Increasingly what companies choose to do, or NOT do, with their data makes a big difference in their operational efficiency, ability to gain market share and overall profitability. It doesnt matter if your business is manufacturing or service, sales or administrative – turning raw data into information works to your advantage, or is ignored at your expense.
Think of the amount of information that flows through your operation on a daily basis transactional information related to customers, sales, and inventory; operational information related to materials, costs, productivity, workload; administrative information related to payroll and accounting, vendor performance or employee benefits. Your ability to capture this information, organize it, understand it and act on it is your data strategy and its a fundamental part of running a successful business in todays marketplace. Knowledge of your customer base can drive marketing. A comparison of the cost and performance of different vendors or suppliers can drive your purchasing or contracting decisions. And of course, the ability to slice and dice the financials and understand the underlying drivers is critical to all decision making.
While the mechanics of capturing your data can be as simple as a tic mark on a note pad, the process of turning it into business intelligence and actionable insight is typically far more complicated and, in my experience, rarely done effectively. Those tic marks can be key-entered into a database; or technology can capture data from on-line systems; or transactional history can be dumped from a processing system; but once youve got all that raw material, now what?
Try getting six different functional departments and their leadership to agree on the header for the six digit alpha-numeric string that represents a customers unique identifier. Or what the valid choices of values should be for the reason an individual called the service department. Youll have three folks on Account Number and two on Client ID and one guy who wont respond. And then youll have five people that will give you causal type descriptions like system problem or account update and one guy who suggests a location (east coast) or product line (mens apparel) be in the same bucket.
This challenge in terms of consistent classification and structuring of the data is where many efforts fail. Even if the company or organization goes through with their program, theyll be hard pressed to get anything from it. Therell be lots of Pareto charts and histograms, no doubt, but unless they stumble across something, there will be nothing that will be truly meaningful on the front-line or to the bottom line. And, in fact, the program may end up doing more harm than good, because the folks that live and breathe the stuff, or that buy your product, will be able to sense that youve missed the point. Just go ask a service rep or billing clerk what they think of their companys operational excellence team or business intelligence team see if they feel like their jobs got easier or if they think theyre more effective as the result of the latest big initiative; or ask the customer, or former customer, of a business thats failing and see if the latest promoti on or give-away addresses the reason they quit buying there.
A misread of the data or bad intelligence, whatever the reason, can result in a loss of market share or send you so far afield that you actually lose efficiency. There is much leverage flowing through your computer systems and across your desks, but its a tricky deal. If you decide to go after it, you better be ready strategically, politically, logically otherwise, better left alone.