小程序
传感搜
传感圈

The Next Step in the Evolution of Data Strategists

2023-04-05 12:56:11
关注

Illustration: © IoT For All

As companies progress on their journey toward data maturity, the role of the data strategist becomes ever more important. These new technical business experts have to master increasingly specialized skills in their quest to bridge the gap between strategy and data science. We wrote about The Rise of the Data Strategist in 2019 and 2020. We argued that organizations cannot solely rely on unicorns arising from data professionals to have all technical and business skills on their hands. Data strategists have come to serve a prominent role as the interface between business and technical data teams. This allowed each side to focus on what they do best and not get bogged down by tasks where they have the lack skills and understanding to execute well. Data strategists have become the glue that keeps the machine together and continue to undergo an evolution.

“As companies progress on their journey toward data maturity, the role of the data strategist becomes ever more important.”

-DAIN Studios

An Evolving Role

Now, two years forward and one global pandemic later, there is an even greater need for data strategists, and the debate has developed on several fronts. During the pandemic, we saw organizations trying to accelerate their data transformation, leading to the circumstance that talent in the respective fields is in even higher demand.

At the same time, the academic offering cannot match the speed at which the demand develops. This leaves organizations in a difficult position. Experienced talents are scarce and expensive. Simultaneously, the skills required to execute the data strategy have further developed for all data domains.

“Just as with the recent specialization of data science roles along multiple dimensions, we foresee a similar trend for the role of data strategists. As companies become more mature on their data journey, a mix of multiple strategist profiles will be needed to scale data capabilities,“ said Dirk Hofmann, Co-Founder and CEO of DAIN Studios Germany.

Data Strategist Profiles

We now regularly identify three distinct data strategist profiles:

  1. Those leading data and AI transformations from a strategy perspective.
  2. Those responsible for translating this strategy to the operational level.
  3. Those that work closely with technical teams to deliver data products.

Some are expected to bring about transformational changes, while others focus on contributing with incremental impact. Some must have conceptual thinking and communication strengths, while others need to bring executional excellence.

None are more important than the others, but having a good mix of these different talents is key to data-driven success. Relentless specialization has brought us back full circle to the old problem of the data scientist: it is still possible to find the right people for the job, but it will become ever more difficult.

DAIN Studios

#1: Transformation Leaders

As a transformation leader, the data strategist is responsible for all or part of a larger data transformation, its goals deriving from the company’s overall business strategy. This role interfaces with or directly covers the responsibilities of a chief data & analytics officer (CDAO) or an analytics lead.

They have to define and drive the execution of the data strategy with all its critical enablers. This may include defining key priorities for the data organization, driving the value-driven execution of their project portfolio, promoting and building the data culture, and supporting both upward, lateral, and downward communication.

The focus of this role is to enable the success of the entire data organization.

#2: Operation Leaders

Operation leaders must be ready to bring the data strategy home by translating it into a tangible operating model and helping to establish robust data governance. As the size of data organizations grows larger and larger (including citizen data scientists embedded in business functions), they are responsible for designing an operating environment that is built for the needed scale both in terms of data, tools, and processes.

Daily work ranges from creating logical data assets, and setting up the governance structure, all the way to defining tasks, roles, and responsibilities for the data development and operations processes. They play a crucial role in bringing companies out of pilotitis – a constant state of experimentation with data & AI.

#3: Product Owners

Product owners have to be just that, but with a data angle. Their main focus is the business success of a specific data project or product, always aligned with the company’s strategic objectives.

They manage requirements, communicate between business and technical teams, identify new feature demand, assess feasibility, set priorities for the developers, and promote the product internally as well as externally.

They need to ensure that integrations to all impacted people and processes are in place to generate value for the organization.

DAIN Studios

Further Specialization is Around the Corner

The good news is that the specialization of data strategists does not require the carve-out of yet another corporate function. All three sub-profiles broadly do the same crucial thing – play a vital translational role between the data professionals and the business side.

They all rely on similar skills, if in different concentrations: data and tech-savvy, domain expertise within the company’s business, good communication, corporate strategy thinking, product and project management experience, and operational know-how. C

rucially, this means a data strategist can be trained to embrace a sub-profile, though perhaps no longer be the only data strategist aboard.

Over the next five years, we expect data strategists to add even more skills to their profiles – data management and governance, for example.

The role of the strategist has always been about building bridges and connecting the dots. Between business and IT. Between strategy and execution.

As the field matures and new problems arise, building these bridges requires more specialized skills in every role. There will still be a role for generalist data strategists – and people who can master all skills will likely rise faster than others.

But companies need to brace for specialized data strategists becoming more important – and exactly the right ones are harder to find.

