One Strategic Step For Data, One Important Step For Customer Experience
In my blog earlier this year, Improve Customer Experience with ERP, I reviewed possible causes of thin margins, customer churn, flat revenues and increasing customer complaints.
Two possible causes are:
Lack of accurate and timely information resulting in poor decision making capabilities
Information silos hindering internal data sharing and visibility into key customer information
Innocently tucked into that blog is a silent saboteur of so many initiatives that could provide powerful improvements. Data & Information. Multiple sources for the same type of information and dirty data often undermine the best efforts to have a single-source of the truth for master data, a 360° view of our customers, vendors, partners and/or suppliers.
Nothing sabotages customer experience like getting the wrong information when calling in for support or checking an order online. Or, sometimes the even more frustrating scenario occurs - customers get different answers depending on which channel they go to (calling Customer Support, emailing Technical support, checking my online account, reaching out on social media) and who we interact with. Pause for a moment: Has this happened to you? Do you think this happens to your customers?
Beyond Data Clean Up
The good news is nowadays the necessity of data cleanup is generally understood at least by our IT team members as a key component of a successful ERP implementation. Few look forward to the effort and many underestimate it, but the satisfaction that comes from investing the time and energy to scrub master data ultimately results in a feeling of satisfaction on the big day – Go Live!
But, the bad news is... then we get to Day 2 post go live, then month 2, and then year 2 and our data clean-up investment is quietly eroding as we use the new ERP system. For many, this is happening unknowingly and for others it feels inevitable. It doesn't have to be inevitable; there is a way to protect your investment in data clean up and continue realizing the benefits of consistent and reliable information for customers.
To begin, it's important to understand data cleanup is only taking the minimal steps to prepare the data for a fresh, clean start in the new ERP system.
Data standardization is taking a broader view of the data, but typically only occurs at an application level and determining the rules for the data.
Data management is the overall body of knowledge and framework to manage data.
Data governance is the identification of all stakeholders and development of strategic policies across the organization. These policies are then operationalized as processes, workflows or rule based (system) to manage and protect data across the org. i.e. no discrepancies between operational systems, data warehouses customer facing systems, etc.
Here lies the problem: typically, only the first two, clean up and sometimes standardization if cleanup is problematic, are addressed.
Lack of focus on data management results in data that is not trusted by the stakeholders or users: such as inaccurate inventory levels, vendor or customer master data redundancy or inconsistencies, customer service issues, order delays, incorrect orders, etc. Many employee hours are spent reconciling data in spreadsheets outside the system; these reconciliations never make it back into the system so the spreadsheets become the defacto "operational system" and ultimately become the accepted norm. Then, new hires are trained in this process and the cycle is perpetuated.
Break The Cycle
Data standardization is a critical component within the Data Management framework to standardize and simplify processes and reporting across the business.
The well-thought through Data Governance approach starts with:
Identification of the stakeholders
Determining strategy and alignment with business objectives
Determining who owns the data
Assessing how are changes to data and processes are determined and executed
Determining how the change management process is orchestrated and training is performed
These activities ultimately lead to more granular activities such as what data needs to be standardized, defined and managed locally. A data standardization approach includes:
Definition of standards for data naming and management
Identification of responsibility for standardization decisions and ongoing data management
Identification of sources of key data
Mapping, cleansing, and consolidating legacy data
Without a strategy for data governance, disappointingly you'll be back to the original problem in no time – unreliable data that team members can't rely on and oftentimes leaves us with frustrated customers.
Your ERP implementation plans should include team members to lead the data architecture effort. In addition, your company needs to have plans to manage and govern the data after the ERP implementation project is complete.
Our Business Consulting team can work with you to identify and prioritize ERP-relevant Customer Experience improvement opportunities. We also have expertise in developing strategies for Data Standardization, Management, & Governance.
