Tag: OKR

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Customer Master Data and Digital Transformation

Quartz LCD digital 'transformer' child's wristwatch (wrist-watch; Quartz LCD digital)

Digital Transformation is very popular as a goal currently. Exactly what it is though, can be confusing and ambiguous. Digital transformation is a catch-all term that squarely lands in the world of sales and marketing buzzword bingo.

The scope of issues, functions, technologies and efforts around digital transformation are vague, and the term seems to mean something different for every organization. One thing that is pervasive though, is the message. A message that embraces the idea that your business should be digitising as much of its data and activities as practically possible.

For customer master data management there is a high interdependency between a digital transformation strategy and customer data management.

The ability to have a solid basis for the customer master is a critical part of any digital transformation strategy.

How you execute on customer master data management as a part of digital transformation is the critical piece of the puzzle that holds the potential for maximal organizational value.

What is digital transformation exactly?

As mentioned, the term “digital transformation” can mean anything and everything depending on who is pronouncing it and who the audience is. It can encompass tools, technology, business processes, customer experience, machine learning, and artificial intelligence, and accompany every other contemporary buzzword that marketers and promoters can come up with.

The ‘semi-official’ definitions from industry analysts and technology vendors include digitizing manual processes and records, modernizing the IT function or moving to cloud technologies, putting services online and accessible outside of the corporate network; developing new business models and taking a “digital-first” approach. This last piece is important, because when we consider it in relation to the creation and maintenance of customer records and record-keeping that may mean creating new business processes and overhauling or devising new customer experiences and ways for your business to engage with customers.

Digital transformations tend to be expensive, broad swathe and highly strategic with the impact expected to be felt in many areas of the business. Bricks and mortar businesses moving a fair portion of their business strategy to online, for example, might be considered a critical element of a digital transformation strategy,

The end-to-end customer experience may see transformations in every aspect of the customer engagement model from campaign construction, through lead accumulation, lead nurture, identify, contact, needs assessment, qualification, opportunity establishment, proposal, quote, order, bill, fulfil, collect and support. A great deal of technology-based solutions may be involved along the way and many systems. These may include CDPs, CRMs, ERPs, back-office technologies, aggregation services and a host of configurable technologies that support business processes. The goal, in the end, is to reduce the amount of friction associated with contracting with customers. The challenge is the complexity of the whole end-to-end process and the level of effort and solutions required to achieve the end goal.

Some digital transformation initiatives will attempt to boil the ocean in the pursuit of a friction-free engagement model, others will be more incremental, progressive and pragmatic. One trait that any customer-related digital transformation initiative will fail or succeed in, is the quality of the customer master data management process. Though a high degree of data curation with quality at the customer master level, cannot guarantee success, it is almost certainly true that light curation accompanied by potentially low-quality data will almost certainly lead to failure to meet the goals of the program.

Customer master data management is foundational and often not directly tied to an ROI. Identifying intermediate wins from improved data quality and more comprehensively or flexible data curation can be evaluated in the context of OKRs. These, in turn, can be leading indicators that can feed into desired outcomes which in turn will fuel ROI measures.

To learn about the Pretectum approach to Customer Master Data Management and work out whether you can take advantage, why not contact us?

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What’s your master data management style?

colorful cubes and puzzle piece

In deciding what to do next, in terms of customer master data management, it is important to understand what your organization does with its master data and how it manages it.

I say, do next, because there has to be an implicit assumption that whatever you’re doing today, there is a good chance that you want to do what you do even better!

Establishing a good understanding requires an assessment of the “maturity” of the master data management function in your organization.

It’s suggested that using a Capability Maturity Model (CMM) is a good way of determining the degree of formality and optimization of existing operational processes. This includes identifying ad hoc practices and formally defined steps in the end-to-end process.

The end result may also be Key Performance Indicators (KPIs), managed result metrics (OKR measures) and active evolutionary optimization of the data mastery practice over time.

