{"id":10311,"date":"2012-04-18T05:31:07","date_gmt":"2012-04-18T05:31:07","guid":{"rendered":"https:\/\/www.subex.com\/blog\/?p=166"},"modified":"2012-04-18T05:31:07","modified_gmt":"2012-04-18T05:31:07","slug":"data-discrepancies-dont-matter","status":"publish","type":"post","link":"https:\/\/dev.enki.studio\/test\/?p=10311","title":{"rendered":"Data Discrepancies Don’t Matter"},"content":{"rendered":"

Now, referring to the title, you may be thinking: That\u2019s a rather cheeky thing to say given the high direct and indirect costs of errant data incurred by virtually all operators.\u00a0\u00a0 You might cite the significant Opex penalty related to reworking designs and to service activation fallout.\u00a0\u00a0 I get that.\u00a0 What about the millions of USD in stranded Capex most operators have in their networks?\u00a0 Check.\u00a0 My personal favorite comes from Larry English, a leading expert on information quality, who has ranked poor quality information<\/a> as the second biggest threat to mankind after global warming.\u00a0 And here I was worried about a looming global economic collapse!<\/p>\n

My point is actually that the discrepancies themselves<\/em> have no business value.\u00a0\u00a0 They are simply an indicator of things gone bad.\u00a0 The canary in the coal mine.\u00a0\u00a0\u00a0 These \u201cthings\u201d are likely some combination of people, processes and system transactions, of course.\u00a0 Yet many operators make finding and reporting discrepancies the primary focus of their data quality efforts.\u00a0 Let\u2019s face it, anyone with modest Excel skills can bash two data sets together with MATCH and VLOOKUP functions\u00a0 and bask in the glow of everything that doesn\u2019t line up.\u00a0 Sound familiar?<\/p>\n

For context, I am mostly referring to mismatches between the network and how the network is represented in back-office systems like Inventory\u2014but the observations I will share can be applied to other domains.\u00a0 \u00a0Data anomalies, for example, are all too common when attempting to align subscriber orders and billing records in the Revenue Assurance domain.<\/p>\n

Too often, Data Integrity Management (DIM) programs start with gusto and end with a fizzle, placed on a shelf so that shinier (and easier!) objects can be chased.\u00a0 Why is this?\u00a0 Understanding that I am now on the spot to answer my own rhetorical question, let me give it a go.<\/p>\n