通过单一的愿景和投资实现多个战略目标是关键——尤其是在数字投资是精益的，而期望的业务成果是广泛的情况下。

许多首席信息官将面临充满挑战的一年，努力应对转型计划、每周裁员公告以及经济衰退前景带来的越来越大的压力。

虽然数字计划和人才是董事会在2023-2024年的首要战略业务重点，但预计2023年IT支出仅增长2.4%。自2022年以来，科技公司已经解雇了超过25万名员工，93%的首席执行官表示，他们正在为未来12至18个月的美国经济衰退做准备。

给首席信息官们的信息是用更少的钱做更多的事，这意味着首席信息官们必须以不同于过去几年的方式看待数字化转型计划。

在新冠疫情之前的几年里，交付速度是主要目标，首席信息官们希望改善客户体验，并建立实时分析能力。在大流行期间，随着首席信息官转向自动化工作流程和改善员工体验，速度仍然是首要任务。

但2023年正在变得自相矛盾，在过去几年与数百位首席信息官交谈后，我一直建议他们在数字化转型计划中寻求“force multipliers”。

多重数字化转型计划旨在通过单一的愿景和投资实现多个战略目标。例如，改善客户和员工体验的计划，或者其他提供创新和安全增强的组合的计划。

这是一个非多重计划的例子;首席信息官们熟悉的循序渐进的交付。一些IT组织选择将应用程序提升并转移到云端，更快地离开数据中心，希望第二阶段的现代化资金能够到来。但是更快的过渡往往会导致应用程序性能不佳、安全风险更大、成本更高和业务结果更少，迫使IT部门在开始应用程序现代化之前解决这些问题。力量倍增方法将考虑多个目标，并认识到快速的云转换可能会导致更长的、更昂贵的转换。

那么，如今的首席信息官们应该做些什么来推动数字化转型，确定力量乘数，并定义实现更智能、更安全、更快速的业务结果的计划?在接下来的文章中，我将介绍更多关于力乘数的例子，这里有三个可以从适用于大多数cio及其IT组织的例子开始。

敏捷宣言现在已经有22年的历史了，它是在IT部门为瀑布式项目计划而挣扎的时候写的，这些计划经常无法完成，更不用说交付业务成果了。如今，许多首席信息官必须决定使用哪些敏捷工具，以及在哪里创建实践标准。

组建一个Scrum教练团队，他们可能会争论自组织团队需要多少授权，何时评估用户故事，以及当devops团队使用CI/CD自动化部署时，sprint是否仍然相关。

虽然许多组织在敏捷和Scrum方面取得了成功，而且我相信敏捷实验是推动数字化转型的基石，但没有一种万能的方法。组织的规模、项目类型、遵从性需求和文化准备程度只是需要考虑的几个关键变量。

一些被忽视的变量可以帮助推动敏捷实践成为数字化转型的力量倍增器。

1、从日常脱口秀到混合虚拟仪式的过渡。敏捷团队成员的一个常见抱怨是协调会议的数量和花费在会议上的时间。首席信息官们应该考虑采用哪些技术来促进他们的混合工作模式，以取代面对面的会议。Scrum管理员可以使用Slack或Microsoft Teams来代替一些站立式工作，而敏捷团队领导者可以记录虚拟的sprint评审，以便团队成员和利益相关者可以在他们方便的时候进行评审。

2、在开发低代码和无代码体验时应用敏捷。人们仍然认为敏捷主要是一种软件开发实践，然而许多组织在营销和其他部门的工作流程中使用看板和Scrum。首席信息官们希望缩小业务利益相关者和IT之间的文化和实践差距，可以将敏捷方法应用于公民开发(无代码)和低代码应用程序开发，作为统一愿景和实践的桥梁。

首席信息官们的关键是找到他们组织的敏捷工作方式，并将其与it部门以外扩展技术能力的其他努力相一致。

还记得当信息安全被引入到应用程序开发过程的末尾时，几乎没有时间和机会来解决问题吗?Devops团队现在希望改变左安全性，并实现持续测试，从一开始就开发出更创新、更安全、更可靠的功能。

希望建立数据和分析能力的首席信息官也有类似的担忧。

在追求数据驱动型组织的过程中，首席信息官可能会拥有开发机器学习模型的集中数据科学家团队，使用自助商业智能工具的数据分析师，以及仍在运营功能中使用的无数电子表格。然后，通常向风险、遵从性或安全组织报告的是专注于数据安全、隐私和质量的独立数据治理团队。

寻求力量倍增器的首席信息官将通过创建多学科的敏捷数据团队并根据业务目标调整来合并数据运营、数据科学和数据治理计划。

以下是敏捷数据团队可以实现的一些力量倍增差异:

1、需要该仪表板，然后更新数据目录。

2、发布更新后的数据，然后自动进行回归测试。

3、集成一个新的数据源，然后扫描和屏蔽数据以获取个人身份信息。

在没有应用数据治理最佳实践的情况下实现数据可视化或构建ML模型会带来风险，并增加技术和数据债务。

一项研究报告称，到2028年，全球定制软件开发将达到859亿美元，市场年复合增长率为20.3%。

我无法想象IT运营团队在不使用自动化和机器学习功能的情况下，能够在提高应用可靠性、性能和安全性的同时跟上这种增长。AIops平台可以集中可观测数据，关联监控警报，并实现自动化响应，对于应用程序太多而网络运营中心(NOC)响应事件的人员太少的企业来说，它可以成为数字化转型的力量倍增器。

这是我举的三个力量倍增器的例子，每个推动数字化转型的组织都应该考虑。少花钱多办事、推动更快更智能的业务成果、实现更安全创新的压力短期内不会减弱。

3 force multipliers for digital transformation

Accomplishing multiple strategic objectives through a single vision and investment is key — especially when digital investments are lean and desired business outcomes are broad.

