselves to a type of core pillars, and we’re no totally different. On the information crew, we are able to hyperlink ourselves to all 4, however particularly Organizational and Operational Excellence,” Lawrence defined.

Powering DOCS with the Fashionable Knowledge Stack

Among the many most necessary methods the information crew helps the DOCS technique is a brand new manner of working, an agile, product-led supply methodology the place analysts and engineers are embedded inside product groups. Interacting with their enterprise colleagues day-after-day, and proudly owning the outcomes of their work, signifies that Dr. Martens’ knowledge crew higher understands the enterprise drawback they’re serving to to unravel.

Prepared and in a position to help these enterprise capabilities is a crew construction composed of 5 core capabilities, Knowledge Engineering, Knowledge Structure, Knowledge Analytics, Reporting, and Knowledge Governance, reporting into the Dr. Martens International Knowledge Officer, Nick Sawyer.

“It’s a matter of how we get all these capabilities to work easily with one another to unravel a enterprise drawback, which could not match neatly into every of those pillars and requires us to return collectively,” Karthik shared. “Our focus has at all times been to align to enterprise targets, and on how we are able to drive worth from the information and ship to the enterprise.”

Persevering with by its fast development part, and remodeling into an organization that providers prospects throughout a number of channels, together with digital, knowledge performs a extra necessary position than ever in guiding Dr. Martens’ selections, driving their crew to rapidly modernize their knowledge stack.

As a part of our transformation, we acknowledge that knowledge is a basic and a crucial pillar to understanding our prospects’ experiences and wishes, and guides how we are able to enhance and optimize. There’s been important funding in modernizing our knowledge platform to deal with challenges. We wanted to maneuver in direction of a single supply of reality, and improve the reliability and scalability for delivering insights for the varied departments we serve. We’re primarily eradicating expertise as a barrier to utilizing knowledge and discovering insights.”

Karthik Ramani, International Head of Knowledge Structure

Beginning with Microsoft Azure as their cloud supplier of selection, Dr. Martens’ new, best-of-breed knowledge stack consists of dbt for transformation, Snowflake as their knowledge warehouse, and PowerBI for reporting and visualization, offering a contemporary basis for additional development.

Driving Knowledge Transparency with a Fashionable Knowledge Catalog

With a brand new manner of working that prioritized a better relationship between the information crew and their enterprise counterparts, and with an array of latest knowledge expertise, Dr. Martens’ knowledge crew wanted a technique to make these new capabilities and belongings clear and comprehensible to a spectrum of inner knowledge shoppers.

Making a “Restaurant Menu” for a Fashionable Knowledge Stack

Transferring from legacy expertise into a contemporary atmosphere, Karthik and Lawrence sought a platform that would function a “knowledge menu”, presenting essential context about their knowledge belongings in a straightforward to know method.

“Transparency of information possession, lineage and high quality was going to be an enormous driver for us if we have been actually going to demystify our knowledge property,” Lawrence defined.

Within the absence of a contemporary knowledge catalog, questions on knowledge would proceed to drive a expensive back-and-forth, the place knowledge shoppers wanted to succeed in out to the information crew every time they’d easy questions on definitions, freshness, and calculations.

“There was an enormous period of time that was spent by our knowledge crew on info questions like ‘The place do I discover this metric?’, ‘How is that this metric calculated?’, or ‘The place does this area come from?’,” Lawrence shared.

Introducing self-service functionality would imply not solely important time financial savings for technical groups usually tasked with answering these questions, however considerably accelerated time-to-insight for his or her enterprise counterparts that have been wanting to benefit from Dr. Martens’ knowledge.

Furthermore, working throughout dozens of markets and areas meant the information crew was delicately balancing the wants of the worldwide Dr. Martens entity with the distinctive, localized wants of assorted working items. Metrics and KPIs in a single market could be outlined otherwise in one other, making it tough to talk a standard language, and ship frequent capabilities.

“It’s a must to work to carry this collectively in a knowledge layer, however there’s additionally the metadata layer, the place you need to outline data and possession for these belongings,” Karthik shared. “That was one other robust cause for creating not solely a single knowledge layer in Snowflake, however complementing it with a single metadata layer in Atlan.”

A Enterprise-focused Analysis Course of

Fairly than working their analysis with knowledge crew members solely, Lawrence insisted on enterprise involvement from the very starting of their course of. Dr. Martens’ knowledge catalog would fail with out sturdy enterprise adoption, and the inclusion of those stakeholders within the analysis would make sure that they understood the issue being solved, have been champions for knowledge transparency and velocity of supply, and that they offered worthwhile suggestions on the person expertise.

