The true value of data depends on business insight.Data analysis is one of the most powerful resources an enterprise has. However, if the tools and processes used are not friendly and widely available to the business users who need them, the value of the analysis will be significantly reduced.

數據的真正價值取決于業務洞察力。數據分析是企業擁有的最強大的資源之一。 但是，如果所使用的工具和流程不友好，并且無法廣泛用于需要它們的業務用戶，則分析價值將大大降低。

After all, people can use data to gain insights in areas such as sales, marketing, product development, customer support, and customer experience.

畢竟，人們可以使用數據來獲取銷售，市場營銷，產品開發，客戶支持和客戶體驗等方面的見解。

“Data itself does not mean analysis,” said Bryan Phillips, senior vice president of technology and CIO at bottle and jar manufacturer Alpha Packaging. “At a certain point in time, you must fully understand the problems and opportunities displayed by the data, otherwise, it is just data or beautiful pictures.”

“數據本身并不意味著分析，”瓶罐制造商Alpha Packaging的技術和CIO高級副總裁Bryan Phillips說。 “在某個時間點，您必須充分理解數據顯示的問題和機會，否則，僅僅是數據或精美圖片。”

The following are seven methods used by organizations that may not be able to ensure that their data analysis is friendly to business users.

以下是組織無法使用的七個方法，這些方法可能無法確保其數據分析對業務用戶友好。

Abandon the data strategy or the data strategy is inconsistent with the business

放棄數據策略或數據策略與業務不一致

Jeremy Stierwalt, managing director of consulting firm Protiviti in charge of enterprise data and analytics, said that companies need to formalize their data strategy and align it with organizational goals, indicators, and growth.

咨詢公司Protiviti的常務董事Jeremy Stierwalt負責企業數據和分析，他說公司需要正式制定其數據戰略，并使其與組織目標，指標和增長保持一致。

“An organization operating under a clearly defined strategy will naturally become a data broker, using its data as a key asset,” Stierwalt said. “Decisions about the type and amount of data of an organization, how to collect it, where to store it, how to access and use it, who is responsible, and where to invest in data in the future are important to the organization’s digital strategy and its underlying technology components .”

Stierwalt說：“以明確定義的策略運營的組織自然會將其數據用作關鍵資產，成為數據經紀人。” “關于組織的數據類型和數量，如何收集數據，在哪里存儲，如何訪問和使用數據，由誰負責以及將來在哪里投資數據的決定對于組織的數字戰略至關重要。及其底層技術組件。”

The analysis process is often inconsistent with the company’s strategy, so it is not understood and used, Stierwalt said. “Data strategies enable companies to view their data as structured, comprehensive, and cross-domain value creation assets,” he said.

Stierwalt說，分析過程通常與公司的策略不一致，因此它未被理解和使用。 他說：“數據策略使公司能夠將其數據視為結構化，綜合性和跨域價值創造資產。”

Exclude business users from planning and discussion

將業務用戶排除在計劃和討論之外

The analysis cannot be static, nor can it be imagined out of thin air. Input must be obtained from those who can use the findings and benefit. Data analysts, data scientists, and others in the data management team should also work directly with people in different business units to understand what is important to them and what data shows at a specific point in time.

這種分析不能是靜態的，也不能憑空想象。 必須從可以使用調查結果和收益的人員那里獲取意見。 數據分析師，數據科學家和數據管理團隊中的其他人員也應直接與不同業務部門的人員合作，以了解對他們而言重要的內容以及在特定時間點顯示的數據。

“Let the data owners meet regularly to discuss what they see in the data,” Phillips said. “When you can see data in many fields, a real breakthrough will appear.”

菲利普斯說：“讓數據所有者定期開會討論他們在數據中看到的內容。” “當您在許多領域看到數據時，就會出現真正的突破。”

For example, let sales users know which customers or potential customers are being called, and which orders are generated as a result. Financial users can better understand costs and visualize revenue trends. Operating users can better understand inventory, production, and machine capacity. Marketing users can learn about the latest trends and what activities have played a role.