The CMM is based on a development model created in the 1980s for the U.S. Department of Defense which funded a study of data collected from organizations that contracted with the DoD.

The MDM maturity model, a derivation of the CMM, is a means of assessing the whole process of master data management including the data point of view and also focusing on the whole operational process.

No need to boil the ocean

Investopedia Definition

A common misconception is that master information consolidation is always “the best approach to master data management”. The reality is that different parts of the business have different needs and expectations around master data and around the customer master in particular. The idea that you need to “boil” the proverbial ocean of data that you have, to reduce your data to the essential most valuable nuggets that your business requires, assumes that you know the requirements of the business.

The stark reality is that even if you do manage to converge on a single source of truth for the whole organization, the way the different stakeholders curate, manage, maintain, use and disseminate the customer master, may well be wholly incompatible with the governance choices that you make.

Image Credit : Sketchbubble.com

No one will deny the fact that operational inefficiency, unreliable operations reporting, customer dissatisfaction and regulatory compliance issues often have roots in inadequate data management.

Customer MDM Maturity Model

Further, the implementation of advanced analytics and reporting and an increased level of interest in the “digital everything” is forcing organizations to rework their data management model. Taking stock, then of what you do today is important in deciding what decisions you should take strategically and tactically to improve data management operations.

One opportunity lies in the Gartner MDM maturity model. This proprietary model is positioned to give data and analytics leaders a framework to measure and assess their organization’s MDM capabilities, create an MDM vision, and establish a roadmap to reach it.

MDM implementation styles PPT slide 2
Image Credit : Sketchbubble.com

Master Data can be stored in several ways and implemented in a range of styles. It is considered that there are at least four popular master data management (MDM) implementation styles, and their different characteristics suit different organizational needs. Gartner popularises these four and again, it is important to understand, in the evaluation of your own organization’s data mastery setup, which of these is most aligned with the way your business operates.

Consolidation
Support for business intelligence (BI) or data warehousing (DW) initiatives. Often considered as a downstream MDM style. MDM is applied downstream of the operating systems where master data is originally created.

Registry
An index to master data that is authored in a distributed fashion and remains fragmented across distributed systems.

Coexistence
Master data authoring is distributed, but a “golden copy” is maintained centrally in a hub. The central system publishes the golden copy of master data to subscribing systems.

Centralized
When master data is authored, stored, and accessed from one or more MDM hubs, either in a workflow or transaction-based use cases.

Pretectum Approaches to Customer MDM
Pretectum supports the four main approaches to Customer MDM – CoExistent, Centralized, Consolidated and registry

In your self-assessment consider how mature your master data management is and which of these styles is most aligned with the way you work.

When you consider a solution like the Pretectum CMDM, we’re offering support for all stages of the maturity model and all styles of MDM deployment for the customer master. How you choose to do it is at your discretion.

We have best practices but in the end, the best practice may not be the best practice for your business!

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Customer Service driven by data

close up of human hand

Can you think of a recent customer service or support event that stands out in your mind as having been stellar or outstanding?

Chances are you have a better memory of the last negative experience. That’s a natural outcome. As Alina Tugend describes in an NYTimes piece in 2012. Tugend quoted Florida State University, social psychology Professor Roy F. Baumeister, author of a journal article he co-authored in 2001. Baumeister wrote “Bad Is Stronger Than Good,” “Research over and over again shows this is a basic and wide-ranging principle of psychology… It’s in human nature, and there are even signs of it in animals”.

Your, remembering of the bad over the good turns out to be something simply human. Negative emotions, poor parent experiences, and negative feedback have more impact than good. Further, bad impressions and bad stereotypes are quicker to form and more resistant to disconfirmation than good ones.

That’s not much of a consolation to a business that sells goods and services. That a dud product or poor experience ultimately could ruin a lifelong experience for customers is not very encouraging. However, all is not lost.

Though you are more likely to remember the negative experiences, the reality is that your business can recover from these kinds of negatives, but the approach that you use depends heavily on customer data and knowledge and insights about your customers.

