How is a proof of concept or an implantation of Anjana Data?

Uncategorized, 28 January 2021 |
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At Anjana Data we aim to minimise time-to-market and time-to-value in the proof of concept or implementation of our data governance solution and to be able to demonstrate in a very short time a real return on investment.

We have suffered it in our own meats many times throughout our professional career: acquisition of technology with huge initial investments, implantation plans with gigantic projects, hordes of consultants to configure and test that technology… and then, when you have to give the Go-Live for the switch to production, after many comings and goings, replannings and budgetary adjustments, the results are not as expected, nobody assumes the responsibilities and then the whole strategy is rethought.

For this reason, at Anjana Data we do not believe in this model of huge implantations that extend over time and seek a Big-Bang very difficult to manage and, on the contrary, we advocate pilots and implementation plans based on the same philosophy of agile methodologies, looking to demonstrate real value in a very short time.

In addition, in order to demonstrate this real value, the implementation of Anjana Data is not reduced to the technical tasks necessary to implement the solution but we seek to cover the end-to-end from the analysis of the need to the realization of a first case of use in production that allows us to obtain the first measurable results.

So how do we do a proof of concept at Anjana Data?

First of all, we try to understand as best as possible the customer’s needs and their main pain-points and we start working together with him on a proposal to use Anjana Data tailored to your requirements, normally offering different alternative configuration and use of the solution within the capabilities of Anjana Data.

Then, with the aim of drawing up a detailed work plan with defined activities, milestones and deadlines, we try to narrow down and define as best as possible the implementation scenario, also identifying a series of success metrics that can demonstrate quantifiably what has been achieved and the value achieved.

To achieve this goal, we follow a series of steps that can be grouped into the following blocks:

1.- We chose a case of limited use.

A use case or use case diagram is what is commonly understood as the description of the activities that someone or something must perform to carry out some process.

In this context, within this first point we must select a use case where Anjana Data covers the identified needs and its incorporation into the technological stack represents a differential added value. The detailed description of the use case is very important because it will allow us to define the scope of the initial implementation and we will be able to measure what we have achieved to sell it internally.

Here are some examples of use cases:

  • A specific information domain, for example customer contactability data or financial data related to contracts.

  • A specific data initiative or project, for example the creation of a sandbox for advanced analytics or the creation of an MDM of product data.

  • A regulatory case, for example related to GDPR or RDA.

  • An end-to-end information exploitation process such as the generation of a recurrent management report or the generation of the income statement.

  • A specific technological environment such as a Data Lake, a Cloud environment or an Analytics area.

There is no one use case that is better than another; the selection of the use case will depend entirely on the needs of the organization, the importance it may have for senior management, the complexity of its execution or the ease of involving stakeholders, among other variables.

2.- We delimit the technological scenario involved.

Based on the chosen use case, it is important to delimit the technological scenario involved in this use case, since the more delimited the proposed and less technologies involved, the less complexity we will incorporate into the initial implementation plan.

Uno de los puntos diferenciales de Anjana Data radica en la integración nativa extendida con otras tecnologías para incorporar la solución de gobierno del dato como el eje central del ecosistema de datos. Esto hace que este punto sea especialmente delicado y es muy importante no caer en el error de querer abarcar demasiadas tecnologías en la fase inicial porque en las integraciones tecnológicas hay muchas aristas que pueden hacer que el piloto o plan de implantación se complique y se retrase.

Among this, it is important to identify the following technologies: Repositories for data storage. 

  • Systems of data processing. 
  • ETLs and data services. 
  • Exploitation tools and BI. 
  • Systems of management of identities. 
  • Systems of management of permits.

3.- We identified the key stakeholders.

At this point, the people involved must feel empowered to make decisions and see themselves as part of the process of change that is about to take place in the Organization, perceiving the value of it and in turn, taking on a number of responsibilities around the data they may not have had until now.

It is very important to make stakeholders see that the government of the data does not consist of “putting sticks in the wheels” or “doing bad cop” is to equip the organization with the necessary skills to generate value for the business through better use and processing of data. It is essential to provide them with the necessary tools and resources, because without them, their workload will increase and they will not see a quick return.

That is why during the pilot or implementation plan of Anjana Data it will be necessary to work on training and change management with the different stakeholders identified.

4.- We define the success metrics.

Success metrics will help us to demonstrate quantitatively what has been done and the value achieved. These metrics will also depend on the selected use case but as a general rule we can classify them into the following groups:

  • Reuse of data. 
  • Satisfaction of the stakeholders. 
  • Cost savings. 
  • Improved efficiency and productivity. 
  • Reduction of operational risk. 
  • Regulatory compliance (if applicable). 
  • Data monetization (if applicable).

The Anjana Data pilot or implementation plan

Con todo esto, esbozamos un plan de proyecto con un plazo de duración determinada (aproximadamente 3 meses) el cual se acuerda con el cliente antes de arrancar. Dentro de este plan, se suelen incluir las siguientes actividades:

  • Assessment of infrastructure and architecture and proposal of technical design. 
  • Deployment of all services according to the chosen deployment model and configuration of connections with the client’s systems. 
  • Landing of the selected use case and support in the definition of the configuration of Anjana Data to meet the needs of the customer (governance model and metamodel). 
  • Configuration of Anjana Data as defined. 
  • Training and change management sessions. 
  • Accompaniment in the first loads of information, functional tests and execution of the case of use. 
  • Review of success metrics and generation of conclusions.

And what do we get out of this way of working?

Thanks to this approach, not only do we manage to minimize time-to-market and time-to-value in the implementation of our data governance solution, but this also allows us to demonstrate in a very short period of time a real return on investment.

On the other hand, we managed to empower both the organization and the stakeholders so that they can evolve in their implementation of the government of the data according to their needs and requirements and so that they can also extend the coverage of Anjana Data to more cases of use independent, resulting in a reduction to the maximum of the dreaded vendor lock-in, from which we try to flee as much as possible.

In addition, we always certify the implantations of Anjana Data and until it is certified, does not begin the validity of the licenses of use of the solution, which represents our commitment to our customers and our confidence that Anjana Data meets expectations and meets identified needs.

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About the Author: Angela Miñana Francés
(angelamf@anjanadata.com)


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