例如，讓銷售用戶知道正在呼叫哪些客戶或潛在客戶，以及由此生成了哪些訂單。 財務用戶可以更好地了解成本并可視化收入趨勢。 操作用戶可以更好地了解庫存，生產和機器容量。 營銷用戶可以了解最新趨勢以及哪些活動發揮了作用。

“Each group has many questions to answer,” Phillips said. “The real value lies in whether you can use data to find opportunities. For example, by providing data analysis to a group of users from different disciplines, they can all know which products and services are being sold, to whom and where, and how many products are still available. In inventory, which products need to be replenished, what is the sales profit, which items are the most profitable, and how to adjust marketing activities, etc.

菲利普斯說：“每個小組都有很多問題要回答。” “真正的價值在于您是否可以使用數據來尋找機會。 例如，通過向來自不同領域的一組用戶提供數據分析，他們都可以知道哪些產品和服務被出售，向誰出售，向何處出售以及還有多少種產品可用。 在庫存中，需要補充哪些產品，銷售利潤是多少，哪些項目最賺錢以及如何調整營銷活動等。

“Then you will look for hot, profitable, and productive products and target the right customers,” Phillips said. “Or the data may tell us that we need to invest in capital” to increase production. “And involving cross-functional teams will also help ensure that you can solve real problems or see real opportunities.”

菲利普斯說：“然后，您將尋找熱門，有利可圖，生產效率高的產品，并針對合適的客戶。” “或者數據可能告訴我們我們需要投資資本”以增加產量。 “讓跨職能團隊參與進來也將有助于確保您可以解決實際問題或看到實際機會。”

Ignore your analytical audience

忽略您的分析受眾

“When conducting business analysis projects, you need to understand the audience-who they are and what data points they want to see,” said Robin Allen, a business software executive and former chief information officer at tax software provider Vertex.

“在進行業務分析項目時，您需要了解受眾群體-他們是誰，以及他們希望看到哪些數據點，”稅務軟件提供商Vertex的前首席信息官，商業軟件主管Robin Allen說。

“Because several people at different levels in the organization will make decisions based on data, it is necessary to tell an understandable story from their unique perspective based on their roles,” Allen said.

“由于組織中不同級別的幾個人將根據數據做出決策，因此有必要根據自己的角色從獨特的角度講一個易于理解的故事，”艾倫說。

For example, an executive should not only see team-level metrics, but also need to see data that provides a more comprehensive view. “The story told by the data needs to be consistent, but it must also be easily understood by all stakeholders,” Allen said. “To do this, you first need to understand who will look at the data and what insights they will want to gain.”

例如，高管不僅應該查看團隊級別的指標，還需要查看提供更全面視圖的數據。 艾倫說：“數據所講述的故事必須是一致的，但所有利益相關者也必須易于理解。” “為此，您首先需要了解誰將查看數據以及他們希望獲得什么見解。”

Stick to terminology instead of simplifying information

堅持術語而不是簡化信息

One of the best ways to keep business users uninterested in analysis is to start throwing out terms that they cannot understand, or terms that are not relevant to them. Gautam Puranik, chief data officer and head of business strategy and analysis at car retailer CarMax, said this inconsistent communication style is the most common pitfall faced by data analysts when trying to pass value from analysis.

使業務用戶對分析不感興趣的最佳方法之一是開始拋出他們不理解的術語或與他們無關的術語。 汽車零售商CarMax的首席數據官兼業務戰略與分析主管Gautam Puranik表示，這種不一致的溝通方式是數據分析師試圖傳遞分析價值時最常見的陷阱。

This includes presentations full of complexity and terminology, which can make it difficult for users outside the professional field to understand. This also applies to the way the results are presented. For example, Puranik said that analysts usually cite results by detailed figures like 5.238%, rather than simplify it to 5.2% or even 5%.