“How does a person contact and really feel the product? How actively can they have interaction with out a number of course, and the way will we flatten the educational curve? How will we be sure that if we’re going to onboard 100 customers once we launch the product, that it’s going to be a seamless course of? Will they want hand holding throughout days, weeks, or months of coaching, or is it one thing they will naturally choose up?,” Lawrence shared.

Most necessary to Lawrence, nevertheless, was a sandbox atmosphere of Atlan provided in the course of the proof of idea that consumed Dr. Martens’ precise metadata, somewhat than well-curated samples, and ensured that after they performed person testing with the enterprise, that the outcomes would carefully mirror their future expertise.

In a proof of idea, except you have a look at it, really feel it, and use it with your personal group’s knowledge ecosystem, which will be messy and brings its personal challenges, you may’t see how the device adapts to that. It is advisable finally give your sponsors and customers, who will probably be utilizing this device, the power to get hands-on and say what they do and don’t like. It will get them extra engaged within the course of.”

Lawrence Giordano, Knowledge Governance & Technique

Lastly, Lawrence and Karthik began constructing their analysis standards by contemplating what they didn’t need in a contemporary knowledge catalog, somewhat than what they desired, guaranteeing they solely evaluated platforms with out “dealbreakers”.

Starting by avoiding options that imposed expensive integrations to their fashionable knowledge instruments, their final focus was on usability, guaranteeing that their enterprise colleagues might simply undertake the platform.

“We have been clear that this was not a tech answer, and it wasn’t being constructed for technical groups. It’s for the enterprise, and by the enterprise,” Karthik defined.

A Collaborative Implementation of Atlan

Having chosen Atlan as their fashionable knowledge catalog, Karthik and Lawrence rigorously deliberate its implementation. To make sure Atlan was not perceived as “simply one other device”, they adopted a philosophy of deep engagement with their enterprise colleagues, opted for experiential studying the place knowledge shoppers might uncover capabilities of their new catalog, and thoroughly thought of their first use instances to make sure the utmost attainable early impression.

Making certain Sturdy Enterprise Engagement

Persevering with the partnership they constructed with enterprise colleagues in the course of the analysis part, Dr. Martens’ knowledge crew started rollout with a collection of workshops to higher perceive potential use instances, and to construct champions for Atlan.

“We’re bringing in fashionable knowledge instruments to boost our knowledge journey, however Atlan could possibly be seen as simply one other device, in a form of fatigue for finish customers. We wished Atlan to be on the forefront of individuals’s minds so if they’d a query on knowledge, they went to Atlan,” Lawrence defined. “We wished to carry them on board in a fashion the place it’s not seen as simply one other activity they should do, however that we engaged them in a manner that they have been a part of the journey, and so they wish to get to the ‘promised land’, too.

These workshops, supported by Dr. Martens’ senior management, ensured that the long run customers of Atlan felt empowered to contribute to, and devour the belongings made accessible on the catalog, and understood the worth of partaking additional.

Lastly, the early use instances constructed by the Dr. Martens knowledge crew have been decided by worth mapping classes, figuring out which enterprise groups would yield essentially the most profit from the platform, which capabilities of Atlan might ship these options, and that even the earliest customers would obtain worth, then evangelize for additional use.

Treasure Hunts for Context

With Atlan built-in into their crucial knowledge tooling, Lawrence started one other collection of workshops, energizing their enterprise colleagues to additional take part within the rollout. 

Starting with a showcase of the work they’d accomplished on Dr. Martens’ analytics fashions, they performed an Indiana Jones themed treasure hunt, the place customers have been tasked with discovering 5 items of data hidden in Atlan to retrieve a stolen gem. Providing Atlan swag like t-shirts, their enterprise colleagues rapidly started working discovering the knowledge, meaningfully partaking with the platform and constructing a deeper appreciation for a way they could use it of their day-to-day lives.

That was actually our energizing second. It confirmed how rapidly you may reply questions, however the huge takeaway from the workshop was that regardless that Atlan wasn’t in its ‘excellent state’, we have been coming into a part the place we have been group pushed. We have been encouraging them to begin feeding definitions into Atlan, constructing workflows, and approving curated knowledge. It was good to get their power ranges up and get them engaged within the course of. They might see how rapidly questions could possibly be answered, and the long-term good thing about taking part.

