我曾经坚信“用数字说话”,认为数据是客观、公正的评价标准。然而,最近的经历彻底颠覆了我的认知。在为一家高度数字化的银行提供咨询服务时,我发现其高度自动化的系统反而成了一个“黑箱”,问题难以追踪,员工对业务流程也缺乏了解。这让我开始质疑过度量化和对系统的盲目崇拜。
数字并非全部,人的判断力不可或缺
单纯依靠数字评价工作产出,忽略了诸多无法量化的因素,这是一种懒惰且片面的做法。领导的评分也可能掺杂个人喜好,缺乏客观性。“用数字说话”并非万能良方,管理者更应该关注员工的价值观、不足之处以及改进方向,而不是简单地依赖数字指标。
小红书和淘宝的案例更是佐证了这一点。淘宝的成交额远超小红书,但仅凭此就断定淘宝更值得投入资源,无疑是目光短浅的。小红书的种草功能对淘宝的最终成交额贡献巨大,但这种影响难以量化,却不容忽视。
因此,在汇报工作时,我们需要将无法量化的因素融入其中,例如与领导的关系质量、工作的趣味性和挑战性等。这些因素虽然难以量化,却深刻影响着工作体验和效率。
系统化管理的利与弊:警惕系统崇拜
系统化管理固然有助于解决问题,但过度依赖系统,反而可能导致人们对系统内部运作缺乏了解。一些看似“智能”的系统,背后往往是人工操作,而我们对系统的盲目崇拜,掩盖了其不可控性和落后性。
在招聘工作中,单纯依靠数字指标(例如简历数量、面试通过率)来评价招聘质量,也是一种误区。候选人的匹配度、潜在价值等主观因素同样至关重要,却难以量化。招聘漏斗模型虽然有效,但过分追求数量,可能会降低招聘的精准性和效率。
对人的主观判断的依赖性降低,导致人们更倾向于依赖数字,认为数字更客观、更公平。这种对个人判断的不信任感,反过来加剧了对数字指标的依赖,即使这些数字可能并不完全准确。价值观考核的难以量化,也容易导致主观偏见,进一步强化了人们对更容易量化指标的依赖。
在猎头行业,我深刻体会到,人对行业的洞察力远比公开渠道获得的信息更有价值,但这种洞察力却难以量化。量化部分固然重要,但我们不能忽视无法量化的部分。过分追求量化,只会导致许多宝贵的、无法量化的信息被忽视。
工作性价比计算器就是一个典型的例子,它忽略了工作趣味性、挑战性等无法量化的因素,而这些因素却对工作体验至关重要。
量化指标的陷阱:矛盾、冲突与内卷
过分依赖量化指标,还会导致部门之间产生矛盾和冲突,使整个系统陷入困境。例如,裁员行为虽然可以量化,但其潜在影响(例如员工士气下降、与客户关系恶化)却难以量化,可能导致部门间矛盾激化。
不同部门对同一数据的解读和归因也可能大相径庭,导致部门间冲突不断。不同团队之间为了追求量化指标,可能会陷入无休止的内卷,最终损害企业的长远发展。
设定过高的业绩目标,并将其与提成挂钩,也可能导致员工收入降低,得不偿失。因此,员工需要理解数据指标背后的逻辑和关联性,并积极与相关部门沟通协调。
超越数据:洞察未来,讲好故事
数据只能衡量过去,无法预测未来。我们需要依靠人的判断力,结合实际情况和故事进行分析,将无法量化的因素融入到汇报中,才能做出更明智的决策。
绩效考核中,我们需要兼顾可量化和不可量化因素,并及时发现考核不合理之处。数据可以辅助管理,但不能代替管理者的判断和思考。数字化转型是为了解决老板的焦虑,但不能盲目追求数字化,而忽略了员工的实际需求和公司文化。
总而言之,我们需要理性看待数据,避免过度依赖数字,而忽略了人的主观判断和无法量化的因素。只有将量化与质变相结合,才能实现真正的有效管理,避免陷入数字的迷思。
Over-reliance on data and systems can create a 'black box' effect where processes are automated to the point that employees no longer understand the underlying logic or mechanisms. For example, in a highly digitized bank, accounting entries are automatically generated, but when issues arise, no one knows how to trace or fix them because the system operates without transparency. This disconnect can lead to inefficiencies and a loss of critical business insights.
Prioritizing quantifiable metrics can lead to the neglect of important but unquantifiable factors, such as employee relationships, creativity, and long-term strategic value. For instance, in HR, while metrics like recruitment efficiency can be measured, the quality of hires and their fit within the team often rely on subjective judgment. Overemphasis on numbers can result in decisions that look good on paper but fail to address deeper organizational needs.
Organizations favor data-driven decisions because data provides a sense of objectivity and fairness, even if it is not always accurate or comprehensive. Metrics like GDP or sales figures offer a quick, seemingly objective way to assess performance. However, this reliance can mask underlying complexities and lead to decisions that prioritize short-term gains over long-term value, as seen in cases where companies focus on easily measurable outcomes like ad clicks rather than deeper customer engagement.
The obsession with data and systems can lead to unfair performance evaluations, as managers may rely on easily quantifiable metrics while ignoring subjective but critical factors like teamwork, creativity, and adaptability. For example, in some organizations, low performance ratings are disproportionately assigned to employees who are about to leave, regardless of their actual contributions. This creates a skewed and demotivating work environment.
Blindly adopting digital transformation strategies without considering organizational culture can lead to inefficiencies and employee frustration. For example, small companies may implement complex systems like enterprise software that are better suited for large corporations, resulting in unnecessary complexity and reduced productivity. Additionally, if leadership is not comfortable with new tools, employees may end up juggling multiple platforms, leading to confusion and wasted effort.
Storytelling with data is critical because it helps bridge the gap between raw numbers and meaningful insights. While data provides the foundation, storytelling contextualizes it, making it easier for stakeholders to understand the implications and take action. For example, in business presentations, using data to tell a compelling story about market trends or customer behavior can drive more impactful decisions than simply presenting spreadsheets.
Reliance on data can stifle creativity and innovation by prioritizing measurable outcomes over experimental or unproven ideas. For instance, in content creation, platforms may focus on metrics like views and clicks, leading to formulaic content that lacks originality. This focus on data-driven success can discourage risk-taking and limit opportunities for groundbreaking ideas that may not have immediate quantifiable results.
没有人能够真正逃离数字,上学有排名,工作有指标。
我们试图做到一个又一个数字、被数字评价和归类、试图在数字中找到自我的成就感与满足感。但是今天我们想问另一个问题:数字真的就是全部了吗?我们赖以生存的数字,又会让我们失去什么?
「时间轴」
02:07 系统反而让员工不了解自己的业务
11:57 迷信数字的背后是不信任人
16:43 人的洞察和判断,比数据更值钱
19:28 有些重要的东西,无法用数字量化
27:15 职场核心沟通技能:用数据讲故事
36:51 数据是在衡量过去
47:37 互联网HR的绩效实操case
54:39 数字化转型很多时候不解决问题,但可以回应老板的焦虑
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