Big data pain and pass

After the "love", people began to rationally examine the sensibility sought before big data. It's like a high-sports car grand prix, first prepare the car, familiar with the track, and then adjust the attitude, timely sprint to get a good ranking. Big data also has a brewing period and a preparation period. The result is demand and desire. There are pain points and difficulties in every period, and the result of good will is the best.

Big data has great energy. It is significant for economic growth - "In the United States, big data analysis has the potential to increase GDP by $325 billion only in retail and manufacturing." This is an exciting estimate given by analysts. While the global economic growth is slowing down and even becoming exhausted without a new growth point, people are turning their hopes on big data that is expected to shoulder this heavy responsibility.

Pragmatic and savvy entrepreneurs remain rational and clear-headed while being surrounded by enthusiasm and passion for big data. They need far more than a hype-like description of the prospects for big data. They need to be convinced that they will not be transformed into data-driven enterprises as soon as possible. They will be guided how big data should be applied to their own companies, and they will be able to show big data. The real benefits of coming.

The reality that cannot be avoided is that big data also has pain points. These pains have become an annoying stumbling block. The so-called "general rules are not painful." These pains all have "good doctors" that give a good way of communicating. Big data efficiency has become the most direct and most powerful argument. By dissecting every implementation experience, you will find that the answers your entrepreneurs need are included. In reason, in emotion, they can no longer resist the temptation of big data.

There are guidelines for investing in big data

In an interview with Fortune, Phil McCarvey, chief brand officer of Starwood Hotels International, described the big data: “In our oldest hotel, there is a passage between the general manager's office and the front desk. Through this In the channel, the general manager can see every new guest and then meet them like an old friend. I think big data is this passage of the 21st century. It makes us understand the guests more and provide them with what they really need. The service."

Matt Asay, vice president of MongoDB Inc., one of the most well-known companies in the field of NoSQL database technology, once exclaimed: "The attraction of big data is like gravitation, so strong that people can't escape, and people are tempted to push for relevance. project."

More than one CIO of a large company publicly stated that big data has saved the company a lot of money - 1% efficiency gains have brought down millions of dollars in expenditures, and the effective mapping of sales and customer databases has brought 10% The sales volume growth... These mouth-watering data are consistent with the Bain&Company survey: Companies using big data analytics are far ahead of their competitors—the likelihood that the financial position within the industry is within the top 25% will increase. Times; four times faster to make decisions; three times more effective; and twice as likely to use data to support decisions.

Ever since, companies have made a difference. According to a Gartner survey, 64% of companies surveyed said they are deploying or planning to deploy big data projects. However, what is embarrassing is that 56% of respondents are confused about how to get value from big data, and 23% of respondents have doubts about the exact definition of big data.

“Big data fever doesn’t mean that any business is eager to jump into the big data wave.” According to Jamal Khawaja, director of Infinitous Global Services, adoption of big data is a long-term and multidisciplinary integration effort. The platform, services, and internal investment capabilities are no small tests.

Based on his many years of corporate research experience, he gives four criteria for judging whether an enterprise is at the best moment for big data: There has been a certain amount of accumulation in business intelligence (BI), and the amount of data in the hands has reached a certain scale. Cultural recognition, with ample talent pool.

“Only by properly processing existing data can we find a solution to the problem from discrete data streams. There are two criteria for measuring whether or not data is handled properly: one is to bring the professional skills required for higher-level analysis, and the other is to Achieved certain financial benefits.” Jamal Khawaja said in detail, “The related data in historical data sets can bring many opportunities, such as excluding operational anomalies. Before investing in big data, we must clearly realize that big data investment and other The investment is different, it is not driven by the existing and obvious problems, you can not get the standard ROI or net present value model of big data investment, and the expected return is not obvious. It can be said that big data Investment is essentially opportunistic. Therefore, it is necessary to have a corresponding corporate culture to accept this. The importance of professionals such as data scientists need not be said, and the method for extracting value from data is dazzling."

If we look at it and feel confident that we can practice big data projects, we must not take it lightly. Myles Suer, a senior manager from Informatica, pointed out that many big data projects are actually just "before-and-after" versions of existing BI projects. Applicants are only doing so to ensure funds are in place or projects are approved. This means that The project argument must be rigorous.

“In addition, we need to beware of past mistakes made in IT.” Myles Suer said that IT has gone through three major stages of development: local systems, ERP, BI/big data, “ERP should solve all local solutions The problem, but it only provides transaction information.We must avoid BI/big data to repeat the mistakes.Otherwise, CIOs are likely to hear CEO/CFO complaints - the accumulated data did not allow the company to make more money. Big Data connects the trading system, the BI, and the planning system as a viable option, which hopefully will bring more profits to the company."

You will climb first and you will walk again before you can run. The same can not be impatient for big data, can not be eager to achieve - the implementation of big data is like participating in a high-sports car grand prix, you must first prepare the car, get acquainted with the track, adjust the mentality, timely sprint, and finally get a good ranking.

Non-negligible risks

“If you adopt big data methods and technologies in a hurry, some companies may underestimate or completely ignore the risks of some big data. Implementing big data is equivalent to placing a big bet on the company. Whenever a business must not Take it lightly. Understand these risks and plan to deal with these risks is crucial for companies that want to benefit as much as possible from big data.” Rick Delgado, a renowned IT management consultant, sounded the alarm.