Lawrence Giordano, Knowledge Governance & Technique

Early Wins by Alignment on Phrases and Metrics

Knowledgeable by a trusting relationship constructed with their enterprise colleagues, a price stream mapping train that ensured early work can be impactful, and workshops to domesticate an informed, enthusiastic person base, Karthik and Lawrence started working constructing a metrics catalog, and a course of for conserving it updated.

Starting with sourcing definitions then enriching crucial metrics, the information crew assigned house owners to every of them, guaranteeing that when questions arose sooner or later, there was a subject skilled that would handle them.

“As our transformation undertaking rolls on, we’re presenting our analytics fashions to the group and that’s what triggers what we now name ‘The Atlan Course of’, the place we have a look at the analytics mannequin, determine what’s in there, outline it, and set up who owns it,” Lawrence defined.

With this “part one”, as Karthik and Lawrence describe it, underway, “part two” will contain the drafting of extra technical readmes describing transformation logic, tied to Atlan’s automated lineage, offering a wealthy understanding of Dr. Martens’ knowledge pipelines.

Realizing Cross-functional Worth

For Dr. Martens, self-service represents a major shift, driving transparency not only for datasets, however the sometimes tribal data that when existed round these datasets. Whereas their knowledge shoppers stand to profit essentially the most from this work, their knowledge crew now use capabilities like automated lineage to speed up challenge decision, and a “restaurant menu” for his or her fashionable knowledge stack is driving better appreciation for, and ROI from, the trouble spent on the information transformation undertaking.

“It’s about belief, confidence, worth, velocity to market, self-service functionality, and finally decreasing the barrier to utilizing knowledge,” Karthik shared. “Our enterprise customers are right here to unravel enterprise issues, to not sit in entrance of their reviews and spreadsheets spending hours sifting by knowledge.”

Past the short-term wins Dr. Martens’ knowledge crew can ship by enabling quicker velocity of supply and selections, within the years to return, Karthik and Lawrence predict that with knowledge shoppers crowdsourcing and curating metadata, a tradition of self-learning and possession will emerge.

Demystifying the Knowledge Property

Dr. Martens’ knowledge stack transformation is just not occurring in isolation. With a mandate to enhance the way in which their group operates, parallel initiatives to modernize something from their ERP to their Buyer Knowledge Platform are driving fixed collaboration between technical groups to make sure adjustments are applied easily.

“Being within the Knowledge Structure perform, I sometimes get bombarded by questions in regards to the wider tech transformation that’s happening and its impression on Knowledge & Analytics,” Karthik shared. “There’s a number of change taking place inside our provide chain system, our product techniques, our order administration system, and our buyer knowledge platform. All these new options are driving change in parallel to our knowledge transformation undertaking.

Earlier than the introduction of Atlan, every of those upstream adjustments meant a handbook technique of checking downstream techniques for potential impacts, requiring important human capital. However with Atlan’s automated lineage, Karthik’s crew can decide these impacts in an infinitesimal proportion of the time they as soon as wanted.

“I’ve had at the very least two conversations the place questions on downstream impression would have taken allocation of a number of assets,” Karthik defined. “Then truly getting the work achieved would have taken at the very least 4 to 6 weeks, however I managed to take a seat alongside one other architect and remedy that inside half-hour, saying ‘Should you’re altering the column identify or including an additional column, that is what it’s going to interrupt or impression.’”

Whereas their deal with their enterprise colleagues has rapidly pushed worth from Atlan, interactions with technical counterparts that lead to six-week time financial savings on costly processes construct extra inner advocates for Karthik and Lawrence’s work, and drive much more worth from Atlan.

“We did this collectively, and right away the Area Architect mentioned ‘Can I get entry to this platform, please?’ And I mentioned ‘Yeah after all. You may get entry to Atlan. Subsequent time you don’t have to return to us.’,” Karthik shared.

Making a Technical Transformation Actual for the Enterprise

Ideas like a cloud-based knowledge warehouse or a contemporary device for knowledge transformation could appear arcane to the information crew’s enterprise stakeholders, however their buy-in is essential to a profitable transformation. With Atlan serving to to drive higher entry to knowledge, and enhancing understanding round it, it’s far simpler for stakeholders to know the good thing about the information crew’s deal with modernization.