這包括充滿復雜性和術語的演示，這會使專業領域以外的用戶難以理解。 這也適用于結果顯示的方式。 例如，Puranik表示，分析師通常以詳細數據來引用結果，例如5.238％，而不是將其簡化為5.2％甚至5％。

“Unless decimals are very important from a decision-making perspective, you don’t have to always show the complexity of your work in order to show business value,” Puranik said. “Most of the time should not be spent talking about what you have done and how to do it. It should be spent discussing how it will support the data-driven decisions of the business.”

“除非小數從決策角度來看非常重要，否則不必為了顯示業務價值而總是顯示工作的復雜性，” Puranik說。 “絕大部分時間都不應花在談論自己做了什么以及如何做。 應該花時間討論它如何支持業務的數據驅動決策。”

This can only happen effectively if the data analysis team uses a language that everyone in the meeting room can understand (regardless of department or professional level). “The most effective information is often the simplest,” Puranik said.

僅當數據分析團隊使用會議室中每個人都可以理解的語言(無論部門或專業水平如何)時，這種情況才會有效發生。 “最有效的信息通常是最簡單的，” Puranik說。

Sometimes, using analogies can be helpful. In a recent speech, Puranik’s mission was to support product development by increasing investment in digital marketing. “At the time of the show, I described its relationship with the car,” he said. “Unless you fill the car with fuel, no matter how well the car is built, it will not be of much use to you. In other words, the two are indispensable. This resonates with everyone here, and I also Obtained the necessary approval to move forward.”

有時，使用類比可能會有所幫助。 在最近的一次演講中，Puranik的使命是通過增加對數字營銷的投資來支持產品開發。 他說：“在展覽會上，我描述了它與汽車的關系。” “除非您給汽車加油，否則無論汽車的制造水平如何，它對您都沒有太大用處。 換句話說，兩者是必不可少的。 這引起了大家的共鳴，我也獲得了前進的必要批準。”

Underestimate the power of pictures

低估圖片的力量

When trying to gain quick insights, many people prefer to see pictures or graphical descriptions of concepts. So usually, it is a good method to visualize the data results.

當試圖獲得快速見解時，許多人喜歡看圖片或概念的圖形描述。 因此，通常，這是可視化數據結果的好方法。

“One picture can tell the whole story,” Phillips said. It can be a graph, Venn diagram, or other forms of visualization. For starters, I am still keen to use Microsoft Excel or even the drawing board to draw data. “Then turn to more advanced visualization products to provide deeper or more complex information for the research results, while maintaining its intelligibility.”

菲利普斯說：“一張照片可以講述整個故事。” 它可以是圖形，維恩圖或其他形式的可視化。 首先，我仍然熱衷于使用Microsoft Excel甚至繪圖板來繪制數據。 “然后轉向更高級的可視化產品，以為研究結果提供更深入或更復雜的信息，同時保持其清晰度。”

“To make visualizations friendly, you need to display real, large business issues in a concise and easy-to-understand manner,” Phillips said. “It takes skill, which is why you should start with someone who is good at this, and then let others learn from it.”

Phillips說：“為了使可視化變得友好，您需要以簡潔易懂的方式顯示實際的大型業務問題。” “這需要技巧，這就是為什么您應該從一個擅長此事的人開始，然后讓其他人從中學習的原因。”

Business users may be more interested after seeing the output of data analysis in some form of visualization through data visualization tools, Phillips said. Many people want to be trained on their own or have their team trained so they can create their own visualizations without relying on data analysis or IT staff.

菲利普斯說，在通過數據可視化工具以某種形式的可視化看到數據分析的輸出之后，業務用戶可能會更感興趣。 許多人希望自己接受培訓或訓練他們的團隊，以便他們可以創建自己的可視化而不依賴數據分析或IT人員。

The use of data visualization, especially when it comes to senior management, can actually help drive the future development of these tools. “When a senior executive starts to tell a clear story with graphs and charts, the company will make a more profitable decision, which will bring changes to the company,” Phillips said. “It is now much easier to invest in analytical tools, training, and talent.”