In his view, the biggest risk in the implementation of big data is security. The more data the system processes, the greater the likelihood of inevitable data loss. “The recent data leakage incidents of Target and Coca-Cola are enough to show that the data loss accident is immediate and the cost is huge.” Rick Delgado stressed that the emphasis on IT security is a deficiency for many companies. In the era of big data will lead to much more terrible results than before.

Concerns about privacy are also an irreversible hurdle. It is both a legal issue and a commercial issue. The debate about data ownership is endless, especially when it comes to consumers and businesses, or companies and big data vendors. The use of user-related data they collect may result in some violations of the law. The misuse of data may lead to litigation, fines, and even further serious regulatory consequences such as industry supervision. A typical example is the NHS hospital in the United Kingdom accused the defendant to go to court for selling patient information to the insurance company. In addition, although some violations of privacy rights may be legally legal, the company still bears the risk of a major blow to its reputation.

Another risk not to be overlooked in using big data is that it can cause a business to lose agility. This may sound strange, because big data is intended to help companies respond faster to real-time data, but don't forget that different data sets of big data will always be placed on different platforms using different software programs. in. Big data requires that data be managed, organized, and stored in an extremely efficient manner so that it can be properly analyzed and then acted upon. If everything is unorganized and there is no reasonable management of all the input data, it is very easy for companies to hurry when they need to act quickly. The unsurprising result, then, is that in the “time is money” market competition, companies have lost the opportunity to preemptively.

In addition to poor data management, the risk of misinterpreting data is also worth noting. With big data, companies sometimes take it for granted that it can do almost anything, but it's not that simple. Big data can show what's going on, but it can't provide an explanation of why things happened. To get these explanations, you need correct analysis and judgment, but sometimes it is difficult to rely on the data alone. For example, data shows that at certain times of the year, sales volume has blown out, but why blowouts must be interpreted by specialized data experts, otherwise the conclusions may be wrong, resulting in invalid actions. In the long run, distorted data will eventually waste a lot of corporate money.

How can companies reduce these risks associated with big data? Rick Delgado gave a response: employ professionals who are good at managing large data, being good at analysis, and being able to get the right conclusions. Having the right people in key positions will help companies use data effectively and reduce the chance of errors when they need to interpret data and use the latest big data tools. Companies should also conduct self-assessments on a regular basis to ensure compliance with current privacy protection and business regulations. Equally important is that companies must be honest and transparent, let customers know how companies use their data, which will help to get customers' trust and loyalty.

In the face of potential risks, Rick Delgado remains cautiously optimistic: “There is no doubt that big data can provide tremendous benefits. But companies should adopt a realistic approach to risk. No new technology or practice is risk-free. Just keep this in mind and you will be ready to meet the challenge."

Harmony between CXOs

Gartner said that by 2015, there will be a quarter of large companies setting up the position of chief data officer (CDO). And according to cloudpro. According to com's report, there are currently 100 CDOs in place, of which 65% are in the United States and 20% in the United Kingdom.

Gartner describes CDO's authority as follows: "They are responsible for the core processes related to data, managing data, and coordinating the use of data. This is similar to the CFO. The CFO controls the financial processes and allows the capital to flow within the company."

Take the example of the Bank of America, which took an active step before the trend. Its CDO John Bogetta took office as early as December 2011. This point of time is earlier than big data becoming a hot topic for CIO openings. His main responsibilities are data management and quality control.

CDOs have mushroomed. Did they seize the exclusive territory that originally belonged to IT and CIOs? CXOs such as Chief Digital Officer (CDO), Chief Technology Officer (CTO) and Chief Marketing Officer (CMO) need to make adjustments to adapt to the era of big data.

After a lot of interviews, Harvard Business Week has found an embarrassing fact: CXOs are not tightly centered around the core of big data, especially the CMOs and CIOs are out of step to seek to benefit from Big Data. Common problems in the company.

Indeed, there are differences in the way of thinking of various CXOs, and the pursuit of performance goals is also varied. But don't forget that studies have shown that data-driven companies are "5 percent more productive and 6 percent more profitable than non-data-driven companies." For a company, productivity and profitability are the highest goals. Therefore, CXOs must be consistent with the outside world, soberly aware that big data is an excellent weapon that can effectively help decision-makers select, analyze, and predict when the market needs innovation.

"To date, the role of technology in the operation of enterprises has undergone tremendous changes. These changes require CXOs to work together," said John Dodge, a well-known IT media person.

Matt Ariker, chief operating officer of the McKinsey Consumer Market Analysis Center, gave a convincing suggestion for improving the CXO's respective political situation: The company must have an effective decision-making framework and the CXO leadership team must support each other. This affects every step in the conversion of data into value, including the development of strategies, selection of usage scenarios, budgeting, and deployment. Defining requirements is particularly critical. This requires the CMO to identify business goals, usage scenarios, and specific requirements related to data and analysis. The CIO needs to provide feasibility and cost analysis based on usage scenarios. The CTO provides strong technical support and the CFO is ready to “ wallet". All these need to be weighed and selected in terms of cost, time and priority. Then form a suitable diversified team to make the process transparent and follow up on a regular basis. Effective communication is indispensable. Even when necessary, “translation” is needed to allow CXO to “understand” each other's words. For example, CMOs need to communicate with people who understand customers and businesses and have geek thinking. CIOs need to communicate with technical personnel who have a deep understanding of marketing activities and business. Then, the leadership team should be gradual and can start some reference work to test team collaboration capabilities and new processes, and then promote.

The effective use of big data has become a watershed in many industries to distinguish between winners and losers, but companies have no shortcuts to take. No single CXO can enjoy the success of big data alone or bear the failure of big data alone.