Selecting Atlan as a part of the transformation undertaking helped us to tightly couple the supply of a knowledge catalog with all the brand new, shiny instruments. However our predominant worth driver is attending to a single supply of reality, with everybody getting access to the identical data base, which is consolidated and curated by the enterprise. We have been fairly eager that the brand new working mannequin, primarily based on a single, self-serviceable knowledge catalog, meant altering away engineers, analysts, and finish customers conversing offline on chats and emails round knowledge.”

Karthik Ramani, International Head of Knowledge Structure

By adopting Atlan, the brand new capabilities afforded by Dr. Martens’ transformation undertaking are extra comprehensible and usable to their stakeholders, offering context about knowledge belongings and their possession for knowledge shoppers, and a fine-grained view into their knowledge property for knowledge practitioners, all accessible through self-service.

And going ahead, Atlan will probably be central to the supply of latest knowledge fashions, with enterprise groups required to supply definitions, descriptions, and possession in parallel to creating it accessible to knowledge shoppers.

“That is all data that, traditionally, would have been sourced from conversations, or different technique of a reactive nature. Now, it’s accessible and prepared for them, and so they get this as a part of the transformation that they’ve been patiently ready on,” Karthik shared. “It’s icing on the cake for them. We already see a change in habits as Atlan nearly begins to behave as a gatekeeper for what’s truly happening in our manufacturing techniques.”

Finer visibility into knowledge belongings, afforded by Atlan, is already driving behavioral change and extra proactive fixes, most just lately exemplified by Knowledge Engineering studying {that a} knowledge mannequin hadn’t been efficiently processed, leading to metadata not but accessible in Atlan. As extra knowledge shoppers onboard into Atlan, Karthik and Lawrence hope to see extra of this habits, resolving points earlier than finish customers even notice they’ve occurred.

“We already see that change in tradition and habits taking place, and we’re hoping to scale that up as we roll out extra,” Karthik defined. “I’d say it’s made an enormous distinction. From a knowledge crew perspective, this prolonged, further layer helps us do governance proactively, and never as an after-effect of the transformation undertaking.”

With Atlan as their “window to the information world”, the transformation undertaking’s myriad stakeholders perceive its advantages extra, extra assured that the information crew are doing the proper issues, specializing in governance, safety, and compliance proactively, along with modernizing their infrastructure and tooling.

A Basis for AI and Knowledge Governance

Dr. Martens’ knowledge crew are keenly centered on delivering what they’ve promised to their enterprise companions as a part of their transformation undertaking, however have formidable plans for Atlan, as soon as accomplished. Whereas they steadily roll out promised use instances on Atlan and monitor adoption, new applied sciences like Generative AI maintain promise for accelerating asset enrichment, and rising context round their knowledge represents a robust basis for enhancing governance.

“A number of the new use instances we’re seeing are round new options like Generative AI, which is actually thrilling for us. We’re one of many pilot prospects with a hands-on trial of the characteristic, and we are able to see the way it might make our curation course of a lot slicker, then faster. We now have a baseline that our customers can begin working off, then refine,” Karthik shared.

Rounding out Karthik and Lawrence’s future plans for Atlan embody knowledge profiling, classification, and implementing DataOps greatest practices, capabilities they’ve lengthy sought, however solely now can obtain with a platform that may carry them to life.

Classes Realized

Whereas there’s nonetheless work to be achieved modernizing their knowledge expertise, and democratizing entry and context round their knowledge belongings and capabilities with Atlan, Lawrence and Karthik consider there are key issues for his or her peer knowledge leaders contemplating an funding in a contemporary knowledge catalog.

Lawrence: Get Fingers-on

Being hands-on is the largest factor for me. It’s a must to consider a bit of expertise that’s embedded in your stack and your knowledge for those who’re truly going to know if it should work together with your datasets, your tradition, and your group. This was the largest factor once we evaluated Atlan. Then, it’s welcoming these senior stakeholders into the journey earlier, and bringing them nearer to the advantages you plan to ship.”

Lawrence Giordano, Knowledge Governance & Technique

Karthik: Work Agile

Atlan lets you be agile and iterate rapidly, so make use of it that manner. Don’t make your implementations too tight and ‘waterfall-y’ the place you’re attempting to be proper the primary time. Then you definately’re not making use of the chance Atlan gives the place you may strive one thing out rapidly. If it really works, it really works. If it doesn’t it doesn’t. Ship worth, and if it doesn’t work, go away it and transfer to the following factor and deal with that. Be agile. Take a look at and be taught. Strive new issues rapidly.”

Karthik Ramani, International Head of Knowledge Structure

Photograph by Kilian Seiler on Unsplash

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