Praise Is Fleeting, but Brickbats We Recall

ALINA TUGEND – NY Times 23 March 2012

You might have heard or read about the concept of Net Promoter Scoring or NPS. At its heart, NPS, as a measure, is used to calculate the status of sentiment within a customer in relation to a product, service, brand, or experience. When looked at in aggregate it is the percentage of customers who are effectively pro or positively disposed toward that thing as opposed to against, or negatively disposed detractors of that good, service, brand, or experience.

For organizations, NPS is actually calculated based on one or more surveys of customers where they “How likely would you recommend X to a friend, colleague, or family member?”

The responses are often out of 10 with 0 = “not at all likely,” 5 = “neutral,” and 10 = “extremely likely.”

A net promoter is someone who scores 9-10 and a detractor is 0-6 with 7 and 8 falling neutral. This is a sharp contrast to the mean, median, and mode scores often used in ratings where you might think that anything above 5 suggests support or enthusiasm for your offering.

We know, from what we see in social media, on review sites, and the like, that people are quick to share negative experiences and not necessarily as balanced on the positive side. Actually, providing genuine positive feedback takes a lot of effort and negative feedback may be fueled by disappointment or frustration, or feelings of betrayal.

If you’re gathering NPS, where does that information land? It is probably in your survey system, probably in your statistics, but do you bring it all the way back to your customer master? Perhaps you want to.

Your next question might be, well “why on earth would I want to store something that is potentially negative or only valid for a particular point in time“? It’s a good question and one that the following ideas on engagement might answer.

Feedback becomes insights

If you’re a product or service company, you should look at how your business harvests customer sentiment to drive the enhancement of your products and services. If it doesn’t then perhaps there is an opportunity right there. If you know who your fans are, then they’re great candidates for providing you with an understanding of what matters to them. Further, the detractors can fuel an understanding of the deficiencies or what’s missing in what you provide.

If you don’t have any of that tied to your customer master then, you’re effectively blind and building and refining based on unknown customers or potentially only those who shout the loudest.

If you recognize and acknowledge that surveys are a good way to get a sense of customer sentiment then it makes sense to go to the next step of attaching that sentiment to the customer master itself. This also can help guide service and support personnel in understanding that in some instances a particular customer has already indicated some sort of unhappiness and may need some specific special handling, Now that’s what we call customized or personalized customer interaction!

Using Pretectum APIs to manage and access the customer master, you can hook the survey results on a per-response basis right back into the customer master and surface elements like the date the last survey was undertaken the NPS, and any other data that you feel might be important. Ultimately the choice of what you store when you store it and the frequency with which you store it, is entirely up to you and the needs of your business.

Aggregated data

It was mentioned earlier but of course, there is value in understanding the NPS for your responses in aggregate. In other words, looking at all the customers that responded to your survey, what is their general feeling towards your product or service. This again can be useful for guiding leadership on how aligned the business is in relation to its overall goals. Nudging the NPS for example could be an OKR for both product and service or all kinds of aspects of your business.

When you look at that data in aggregate and then zone in a campaign to say promote a new offering or a new product; you may have, as your intent, incentivization of a particular kind of customer or past customer. Here, knowing where they lie in NPS ranking might be a way you optimize the effectiveness of your outreach or promotion campaign. You may choose to actually ignore your fanbase and focus on trying to convert those still sitting neutral or you may choose to convey a completely different message to the three different camps. What you choose to do, will of course be dictated by what you know and what you have planned.

Surveys and their results can help organizations evaluate the strength of their offering and even their competition. The results can be used to segment and pursue new markets or cross and upsell in existing ones. Ultimately, though, you need to have the data and it needs to be accessible, and usable. With Pretectum you can close the potential gap that exists when you consider your customer master data through too narrow of a lens.

Contact us today to find out how you can get the Pretectum advantage with your Customer Master Data Management.