This chapter highlights the difficulties of translating the benefits of information technology into quantifiable productivity measures. Because information technology is so complex and new, it is hard to develop return and productivity numbers, but researchers should look beyond conventional productivity measurement techniques. According to traditional measures, a high percentage of the productivity created to IT is attributed to its production and sales. However, traditional measures fail to measure some areas IT increases productivity. Unquantifiable benefits such as quality, timeliness, customer-service, flexibility, innovation, customization, etc all add to productivity but aren’t accounted for. Because of this, consumers are generally in a great position to assess the value they gain from technology purchases, so researchers could look to IT purchasers for an estimate of productivity. Hopefully in the future, productivity measures and research methodologies will improve so that returns on investments in IT can be calculated in advance.
One point that really stuck out was that technology has allowed many people in the labor force to work longer hours. Even with my own job that I really care little about, I spend hours at home working on assignments. Instead of the twenty hours I get paid to work, I am actually working 40 or so hours. Therefore, I would think the productivity numbers are much lower than stated.
A final point that this chapter proved to be important is that spending averages illustrate how much organizations spent, not how well they used the technology. Many managers don’t realize this and believe they must spend more to do “better” than the competition. Any productivity gain is highly dependent on how the technology is used; not on simply whether it is present. Investing in technology to keep systems functioning is a better and less risky approach than maintaining technological equality with than the competition. In some industries, risk-taking is acceptable, but when it comes to millions of dollars in untested technologies, investments in IT must be carefully analyzed.
One point that really stuck out was that technology has allowed many people in the labor force to work longer hours. Even with my own job that I really care little about, I spend hours at home working on assignments. Instead of the twenty hours I get paid to work, I am actually working 40 or so hours. Therefore, I would think the productivity numbers are much lower than stated.
A final point that this chapter proved to be important is that spending averages illustrate how much organizations spent, not how well they used the technology. Many managers don’t realize this and believe they must spend more to do “better” than the competition. Any productivity gain is highly dependent on how the technology is used; not on simply whether it is present. Investing in technology to keep systems functioning is a better and less risky approach than maintaining technological equality with than the competition. In some industries, risk-taking is acceptable, but when it comes to millions of dollars in untested technologies, investments in IT must be carefully analyzed.
2 comments:
I agree with you, it seems that as an MBA I'm use to seeing numbers to represent productivity. As technology advances the labor hours worked will increase. Especially in the sense that companies are making careless investments in IT requiring more time and money to straighten out the issues with malfunctions.
It is very difficult for the managers to define that they will stand more advantages than their competition if they spend more money to develop the new technology. Some of them think why they don't spend more money on reforming their organization; however, they have to take a risk to develop a new technology for increasing their productivity. It is such a dilemma for the managers.
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