數據可視化的使用，尤其是涉及高級管理人員時，實際上可以幫助推動這些工具的未來發展。 菲利普斯說：“當高級主管開始用圖表講清楚故事時，公司將做出更有利可圖的決定，這將給公司帶來改變。” “現在，在分析工具，培訓和人才上進行投資要容易得多。”

One-sidedness instead of understanding

單面而不是理解

Just as you need to simplify your language, you also need to simplify your presentation materials, such as slides, Puranik said. “The title of any slide should briefly summarize the content of the page,” he said. “Although the phrase “a picture is worth a thousand words” still makes sense, the chart should start with a clear summary of the findings.

正如您需要簡化語言一樣，您還需要簡化演示文稿材料，例如幻燈片，Puranik說。 他說：“任何幻燈片的標題都應簡要概述頁面的內容。” “盡管“一幅圖片值得一千個單詞”一詞仍然有意義，但圖表應以對結果的清晰總結開頭。

The charts should also be kept clean and easy to understand. There should be no more than two charts per slide, and no more than 10 in total. “Remember, you are not writing suspense novels; don’t let your audience guess what is the most important point,” Puranik said.

圖表還應保持清潔且易于理解。 每張幻燈片不應超過兩個圖表，并且總數不得超過10個圖表。 “請記住，您不是在寫懸疑小說； 不要讓聽眾猜測最重要的一點。” Puranik說。

Can’t think like a business

不能像企業一樣思考

In some cases, data analysis professionals may need to break away from the daily tasks that are important to business users. They may need to restructure their thinking in order to better understand the needs of users in terms of data and analysis.

在某些情況下，數據分析專業人員可能需要擺脫對業務用戶重要的日常任務。 他們可能需要重新組織思想，以便更好地了解用戶在數據和分析方面的需求。

“Take yourself as a business leader, not just an analyst,” Puranik said. “Imagine if you own a company and you are using data to make decisions. What will you learn from the work you do?”

“讓自己成為業務領導者，而不僅僅是分析師，” Puranik說。 “想象一下，如果您擁有一家公司，并且您正在使用數據進行決策。 您將從所做的工作中學到什么？”

Identify the recommendations supported by the institute and communicate them clearly to everyone, Puranik said. “Data analysis is a tool, not a result; you should know how to make your findings result-oriented?” he said. “The organizations that most successfully use data analytics to deliver business value are those that believe that data analytics is a core capability, not just an important capability.”

普蘭尼克說，找出研究所支持的建議，并將其清楚地傳達給所有人。 “數據分析是一種工具，而不是結果； 您應該知道如何使結果以結果為導向嗎？” 他說。 “最成功地使用數據分析來提供業務價值的組織是那些相信數據分析是一項核心能力，而不僅僅是一項重要能力的組織。”

When preparing a presentation for a group of business users, first get feedback from the manager and mentor to help the business audience fine-tune the presentation.

在為一組業務用戶準備演示文稿時，首先要獲得經理和指導者的反饋，以幫助業務受眾微調演示文稿。

“When I first graduated from graduate school, I had the opportunity to use predictive models and analysis to drive business impact,” Puranik said. “As you can imagine, I am very excited about the prospect of driving a company to achieve real change.” He spent a few days making a report full of complex diagrams and detailed notes.

“當我剛從研究生院畢業時，我就有機會使用預測模型和分析來推動業務影響，” Puranik說。 “可以想象，我對推動公司實現真正變革的前景感到非常興奮。” 他花了幾天時間編寫了一份包含復雜圖表和詳細注釋的報告。

“After showing to business partners, I am very happy, I am proud of my work and believe that I am doing well,” Puranik said. A few days later, my boss told me that although this is indeed a good job, I need to strengthen my communication skills. The boss said that only about 2% of the people in the room understood what he was talking about, and another 80% did not understand at all.

“向商業伙伴展示之后，我感到非常高興，我為自己的工作感到自豪，并相信我做得很好，” Puranik說。 幾天后，老板告訴我，盡管這確實是一項好工作，但我仍需要加強溝通技巧。 老板說，房間里只有大約2％的人知道他在說什么，另外80％的人根本聽不懂。