Many CIOs will face a challenging year grappling with growing pressure from transformation initiatives, weekly layoff announcements, and the prospect of a recession.

While digital initiatives and talent are the board directors’ top strategic business priorities in 2023-2024, IT spending is forecasted to grow by only 2.4% in 2023. Tech companies have laid off over 250 thousand employees since 2022, and 93% of CEOs report preparing for a US recession over the next 12 to 18 months.

The message to CIOs is to do more with less, and the implication is that CIOs must look at digital transformation initiatives differently than in years past.

Speed of delivery was the primary objective during the years leading into the pandemic, and CIOs looked to improve customer experiences and establish real-time analytics capabilities. During the pandemic, speed remained a priority as CIO shifted to automate workflows and improve employee experiences.

But 2023 is shaping up to be paradoxical, and after speaking to hundreds of CIOs over the past couple of years, I have been advising them to seek force multipliers in their digital transformation initiatives.

What are force-multiplying initiatives?

Force-multiplying digital transformation initiatives aim to accomplish multiple strategic objectives through a single vision and investment. Examples are initiatives to improve both customer and employee experiences or others that deliver a combination of innovation and security enhancements.

Here’s an example of a non-multiplying initiative; a sequential phased delivery familiar to CIOs. Some IT organizations elected to lift and shift apps to the cloud and get out of the data center faster, hoping that a second phase of funding for modernization would come. But the faster transition often caused underperforming apps, greater security risks, higher costs, and fewer business outcomes, forcing IT to address these issues before starting app modernizations. A force-multiplying approach would consider several objectives and recognize that a speedy cloud transition may cause a longer, more expensive transformation.

So what should CIOs look to do today to drive digital transformation, identify force multipliers, and define initiatives that enable smarter, safer, and faster business outcomes? I’ll be covering more examples of force multipliers in upcoming articles, and here are three to start that should apply to most CIOs and their IT organizations.

Agile for hybrid teams optimizing low-code experiences

The agile manifesto is now 22 years old and was written when IT departments struggled with waterfall project plans that often failed to complete, let alone deliver business outcomes. Today, many CIOs must determine which agile tools to use and where to create practice standards.

Assemble a team of Scrum coaches, and they’re likely to debate how much empowerment self-organizing teams require, when to estimate user stories, and whether sprints remain relevant when devops teams are automating deployments with CI/CD.

While many organizations are successful with agile and Scrum, and I believe agile experimentation is the cornerstone of driving digital transformation, there isn’t a one-size-fits-all approach. The organization’s size, types of programs, compliance requirements, and cultural readiness are just a few of the key variables requiring consideration.

Several overlooked variables can help propel agile practices as digital transformation force multipliers

1、Transition from daily standups to hybrid virtual ceremonies. One of the common complaints agile team members voice is the number of coordination meetings and time spent in them. CIOs should consider technologies that promote their hybrid working models to replace in-person meetings. Scrum masters can use Slack or Microsoft Teams to replace some standups, while agile team leaders can record virtual sprint reviews so teammates and stakeholders can review them at times convenient to them.

2、Apply agile when developing low-code and no-code experiences. People still associate agile as primarily a software development practice, yet many organizations use Kanban and Scrum in marketing and other department workflows. CIOs looking to close cultural and practice gaps between business stakeholders and IT can apply agile methodologies to citizen development (no-code) and low-code app development as a bridge that unifies vision and practices.

The key for CIOs is finding their organization’s agile way of working and aligning it with other efforts that expand technology capabilities beyond the IT department.

Align data science and data governance programs

Remember when infosec was brought in at the end of the application development process and had little time and opportunity to address issues? Devops teams now look to shift left security and implement continuous testing to develop more innovative, secure, and reliable features from the start.

There are similar concerns for CIOs looking to build data and analytics capabilities.

In pursuing a data-driven organization, CIOs will likely have centralized data scientist teams developing machine learning models, data analysts using self-service business intelligence tools, and a myriad of spreadsheets still used in operating functions. Then, often reporting to risk, compliance, or security organizations, are separate data governance teams focused on data security, privacy, and quality.

CIOs seeking a force multiplier will merge dataops, data science, and data governance initiatives by creating multidisciplinary agile data teams and aligning on business objectives.

Here are some force-multiplying differences achievable by agile data teams:

1、Want that dashboard, then update the data catalog.

2、Release an updated data viz, then automate a regression test.

3、Integrate a new data source, then scan and mask the data for personally identifiable information.

Achieving the data visualization or building an ML model without applying data governance best practices introduces risks and grows technical and data debt.

AIops that improves performance on more apps

One study reports that global custom software development will reach $85.9 billion by 2028, rising at a market growth of 20.3% CAGR.

I can’t imagine IT operations teams will keep up with this growth while increasing app reliability, performance, and security without using automation and machine learning capabilities. AIops platforms that centralize observability data, correlate monitoring alerts, and enable automated response can be a digital transformation force multiplier for enterprises with too many apps and too few people in the network operations center (NOC) responding to incidents.

These are three of my example force multipliers that every organization driving digital transformation should consider. The pressure to do more with less, drive faster and smarter business outcomes, and enable safer innovations won’t let up anytime soon.