Tweet

Share

Share

Email

  • Big Data
  • Data Analytics

  • Big Data
  • Data Analytics
  • Data Scientist
  • IoT Business Strategy

参考译文
数据战略家进化的下一步
插图:© IoT For All → 随着企业逐步走向数据成熟之路,数据战略家的角色变得愈发重要。这些新兴的技术型商务专家必须掌握越来越专业的技能,以弥合战略与数据科学之间的鸿沟。我们在2019年和2020年撰文讨论了“数据战略家的崛起”。我们指出,企业不能仅仅依赖那些具备全面技术与商业技能的数据专业人才(独角兽)来实现目标。数据战略家已经成为连接业务部门与技术数据团队的重要桥梁。这使得双方都能专注于各自最擅长的领域,避免在自身缺乏技能和理解的任务上耗费精力。数据战略家成为了维系整个系统运转的关键纽带,并且这一角色仍在不断演变。 “随着企业逐步走向数据成熟之路,数据战略家的角色变得愈发重要。” ——DAIN Studios 如今,两年过去了,经历了一次全球疫情,企业对数据战略家的需求更为迫切,相关的讨论也扩展到了多个方面。疫情期间,我们看到许多组织试图加快数据转型步伐,从而导致相关领域人才需求激增。同时,学术界所提供的教育内容却无法跟上需求增长的速度。这使得企业陷入两难境地:有经验的人才稀缺且昂贵;与此同时,执行数据战略所需的技能也在所有数据领域中不断发展。“正如最近在数据科学中多个维度的专业化趋势一样,我们预计数据战略家的角色也将呈现出类似的发展趋势。随着企业数据成熟度的提升,将需要多样化的战略家角色来推动数据能力的规模化扩展。” ——DAIN Studios联合创始人兼德国CEO Dirk Hofmann说道。数据战略家的三种角色 我们如今经常识别出三种不同的数据战略家角色: 1. 负责从战略层面引领数据和人工智能转型的领导者; 2. 负责将战略转化为可操作层面的执行者; 3. 与技术团队密切合作,交付数据产品的人员。 有些人需要推动转型性的变革,而另一些人则专注于逐步优化的成果;有些人需要具备概念性思维和沟通能力,而另一些人则需要具备卓越的执行力。每种角色都同等重要,但拥有一组多样化的技能组合是实现数据驱动成功的关键。 不断加剧的专业化趋势,使我们又回到了数据科学家的老问题:虽然目前我们仍能找到合适的人选,但这种人才将变得越来越难寻。 DAIN Studios 角色一:转型领导者 作为转型领导者,数据战略家负责企业全部或部分的数据转型工作,其目标源于公司整体的商业战略。这个角色与首席数据与分析官(CDAO)或分析主管(Analytics Lead)的职责交集或直接对接。他们必须定义并推动数据战略的执行,包括所有关键的支撑要素。这可能包括:为数据组织设定关键优先事项、推动其项目组合的价值实现、建立和推广数据文化,以及支持上行、横向和下行的沟通。该角色的重点是推动整个数据组织的成功。 角色二:运营领导者 运营领导者需要将数据战略转化为可执行的运营模型,并帮助建立稳健的数据治理机制。随着数据组织规模的不断扩大(包括嵌入在业务部门中的公民数据科学家),他们负责设计一个能支撑数据、工具和流程所需的扩展运营环境。日常工作包括创建逻辑数据资产、建立治理结构,以及定义数据开发与运维流程中的任务、角色与职责。他们在这类角色中扮演着关键作用,帮助公司走出“试点依赖症”——一种持续依赖于数据与人工智能实验的状况。 角色三:产品负责人 产品负责人需要具备产品思维,但专注于数据领域。他们的主要目标是确保特定数据项目或产品的商业成功,并与公司整体战略目标保持一致。他们管理需求、在业务与技术团队之间沟通、识别新功能需求、评估可行性、为开发人员设定优先级,并在内部和外部推广产品。他们需要确保所有相关人员与流程的整合到位,以实现对组织的价值。 DAIN Studios 更深入的专业化即将来临 好消息是,数据战略家的专业化并不意味着企业需要再设立一个新的职能部门。这三个子角色在本质上都做着同一件事——在数据专业人员和业务部门之间扮演关键的翻译角色。他们都依赖于相似的技能,只是在不同的子角色中有所侧重:数据与技术敏锐度、公司业务领域的专业知识、良好的沟通能力、企业战略思维、产品与项目管理经验以及运营知识。 关键在于,这意味着数据战略家可以被培训为特定的子角色,尽管这可能使他们不再成为企业中唯一的战略家。未来五年,我们预计数据战略家将进一步拓展其技能组合,例如数据管理与治理等。 战略家的角色一直在于建立桥梁和连接各个点。在业务与IT之间;在战略与执行之间。随着该领域的不断发展和新问题的出现,建立这些桥梁需要更加专业化的技能。 通用型的数据战略家仍然会有其价值——那些能够掌握全部技能的人将比其他人上升得更快。但企业必须做好准备,因为专业化数据战略家将变得越来越重要,而寻找完全合适的人才也将变得更加困难。 推文 | 分享 | 邮件 大数据 | 数据分析 → 大数据 | 数据分析 | 数据科学家 | 物联网 | 企业战略
您觉得本篇内容如何
评分

评论

您需要登录才可以回复|注册

提交评论

广告
提取码
复制提取码
点击跳转至百度网盘