A Dozen Smart Metrics, To Go
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Metric: Percentage of Revenue-Related IT Projects
Definition: The percentage of IT projects, begun and completed within the past five years, that were critical components of new products or services that are producing revenue. For example, the IT project that contributed to the creation of a Web storefront that generates sales.
|Example:||# of revenue-related IT projects||x 100|
|# IT projects|
Significance: How IT has contributed to the business' financial success.
Metric: Payoff of IT Dollars
Definition: The ratio of dollars spent on the IT projects that were critical components of new, revenue-producing products or services, to the revenue dollars received to date from those products/services.
|Example:||$ spent on revenue-related IT projects|
|$ generated by parent projects|
Significance: The payoff of discretionary IT funds. Tracks the efficient use of IT dollars; a lower ratio is better
Metric: Knowledge Management Payoff
A. Employee Suggestion Payoff
Definition: The payoff of IT's support of employee suggestions. Divide the annual revenue or cost savings generated by employee suggestions by the number of employee suggestions; divide this number by the annual information technology costs used to support the employee suggestion system (which might be e-mail, an intranet site, the telephone, a database and so forth).
|Example:||$ saved or created by employee suggestions|
|                        # of employees                      |
|$ costs of IT to support employee-suggestion system|
B. Patent Payoff Definition: The payoff of IT's support of company innovation. Determine revenue of products or services that are protected by patents; divide by the number of patents involved. Divide again by the annual cost of the IT employed to serve the company's research and development efforts.
|Example:||$ generated by patented products and services|
|                        # patents                      |
|$ costs of IT to support R&D department|
Significance: The return on IT's assistance in the creating of new knowledge that generates products or services or saves money.
Metric: Technology Core Business Spending
Definition: The amount of technology spending versus the main unit of work, or type of transaction, in a given line of business. In the package-delivery business, for example, divide the number of packages delivered by the amount spent on IT for those divisions and projects related to package delivery; in the auto business, use the number of cars produced, and so forth.
|Example:||units of work|
|$ spent on IT|
Significance: Judging spending against the main way your company's product or services are consumed by its customers shows the effectiveness and efficiency in which IT is being applied. If the percentage is in decline, you're getting more efficient; if it's rising, you're not. Examine why.
Metric: IT Productivity Support Metric.
Definition: The productivity of IT in supporting the main unit of work in a particular line of business. Divide the units of work by the number of employees; divide again by the IT spending (including training) related to that line of business.
|Example:||            units of work            |
|                # of employees               |
|$ IT spending related to units of work|
Significance: This tracks your ability to support overall productive operations of company. A larger number is better: If the output is more packages, with fewer employees and less technology spending, you're headed in right direction.
Metric: IT-Based Product Launch Ratio
Definition: The percentage of product or service launches planned for the upcoming 24 months in which IT is a key component of the offering. (The personalization software in a new targeted marketing campaign on the Web site, for example.)
|Example:||# of IT-based product launches||x 100|
|Total # of product launches|
Significance: Shows the focus of the IT department on ensuring near-term success of the company in the marketplace.
Metric: R&D Investment Ratio
Definition: The impact of R&D investments on the worth of a company. Calculate the percent change in your company's market-to-book ratio for each year for the past five years. Divide by the percent change in dollars invested in R&D efforts.
|Example:     ||A. Calculate Market-to-book ratio for each year|
|                      stock price                      ||= Mx (x=year)|
|      stockholders' net worth (book equity)      |
|# of shares outstanding|
|B. Calculate percent change and divide by percent change in R&D dollars|
|        (M1-M2)/M1        |
|(R&D1-R&D2) / R&D1|
Significance: A 34-year study led by MIT Sloan School of Management professor S.P. Kothari found that market-to-book ratios rose 4.3% with each 1% increase in R&D investment-predicated on sound investments, of course. Compare this number with the ratio of R&D costs to IT's R&D support costs to further manage spending.
Metric: Touchpoint Tracking
Definition: This marketing metric relies on IT to track each point of contact between customers and your company.
Example: Typically, companies establish a promotion that confers a tangible benefit or discount to a customer. The promotion code is delivered via one medium-direct mail, say-and is redeemable through any distribution channel.
Significance: Lets you track and understand consumer research and buying patterns so that you can gear each channel to the specific needs of customers and drive the customer toward purchases. Measuring "touchpoints" lets you see which channels your customer uses (and how many times) before an actual purchase is made, notes NetGenesis chief eBusiness intelligence officer Matt Cutler.
Metric: Freshness Factor
Definition: The frequency with which you should update features or content online to meet customer expectations.
Example: Your competitive intelligence site posts news about 35 market sectors every day. But 85 percent of your customers visit your site once per week. "What is the value to you, of changing your content all the time, if nobody really notices?" queries NetGenesis' Cutler.
Significance: The freshness factor (once per week) shows that the daily postings are inefficient. Either your company should reduce staff and aim for weekly postings, or rethink the marketing plan to increase the freshness factor.
Metric: Time to Resolution
Definition: The speed at which a particular help-desk issue is solved. This metric can be measured against internal or external service level agreements.
Example: A trading partner, promised 99.7% uptime annually, reports that the extranet link is down. The time to fix the outage from the moment of notification is the time to resolution.
Significance: Particularly important in cases where reliability is the primary indicator of customer satisfaction. Time to resolution, along with the frequency of breakdowns, can provide early warnings of an overburdened staff, a troubled system or a possible breach of a service level agreement. Also of particular importance as an "ecosystem metric," whereby a company such as Cisco Systems can assure that a customer will get the same high level of service "end to end"even if a partner company has to provide support and service. For instance, Cisco might require four levels of case resolution in the event of a outage at one of its network gear customers, says Kevin MacRitchie, vice president of worldwide channels technical operations. And if by that time the ecosystem hasn't fixed the problem, notice reaches the desk of chief executive John Chambers.
Metric: Customer Data Management Payoff
Definition: The payoff of data cleansing. Divide the amount saved in improved data quality by the amount spent to clean that data.
Example: Duplicate customer records in a database can hurt earnings through unnecessary mailings. In this case:
|# duplicates in database x mailings/year x cost/mailing|
|cost of data deduplication|
You may also use the number of incorrect customer fields to find the percentage of data that is bad, then calculate the costs of customer interactions that depend on the accuracy of those fields to predict further the cost savings of data cleansing projects.
Significance: Companies often fail to understand the real effects of dirty data, according to customer relationship management software vendor Harte-Hanks. Showing a direct correlation with a tangible expense like shipping helps the business case of data-cleansing projects. A higher ratio is better.
Metric: Early Buying Signal
Definition: The click-through and usage behavior of a visitor to your Web site that corresponds to an increased propensity to make a near-term purchase.
Example: Analyze behavior of customers that have made purchases to infer patterns, then flag visitors that exhibit such patterns. Manny Sodbinow, senior analyst of the Patricia Seybold Group, gives this example: On its Web site, a chip manufacturer provides simulations modeling new types of chips. Engineers that have purchased components have (a) spent increasingly longer amounts of time viewing the simulations and (b) explored them in greater depth. Increases for other visitors in either (a) or (b) indicate a potential sales lead.
Significance: Using a buyer's behavior before purchasing closes down the sales cycle; customer is served; and sale is made with minimum friction.
SOURCES: Gartner Inc., The Alexander Group, Cisco Systems, Patricia Seybold Group, NetGenesis, Harte-Hanks Inc., MIT Sloan School of Management